#i doubt they would do a recast for this specific game though

[sonknuxadow]

i was so excited about the shadow levels and what stuff from his backstory that we could see and black doom being the main villain that for a moment i lived in a world where the worst voice actor shadow has ever had wasnt still in the role

#NOTHING AGIANST THE GUY idk anythign about him and i think hes a good va for other characters hes just not my shadow #maybe if he has better material to work with he'll sound better i dont know .... #but i wouldlove to see david or jason come back. or maybe even the guy who voiced him in prime #actually i think david has shown interest in coming back to the sonic franchise if sega would let him. let him in please #i doubt they would do a recast for this specific game though #because i remember for sonic colors ultimate and all content related to it they used the exact same voice cast as sonic colors #even if a couple recasts have happened between colors and colors ultimate #so. im sure theyre still going to want that voice consistency here and arent going to give shadow a different va from sonic generations

[snowflake-of-destruction]

Fanfic ask game: Q 👀 👀 👀

I’m kidding, I’m kidding, how about M?

Q: How do you feel about collaborations?

I have a lot of thoughts on this one, rambling on far longer than the short answer I’ll give now.

Sharing ideas and feeding off of each other’s creativity is fantastic, it fills a different facet of that storyteller instinct, and it creates a special bond when you weave that tapestry together. However, there can be at times frustration in compromise when you realize a story is not completely within your control--though with the right partner and open communication that can be avoided--and the worry of letting someone down no matter what you do, always present just when you think about audience, is amplified and magnified when you now have a specific person, presumably one you respect and care about if you are writing with them who has just as much stock in the story as you and is now stuck with you.

That’s the writer side. Now the reader side of collaborations is unbound enthusiasm to see people you know and like joining their powers, though, I’ll admit when it’s writer/writer collaborations and not writer/artist power duos I am automatically (and now hypocritically) skeptical until I read a few chapters to see how they meld styles and make a narrative cohesive.

M. Got any premises on the backburner you care to share?

Oh so many, but let’s talk about a couple of my favorites, though I doubt it will be anything I haven’t shouted about before. PLEASE click these links and talk to me about any of these

The Sailor and Siren AU

Sk8 the Infinity Train

Expanding on the Superhero Story

A post Episode 9 story where the full swing kiss caused more damage and Cherry wakes up believing it’s 8 years ago and he’s still dating Adam.

Matchablossom Fairytale Fridays….which actually predates all these other ideas. Joe and Cherry fall asleep during a Disney movie marathon they are having with Reki, Langa, Miya, and Shadow and end up each dreaming about a series of fairytales and Disney tales recast with them and people they know (ala Cindereki), each one teaching them something about themselves or each other. The premise is every Friday would center around a different story. I would do words and @shaky-mayhemm would do illustrations.

The Affair AU/Lovematcha Tries to Love Smash-a AU. Lovematchablossom. Post-canon where they had worked out their issues and were just starting to re-navigate a possible relationship as more than friends when a series of miscommunications (starting with Ainosuke getting married, which Ainosuke himself doesn’t see as a problem to other pursuing other relationships, but you can image sent...um...mixed signals) causes Kaoru to give up on Kojiro and Ainosuke and seek happiness elsewhere. Fast forward to Kaoru announcing he’s getting married and Kojiro and Ainosuke panicking/deciding to break up the engagement and plan one last bid with grand romantic gestures to win back Kaoru. Collaboration with @twileighplants conceived after THIS BACK AND FORTH during the original Six Sentence Fic day.

OH WAIT, DOES ANYONE REMEMBER THAT TIME I STARTED A MULTI-CHAPTER FIC AND THEN FORGOT IT BY THE NEXT DAY?

And that’s just for sk8. Please ignore the poor orphaned children begging outside my window dressed as Sora.

#fanfic writer ask #matchablossom #renga #lovematchablossom #loveblossom

[reflectionsofacreator]

So like. I kinda sat down to write about this one, and I feel like I don’t know what to write about. There’s a lot to write about, but like... [scrubs face] it’s like, there’s a lot of emotional (sledge)hammers with this one, and it’s hard to pick apart so I can actually talk about it. Paralyzed by there being so much, you know? 

God writing this one was like pulling teeth, tbh. 

Buckle up lads, this one clocks in at over 2k. Mobile users I’m so sorry. 

I think the first thing I’m gonna tackle is the name of this one. It’s called The Truth, but in the context of Clay, that previously had an incredibly specific meaning. “The Truth” wasn’t so much a phrase as it was referring to the real truth of the Precursors and the nature of Eve and Adam, and the truth of humanity as a whole. Historically, every mention of “The Truth” around Clay refers to that specific idea, and now we have a new thing that uses the same name. It’s kind of interesting too, because the Truth that Clay shared was very explicitly something he was giving to other people, after learning about it for himself. And in this case, this is Truth that he’s being given, either about his situation, or the situation of his successor. 

This memory opens up with a doctor and Warren Vidic talking, after the episode that Clay had with the Bleeding Effect, and the doctor makes mention of Clay having been here a year already. He administers a medicine that’s actually an anti-psychotic, as a way of trying to stabilize Clay’s deteriorating mental state. There’s no guarantee that it’ll actually work, is the issue, mostly because the Bleeding Effect isn’t exactly a well known mental condition, and what everyone knows about it is simply what they’ve found out via the Subjects. Which is a very small group of people. I do wonder, though, about the Bleeding Effect as a .. hmm, genetic thing? It’s seeing the memories of your ancestors superimposed over your own perception of the world, and it’s implied that it’s because of the Precursor DNA that you can even have that happen, because it’s linked to Eagle Vision. Or at least, that’s what I’ve gotten so far, I could be completely wrong. 

The conversation with the doctor gets shooed away in favor of a conversation between Clay and his father, and like. I really wonder at the timing of it, if it’s supposed to be a conversation that Clay had while he was in Abstergo. It’s possible that it was a conversation that happened before Clay got sent in, but he sounds too resigned and weary I feel like, to have it happen outside of his imprisonment. Another reason why I feel like it’s after is because the last conversation we heard with Clay and his father was during the Bleeding Effect, when Clay was telling him about the Assassins, and things dissolved into a fight when Harold made it about money. This conversation feels like it’s a while after that, after Clay’s resigned himself to not being able to really convince his father of anything. 

Before Clay dives into the mainframe, there’s another glitch, which causes your controller to rumble. The screen goes noisy, and what shows is an exit at the end of a long walkway. This isn’t the first time we’ve seen glitches or hallucinations, but it’s freaky literally every time. 

We watch as Clay starts to hack through Abstergo’s systems after that, and the actual design of “going into” the mainframe is covered in a dozen different firewalls. It’s a neat sort of visual way to show just how hard Clay’s hacking is, as well as how many firewalls there are, because if he gets caught, he can get killed. 

Right before he goes in, on the right side of the “mainframe” is a code cipher. 

This is a Caesar cipher with an alphabetical shift of 3, and it reads  "Lucy, she Is aLways behind You." The capital letters spell out LILY -- traditionally lilies were associated with death. Now, you could interpret this as “Lucy’s got his back, she’s his teammate.” Which like, maybe. But with the addition of the word lily, and knowing that Lucy betrays him... nah. It’s more like she’s a threatening presence that needs to be watched. 

Clay snoops through Vidic’s mainframe and learns that Vidic is specifically after Desmond. Now, we know that this is at least over a year of Clay’s being here, and that Desmond was captured September 1st. What I’m really saying is just how long did Abstergo know about Desmond, and what lengths did they go to research him before they took him? Another question I have is like -- I know ac1 said that Abstergo found him via his fingerprints for his motorcycle license, but just how would that give them access to his genetic profile. Granted, that’s probably some early installment weirdness of ac1, but. (That being said, I remember reading a fic where they made mention of Desmond donating plasma for cash, and that’s how Abstergo found him, which is more believable than fingerprints....) 

I also can’t help but wonder like -- what’s going through Clay’s mind as he realizes that the Desmond Miles that Juno spoke of during his Bleed is the next Subject, and his successor? Or is it that he was completely unsurprised because Juno gave him a look into the possible future with the Calculations? 

Anyways, Clay finds out what Vidic wants, and excitedly says that they can leave, and we follow the path to see what looks like a broken stone circle at the base of two beams of light. 

(The wireframe is just the gameplay mechanic) I have... no earthly idea what this is, or what it could possibly mean. I think this is the only broken structure you see in all the memories, Desmond or Clay’s. It’s vaguely reminiscent of a broken film wheel, but I’m not sure if that’s what it’s supposed to be. But like, it’s so goddamn conspicuous because it’s the only broken structure we find. ls it supposed to symbolize a broken trust, a loss of faith after witnessing the “play” unfold?? .

Speaking of the “play”-- what the fuck. What the actual fuck. Is it supposed to make me uncomfortable? Because by god it did that. The sharp departure from how the rest of the narrative has been told is jarring as fuck, especially because it’s so like, proper. I swear, all that’s missing is like, a slightly off-key oldtimey music track and you’ll have a full blown horror segment. Maybe I’m just being dramatic, but like -- finding the broken wheel when that’s already something weird, having the camera forcibly taken away from you so you can watch this performance. And like, just listening to Warren monologue at Lucy is disturbing as well, for reasons that are hard to articulate. 

It’s like -- Meta wise, I know why she’s not talking. Her voice actress, Kristen Bell, had left and didn’t renew her contract (as her contract was only for 3 games), thus not being able to voice Lucy for any further appearances. IIRC, this is actually why Lucy was written to die, instead of simply recasting her, and then they had to scramble to make the “She’s a Templar!” twist work. Jury’s still out if it did or not, but like -- I do appreciate them trying to explain why she defected during her undercover years, but like... Ugh. It still leaves such a sour taste in my mouth, because it’s obviously a writing scramble and not a cohesive narrative that was plotted from the beginning. 

For a comparison, Clay’s story and ultimate fate feels complete, it feels alright. Yeah, it’s arguably a worse fate than Lucy, he died twice over, but like. We knew he was dead from the first moment we saw him, we knew that there was only one way that this could really go, a tragedy. There was a clear progression of his story, and the fact that you know how it ends. That being said, I do wonder about Clay’s death as a Subject in ac2, before the plotbeats of Lucy being a Templar were set in stone for Brotherhood. I know that the 20 glyphs in ac2 did talk about how Lucy was there when Clay killed himself, but I kinda doubt that it was in the same context of “she was supposed to save him but deliberately betrayed him due to her loyalties”. I guess what I’m getting at is that Lucy’s story feels terrible due to the writing surrounding it, while Clay’s feels deliberately terrible because that was the point. 

Back to my original point of “Lucy not talking”-- while there is a meta reason for it, I kinda want to ascribe a narrative reason, despite the meta outweighing the narrative. 

Lucy is characterized by almost never showing the full extent of her feelings or motivations, leaving you to wonder what’s actually going on in her head constantly. Sure, she leaned on Desmond a lot, but there’s also an undercurrent of a power imbalance there, and we always got the sense that she kept more to herself than she revealed. By having Warren talk at her, we’re further kept from knowing just what she felt about all of this, and instead we’re given another glimpse of the strange relationship that Warren and Lucy had. 

Warren was her boss, but also her superior in the Templar order, and the man who saved her life from his own company. Back in ac1, Lucy recounts to Desmond how she was attacked in the middle of the night, going to be silenced by Abstergo so she couldn’t talk about the Animus, only for Warren to save her life by telling the men to stand down. The assailants were people that she interacted with every day, even ate lunch with. This is after she’d been with Abstergo for a while, and finally feeling like she was being taken seriously with her work (as well as her undergrad thesis/work) she was going to be killed to keep quiet. We don’t actually know why Warren saved her, but it’s my firm belief that that’s when Lucy changed alliances to the Templars.

However, I do wonder about the confrontation between Lucy and Warren at the end of ac2, during the credits. I know, I know, her being a Templar wasn’t really a thing in ac2 (I think), so therefore you have to take it all with a grain of salt, but like. The conversation here brings attention to it, where Warren tells her “Make sure you look very upset. You need to be convincing.” And I can’t help but wonder if Warren and Lucy ended up trading insults that hit way too close to home in order to further the deception... It wouldn’t be hard to pretend to be hurt if she actually was hurt by what he said, y’know? 

I think the last thing about Warren’s speech that really bugs me is like -- he tacks on the whole “Oh, yes. Once inside their hideout, perhaps you might ask the Assassins why they left you alone for so many years.” And like. That just gets under my skin in a lot of ways because like-- he’s got a point, the Assassin’s methods are Rather Horrible™ with how they completely cut her off for a deep cover mission at seventeen (no I will not ever be over that), but the way he says it just. He’s clearly manipulating her to entrench her further onto his own side, and I just. Ngh. I kinda wonder if the delivery of the line was intended for the audience rather than Lucy herself, because she already knows all this, and for him to bring it up feels like an insult to her intelligence. It feels kinda slimy in a way that I can’t really describe. Or maybe it’s just because I just do NOT like Vidic. 

There’s also the question of like, how did Clay see this -- this is all dramatized for the sake of us, the audience, but did he watch this via video feeds or something??? The thought of him watching Lucy and Warren talk about his successor is kinda jarring tbh. Also this throws a wrench into the ending of ac1 (though tbh what DOESN’T throw a wrench into ac1) where they were going to dispose of Desmond only for Lucy to intervene. Is it because Warren and Lucy were operating on their own project that wasn’t exactly approved by the Templar higher ups?? Or something?? 

This whole memory says that Desmond was their goldmine for the amount of genetic information he held, so why would the higher ups -- wait. Unless the whole thing was a ploy by having Lucy speak up in “defense” of Desmond in order to get him to trust her some more.... Hrm.... Granted that fits, it’s just a sort of way of re-contextualizing the ending of ac1... 

Waves hand anyways Clay finds out about this plan for Lucy to gain Desmond’s trust and give them the data, and then we finally have control again. There’s this sort of distorted error noise, and the red blocks start to fill up the room, threatening you as they force you closer and closer to the screen, which only shows a picture of a door with a strange symbol on top of it. 

This is the symbol for 3 Juno, an asteroid in our solar system that’s the 11th largest, and contains 1% of total mass of the asteroid belt. It was discovered September 1st, 1804, by Karl Ludwig Harding, and initially considered to be a planet, along with a few other asteroid/dwarf planets at the time. It was given this symbol, ⚵, like how Mercury, Venus, and Jupiter all have their own symbols. 

Aside from the obvious “hey that’s Juno, she’s the big bad of this shit”, there’s a couple things that stood out to me. The date of discovery, September 1st -- that’s the same date that Desmond got captured by Abstergo, gives me pause. I’m not sure if it’s something that was intentional on the dev’s part, or if they were just looking for a symbol that would represent Juno. Either way, that’s enough of a coincidence that it makes me feel unsettled, the same way that Lucy was bothered by the date of the satellite launch being 72 days away. It might just be an honest coincidence, but considering that this is Clay we’re dealing with... nah. 

Another thing that the AC wiki told me is that this is also the symbol for the Instruments of the First Will, an in-universe religious organization that worships the Precursors, and specifically Juno. Now, this organization doesn’t actually appear until at least ac4 Black Flag, and continues on all the way through Syndicate. This is more like an early bird cameo than a full blown reference, as we still have to get through ac3, But it’s still interesting to point out and look at, and wonder what’s going on with it all. 

Anyways, the door itself is actually part of the screen, and impassible, and it stays that way as the bricks come closing in, chasing you. It’s really tense tbh, with this feeling of claustrophobia on top of the revelations you were forced to watch. It also doesn’t help that like. You had control wrenched away from you so you could watch the conversation, and the speech was long enough to lull you into maybe putting your controller down to watch, and then with a rumble you suddenly have control again and are being chased towards a door that doesn’t open. 

The picture of a door becomes an actual door after the blocks get closer and closer, and we break through into the light, and onto memory 7.

If you like what I do, or want to see any other sort of analysis, consider buying me a ko-fi!

#Lucy Stillman #Clay Kaczmarek #Assassin's Creed #fuck it this goes in the main tag cause i'm proud of it #i'm so fucking sorry mobile users #motherfucker unlimited #creator plays ac rev #creator plays ac lost archive

[loveydoveypiperwright]

The rest of the group headed below deck, leaving the mess to one of the reformed criminals to clean up. Elkiries stood, watching Nathaniel clean. She offered her help, but he refused. Elkiries shrugged it off, standing by the far end of the deck near the Bowsprit. 

The sunset was a thing of wonders, littered with oranges, reds, and pinks. Elkiries sighed, lying her glaive on top of the ledge to keep her arms from leaving burn marks into the wood. She leaned over, gazing at the sea. Just a night and a half till we hit land, it shouldn’t be long.

A pair of footsteps came near, Elkiries turning her head to look. Alas, it was the half-elf whom she had protected from Dallas earlier. The half-elf woman immediately looked down as they met each other's gaze, but she found her place beside Elkiries.

"Hello, Selmene. Is there something you need? Dallas isn't bothering you again, is he? Elkiries kept her eyes to the water.

The half-elf woman laid her arms on the golden railing, "N-No. No. He isn't. I just..." She rubbed her foot along her shin, "I wanted to thank you for what you did earlier. I didn't expect one of your kind to do what you did, especially after what I said."

"I detest those who believe they can keep others under their boot. I realize he wants to stop you from creating potential termoil towards myself, the twins, and our cleric, but he's just feeding the flame."

"Ah." Selmene was silent after that, the sound of the sea filling their ears.

Elkiries turned to her, "You're free to leave if you wish. I doubt you'd want to spend more time than that is due around 'my kind.' I won't keep you."

Selmene fiddled with her left wrist, "Actually, you're not that bad for... For..." She shook her head, raising her hand to her lips, a slight shiver overcoming her. "Well, you're okay. I'm free to avoid the high elves, and your half-elf seems to stick to that ginger man more than anyone else in your group."

"I'm glad they won't be a problem for you then." Elkiries smiled, turning back.

"Will, you, uhh, be coming back to the dining room? I assume supper will be hosted soon before we retire to the cabins."

Elkiries gestured to her head of fire, "If I do, I'll likely set the boat aflame. I'll have to wait till it's possible to swap into another form before I can meet with everyone below."

"And what of your wound?" Selmene pointed to her shoulder, gesturing around it. "Are you just going to let it fester? What if... the giant ant was poisoned!

Elkiries looked to her right, thinking. "It likely was, but," She breathed a heafty sigh, "If anyone tries to touch me, they'll burn their hands. I don't want to harm anyone."

"I-I can try to help, I have an idea."

"And that would be?"

"I could shield my hands in flame, then heal you. Y'know, if it works. May I see your arm?"

"There's nothing wrong with my arm."

"A test run, of sorts."

Elkiries, with furrowed brows, lifted her arms off her glaive, facing Selmene.

After a moment, flame shrouded her hands. She reached out to touch Elkiries' arm, Elkiries hesitant to her touch, jolted her arm back. "Rrgh, sorry." She added.

Selmene slowly reached her hand out, clasping her hand on her arm for a moment before retreating.

"Did it work?"

"There's a harsh sting, but I think I'll be able to help you. You'll have to take off your chainmail shirt, though."

"If I must." Elkiries begun to remove her armor, lifting the chain mail till half of it rested on her shoulder, exposing the wound.

Selmene placed her hands on the wound, enduring the pain as she wove her healing magics upon the wound.

"Forgive me, but" She paused for a slight moment, "How does your armor and garments not catch fire when you're in this state?"

"My people have already mastered how to make non-flammable clothing. The metal rings are made of steel so they don't melt."

"Your people..." She cringed, thinking of them, "Isn't that armor heavy then?"

"You get used to the weight. My pauldrons and gauntlets are rather heavy too."

"What of your weapon? Has the staff ever caught fire?"

"It's made of stone, sans the blade."

"Wow, that really must be heavy."

"Indeed it is."

"Hey!" A foreign voice called out from below the stairs, to which a short Aasimar woman appeared, saying something to someone behind her. Turning around, she looked over the two, and chuckled.

"Yes, Laila?" Elkiries called to her as she approached.

"Well, isn't this a sight!" Laila let loose another chuckle. "Didn't think the two of you would ever get so close. A top off already. Anyway, the cooks will have supper laid out and ready in a few moments. Feel free to join us if you get the chance. Do either of you want a specific drink waiting for you once you head down?"

Elkiries would roll her eyes if she had irises, but she only shook her head. "Mango juice, if the kitchens have it. And you, Selmene?"

Selmene popped her head up from behind Elkiries shoulder, face red. "I-I'll make my own tea once we head down."

"You sure?" Laila sprung.

Selmene simply nodded her head.

"Okay then, I'll see you two in the dining room then. Soon, hopefully."

"Hopefully." Elkiries added. With that, Laila turned on her heel, heading back towards the stairs.

Selmene took the next minute or two working on the wound; working on it was a challenge. She had to work between recasting fire to her hands, the hardy sting, and having to nudge away the hot chainmail as she worked. Alas, she finished quickly and apologized for taking so long, letting Elkiries put her armor on again.

"It's alright, thank you for aiding me." Elkiries fashioned her armor back to it's original spot, flattening it out. "I'll stay out here till I change back, you can head back down.

"Well, alright. Don't burn down the sails." With that, Selmene left Elkiries and headed below.

"I won't." Elkiries huffed, leaning back on her glaive, looking out to the sea.

-------

Selmene headed below deck, towards the dining area to grab their drinks. As she entered, Dallas, Laila, their cleric 'Theira', the ginger man 'Albin', a dwarf, a half orc, a goliath, a half elf, two high elves, and five humans sat around a large table, eating multiple meats, pastas, vegetables, and breads that had sat in the middle of the table.

Selmene noticed Elkiries' pack at the end of the table beside Dallas, and her seat beside Laila. Alas, all that sat in their places was a glass of mango juice. After making a quick cup of tea, Selmene sat down beside Laila, grabbing her fair share of food as it was passed around.

"So, Selmene," Laila piped, "Is Elkiries still..." She tucked a bit of the end of her shirt up and gestured above her.

"No, she's not. She's just... Still... On fire..."

Laila nodded her head with food in her mouth, "Gotcha'."

Dallas paused flipping through Elkiries journal, leaning his body towards Selmene, "What's that mean, the whole," He mimicked the motion Laila had done with the best of his ability with his curiass, "thing?"

To which Selmene and Laila said at the same time, "Nothing!"

Dallas squinted, "Ooookay. Sure." He continued, eating as he read what she had written down in her journal. Selmene eyed the journal, watching him eat beside it. After a bit, she reached over and grabbed the journal from him, holding it.

"Wha-"

"If you keep eating over that thing, you'll get food all over it! I doubt she'll want that!"

Dallas squinted at her, "Since when were you buddy buddy with her? Just earlier you were calling her 'Heathens... Scum... Cursed beings' while you tried not to throw up!" Her reached back for the journal, swiping it back.

Her expression soured, "I-"

"My family! Cursed! It'd be best if you swapped seats." Dallas mimicked, bringing his hands to his mouth.

The feeling to vomit pulled at her, bad memories flooding to her. She reached back for the journal, tucking it under her arm, and running out of the dining room with her tea. Dallas got up to give chase, nearly tripping over Laila as she tried to stop him.

All Laila managed was to grab onto his wrist, "Dallas, enough! She isn't going to hurt Elkiries or any of us, just leave it alone. Leave her be!"

Dallas shook his arm free, chasing after Selmene without a word.

------

"Elkiries!" Selmene shouted, running across the deck.

"What is it?" Elkiries shouted back, watching her head towards her, Dallas on her tail.

Selmene hid behind her, Dallas stopping short of the two. "C'mon, Selmene, we're just eating supper. Join us again!"

"No!"

"Selmene..." Dallas brung his hand to rub the corners of his eyes, "Ugh, Elkiries, will you convince her to come back?"

"No. Why are you chasing her?"

"She wouldn't eat and I'm simply concerned for her!"

"That's not it!" She shouted, "You wanted her journal! I won't let you ruin it!"

Dallas sighed, rolling his eyes. "Why do you care? Elkiries will let me look through it if I wanted too. It's not like you'd ever let yourself to be friends with her."

"Yes," Elkiries stepped forward, "I would let you read it if you wanted, but there's a thing called asking. Looks to me she's doing just fine speaking with me. Quit antagonizing her, Dallas."

"You're not concerned that she's not playing some mind game with you? She could turn on you, on Theira, or any of us at any minute."

"No, I'm not. Leave this, Dallas."

Dallas huffed, trying to peer behind her with a glare. "At least come back for dinner, Selmene. Enoughs enough up here."

"I said no!"

"Selmene-"

Elkiries grabbed her glaive off the ledge, pointing her blade at his chest.

"Dallas!" Laila shouted from the stairs.

"Fine, fine." He turned, heading towards her.

-------

"Now, what was that about?"

Selmene looked up from the side of the ship, wiping the edge of her mouth. She handed Elkiries her journal, before taking another hurl into the sea.

Elkiries held it in her hand, checking it over. "My journal?"

She brung her head back over the ledge, "Y-Yup. He was eating over it and I-I doubt you'd want it damaged."

"Thank you, then. That's all?"

"Well... No. He brung up what I said earlier and I don't want to relive awful family memories, so I just.... Ran." Selmene looked to Elkiries, trying to dig through her yellow scleras that lacked irises.

"I'm sorry that happened. We'll be at the strange continent soon enough." As she finished, her hair turned into Autumn reds and oranges, falling down to her sides.

A small chuckle escaped Selmene's lips, "Heh, you look like you just woke up."

Elkiries grumbled, beginning to braid back her bangs to tuck away behind her ears, "Took myself long enough."

"I'll say."

Elkiries moved onto the larger mass of her hair, pulling it all together in one large braid. She grabbed a piece of twine from her pocket, tying it around the end.

"If you'd like me to escort you down, we can fill up on supper now if you'd like."

"Fine. You know where to sit."

"Right." Elkiries grabbed her glaive, heading below deck with Selmene.

#Natty rambles #Elkiries #Eladrin problems lmao #Would you look at those potential girlfriends wowie wowie wowie #Dallas doesnt mostly act like that but I live for ✨ drama ✨✨ that t e a ✨✨✨ #Well he sorta does #But lowkey #Ah well lol #Selmene isnt even a cleric shes a wild magics sorcerer but I shall take my creative liberties as I please lmao #Nearly midnight bitcheeeesss

[presssorg]

Twitter terror: Arrests prompt concern over online extremism

Twitter terror: Arrests prompt concern over online extremism GREECE, N.Y. — A few months after he turned 17 — and more than two years before he was arrested — Vincent Vetromile recast himself as an online revolutionary. Offline, in this suburb of Rochester, New York, Vetromile was finishing requirements for promotion to Eagle Scout in a troop that met at a local church. He enrolled at Monroe Community College, taking classes to become a heating and air conditioning technician. On weekends, he spent hours in the driveway with his father, a Navy veteran, working on cars. On social media, though, the teenager spoke in world-worn tones about the need to “reclaim our nation at any cost.” Eventually he subbed out the grinning selfie in his Twitter profile, replacing it with the image of a colonial militiaman shouldering an AR-15 rifle. And he traded his name for a handle: “Standing on the Edge.” That edge became apparent in Vetromile’s posts, including many interactions over the last two years with accounts that praised the Confederacy, warned of looming gun confiscation and declared Muslims to be a threat. In 2016, he sent the first of more than 70 replies to tweets from a fiery account with 140,000 followers, run by a man billing himself as Donald Trump’s biggest Canadian supporter. The final exchange came late last year. “Islamic Take Over Has Begun: Muslim No-Go Zones Are Springing Up Across America. Lock and load America!” the Canadian tweeted on December 12, with a video and a map highlighting nine states with Muslim enclaves. “The places listed are too vague,” Vetromile replied. “If there were specific locations like ‘north of X street in the town of Y, in the state of Z’ we could go there and do something about it.” Weeks later, police arrested Vetromile and three friends, charging them with plotting to attack a Muslim settlement in rural New York. And with extremism on the rise across the U.S., this town of neatly kept Cape Cods confronted difficult questions about ideology and young people — and technology’s role in bringing them together. —— The reality of the plot Vetromile and his friends are charged with hatching is, in some ways, both less and more than what was feared when they were arrested in January. Prosecutors say there is no indication that the four — Vetromile, 19; Brian Colaneri, 20; Andrew Crysel, 18; and a 16-year-old The Associated Press isn’t naming because of his age — had set an imminent or specific date for an attack. Reports they had an arsenal of 23 guns are misleading; the weapons belonged to parents or other relatives. Prosecutors allege the four discussed using those guns, along with explosive devices investigators say were made by the 16-year-old, in an attack on the community of Islamberg. Residents of the settlement in Delaware County, New York — mostly African-American Muslims who relocated from Brooklyn in the 1980s — have been harassed for years by right-wing activists who have called it a terrorist training camp. A Tennessee man, Robert Doggart , was convicted in 2017 of plotting to burn down Islamberg’s mosque and other buildings. But there are few clues so far to explain how four with little experience beyond their high school years might have come up with the idea to attack the community. All have pleaded not guilty, and several defence attorneys, back in court Friday, are arguing there was no plan to actually carry out any attack, chalking it up to talk among buddies. Lawyers for the four did not return calls, and parents or other relatives declined interviews. “I don’t know where the exposure came from, if they were exposed to it from other kids at school, through social media,” said Matthew Schwartz, the Monroe County assistant district attorney prosecuting the case. “I have no idea if their parents subscribe to any of these ideologies.” Well beyond upstate New York, the spread of extremist ideology online has sparked growing concern. Google and Facebook executives went before the House Judiciary Committee this month to answer questions about their platforms’ role in feeding hate crime and white nationalism. Twitter announced new rules last fall prohibiting the use of “dehumanizing language” that risks “normalizing serious violence.” But experts said the problem goes beyond language, pointing to algorithms used by search engines and social media platforms to prioritize content and spotlight likeminded accounts. “Once you indicate an inclination, the machine learns,” said Jessie Daniels, a professor of sociology at New York’s Hunter College who studies the online contagion of alt-right ideology. “That’s exactly what’s happening on all these platforms … and it just sends some people down a terrible rabbit hole.” She and others point to Dylann Roof, who in 2015 murdered nine worshippers at a historic black church in Charleston, South Carolina. In writings found afterward, Roof recalled how his interest in the shooting of black teenager Trayvon Martin had prompted a Google search for the term “black on white crime.” The first site the search engine pointed him to was run by a racist group promoting the idea that such crime is common, and as he learned more, Roof wrote, that eventually drove his decision to attack the congregation.

The latest on Sri Lanka's bombing investigation Israel's Counter-Terrorism Bureau issued a travel warning for Sri Lanka on Thursday, raising the threat level to indicate a "high concrete threat," ... In the Rochester-area case, electronic messages between two of those arrested, seen by the AP, along with papers filed in the case suggest doubts divided the group. “I honestly see him being a terrorist,” one of those arrested, Crysel, told his friend Colaneri in an exchange last December on Discord, a messaging platform popular with gamers that has also gained notoriety for its embrace by some followers of the alt-right. “He also has a very odd obsession with pipe bombs,” Colaneri replied. “Like it’s borderline creepy.” It is not clear from the message fragment seen which of the others they were referencing. What is clear, though, is the long thread of frustration in Vetromile’s online posts — and the way those posts link him to an enduring conspiracy theory. —— A few years ago, Vetromile’s posts on Twitter and Instagram touched on subjects like video games and English class. He made the honour roll as an 11th-grader but sometime thereafter was suspended and never returned, according to former classmates and others. The school district, citing federal law on student records, declined to provide details. Ron Gerth, who lives across the street from the family, recalled Vetromile as a boy roaming the neighbourhood with a friend, pitching residents on a leaf-raking service: “Just a normal, everyday kid wanting to make some money, and he figured a way to do it.” More recently, Gerth said, Vetromile seemed shy and withdrawn, never uttering more than a word or two if greeted on the street. Vetromile and suspect Andrew Crysel earned the rank of Eagle in Boy Scout Troop 240, where the 16-year-old was also a member. None ever warranted concern, said Steve Tyler, an adult leader. “Every kid’s going to have their own sort of geekiness,” Tyler said, “but nothing that would ever be considered a trigger or a warning sign that would make us feel unsafe.” Crysel and the fourth suspect, Colaneri, have been diagnosed with Asperger’s syndrome, a milder form of autism, their families have said. Friends described Colaneri as socially awkward and largely disinterested in politics. “He asked, if we’re going to build a wall around the Gulf of Mexico, how are people going to go to the beach?” said Rachael Lee, the aunt of Colaneri’s girlfriend. Vetromile attended community college with Colaneri before dropping out in 2017. By then, he was fully engaged in online conversations about immigrants living in the U.S. illegally, gun rights and Trump. Over time, his statements became increasingly militant. “We need a revolution now!” he tweeted in January, replying to a thread warning of a coming “war” over gun ownership. Vetromile directed some of his strongest statements at Muslims. Tweets from the Canadian account, belonging to one Mike Allen, seemed to push that button. In July 2017, Allen tweeted “Somali Muslims take over Tennessee town and force absolute HELL on terrified Christians.” Vetromile replied: “@realDonaldTrump please do something about this!” A few months later, Allen tweeted: “Czech politicians vote to let citizens carry guns, shoot Muslim terrorists on sight.” Vetromile’s response: “We need this here!” Allen’s posts netted hundreds of replies a day, and there’s no sign he read Vetromile’s responses. But others did, including the young man’s reply to the December post about Muslim “no-go zones.” That tweet included a video interview with Martin Mawyer, whose Christian Action Network made a 2009 documentary alleging that Islamberg and other settlements were terrorist training camps. Mawyer linked the settlements, which follow the teachings of a controversial Pakistani cleric, to a group called Jamaat al-Fuqra that drew scrutiny from law enforcement in the 1980s and 1990s. In 1993, Colorado prosecutors won convictions of four al-Fuqra members in a racketeering case that included charges of fraud, arson and murder. Police and analysts have repeatedly said Islamberg does not threaten violence. Nevertheless, the allegations of Mawyer’s group continue to circulate widely online and in conservative media. Replying to questions by email, Mawyer said his organization has used only legal means to try to shut down the operator of the settlements. “Vigilante violence is always the wrong way to solve social or personal problems,” he said. “Christian Action Network had no role, whatsoever, in inciting any plots.” Online, though, Vetromile reacted with consternation to the video of Mawyer: “But this video just says ‘upstate NY and California’ and that’s too big of an area to search for terrorists,” he wrote. Other followers replied with suggestions. “Doesn’t the video state Red House, Virginia as the place?” one asked. Virginia was too far, Vetromile replied, particularly since the map with the tweet showed an enclave in his own state. When another follower offered a suggestion, Vetromile signed off: “Eh worth a look. Thanks.” The exchange ended without a word from the Canadian account, whose tweet started it.

A few months after he turned 17 — and more than two years before he was arrested — Vincent Vetromile recast himself as an online revolutionary. —— Three months before the December exchange on Twitter, the four suspects started using a Discord channel dubbed “#leaders-only” to discuss weapons and how they would use them in an attack, prosecutors allege. Vetromile set up the channel, one of the defence attorneys contends, but prosecutors say they don’t consider any one of the four a leader. In November, the conversation expanded to a second channel: “#militia-soldiers-wanted.” At some point last fall the 16-year-old made a grenade — “on a whim to satisfy his own curiosity,” his lawyer said in a court filing that claims the teen never told the other suspects. That filing also contends the boy told Vetromile that forming a militia was “stupid.” But other court records contradict those assertions. Another teen, who is not among the accused, told prosecutors that the 16-year-old showed him what looked like a pipe bomb last fall and then said that Vetromile had asked for prototypes. “Let me show you what Vinnie gave me,” the young suspect allegedly said during another conversation, before leaving the room and returning with black explosive powder. In January, the 16-year-old was in the school cafeteria when he showed a photo to a classmate of one of his fellow suspects, wearing some kind of tactical vest. He made a comment like, “He looks like the next school shooter, doesn’t he?” according to Greece Police Chief Patrick Phelan. The other student reported the incident, and questioning by police led to the arrests and charges of conspiracy to commit terrorism. The allegations have jarred a region where political differences are the norm. Rochester, roughly half white and half black and other minorities, votes heavily Democratic. Neighboring Greece, which is 87 per cent white, leans conservative. Town officials went to the Supreme Court to win a 2014 ruling allowing them to start public meetings with a chaplain’s prayer. The arrests dismayed Bob Lonsberry, a conservative talk radio host in Rochester, who said he checked Twitter to confirm Vetromile didn’t follow his feed. But looking at the accounts Vetromile did follow convinced him that politics on social media had crossed a dangerous line. “The people up here, even the hillbillies like me, we would go down with our guns and stand outside the front gate of Islamberg to protect them,” Lonsberry said. “It’s an aberration. But … aberrations, like a cancer, pop up for a reason.” —— Online, it can be hard to know what is true and who is real. Mike Allen, though, is no bot. “He seems addicted to getting followers,” said Allen’s adult son, Chris, when told about the arrest of one of the thousands attuned to his father’s Twitter feed. Allen himself called back a few days later, leaving a brief message with no return number. But a few weeks ago, Allen welcomed in a reporter who knocked on the door of his home, located less than an hour from the Peace Bridge linking upstate New York to Ontario, Canada. “I really don’t believe in regulation of the free marketplace of ideas,” said Allen, a retired real estate executive, explaining his approach to social media. “If somebody wants to put bulls— on Facebook or Twitter, it’s no worse than me selling a bad hamburger, you know what I mean? Buyer beware.” Sinking back in a white leather armchair, Allen, 69, talked about his longtime passion for politics. After a liver transplant stole much of his stamina a few years ago, he filled downtime by tweeting about subjects like interest rates. When Trump announced his candidacy for president in 2015, in a speech memorable for labeling many Mexican immigrants as criminals, Allen said he was determined to help get the billionaire elected. He began posting voraciously, usually finding material on conservative blogs and Facebook feeds and crafting posts to stir reaction. Soon his account was gaining up to 4,000 followers a week. Allen said he had hoped to monetize his feed somehow. But suspicions that Twitter “shadow-banning” was capping gains in followers made him consider closing the account. That was before he was shown some of his tweets and the replies they drew from Vetromile — and told the 19-year-old was among the suspects charged with plotting to attack Islamberg. “And they got caught? Good,” Allen said. “We’re not supposed to go around shooting people we don’t like. That’s why we have video games.” Allen’s own likes and dislikes are complicated. He said he strongly opposes taking in refugees for humanitarian reasons, arguing only immigrants with needed skills be admitted. He also recounted befriending a Muslim engineer in Pakistan through a physics blog and urging him to move to Canada. Shown one of his tweets from last year — claiming Czech officials had urged people to shoot Muslims — Allen shook his head. “That’s not a good tweet,” he said quietly. “It’s inciting.” Allen said he rarely read replies to his posts — and never noticed Vetromile’s. “If I’d have seen anybody talking violence, I would have banned them,” he said. He turned to his wife, Kim, preparing dinner across the kitchen counter. Maybe he should stop tweeting, he told her. But couldn’t he continue until Trump was reelected? “We have a saying, ‘Oh, it must be true, I read it on the internet,”‘ Allen said, before showing his visitor out. “The internet is phoney. It’s not there. Only kids live in it and old guys, you know what I mean? People with time on their hands.” The next day, Allen shut down his account, and the long narrative he spun all but vanished. —— Read more about the four charged in the New York plot here . AP investigative researcher Randy Herschaft in New York contributed to this story. Geller can be reached at ageller//twitter.com/AdGeller Published at Sun, 28 Apr 2019 14:30:01 +0000 Read the full article

#anonymous #attacks #bombs #censorship #muslims #srilanka #terrorism #twitter

[kennethmontiveros]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effect on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

Artificial Intelligence Will Change How You Do Marketing in 2021 published first on http://nickpontemktg.blogspot.com/

[annaxkeating]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effect on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

from Digital https://unbounce.com/marketing-ai/artificial-intelligence-will-change-how-you-do-marketing-in-2021/ via http://www.rssmix.com/

#digital marketing

[jjonassevilla]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effects on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

from Marketing https://unbounce.com/marketing-ai/artificial-intelligence-will-change-how-you-do-marketing-in-2021/ via http://www.rssmix.com/

#SEO

[josephkchoi]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effects on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

Artificial Intelligence Will Change How You Do Marketing in 2021 published first on https://nickpontemrktg.wordpress.com/

[roypstickney]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effects on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

[itsjessicaisreal]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effects on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

from Marketing https://unbounce.com/marketing-ai/artificial-intelligence-will-change-how-you-do-marketing-in-2021/ via http://www.rssmix.com/

[samanthasmeyers]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effects on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

from Marketing https://unbounce.com/marketing-ai/artificial-intelligence-will-change-how-you-do-marketing-in-2021/ via http://www.rssmix.com/

#Digital Marketing

[reviewandbonuss]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effects on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

https://unbounce.com/marketing-ai/artificial-intelligence-will-change-how-you-do-marketing-in-2021/

[amplesalty]

Friday the 13th Part VI: Jason Lives (1986)

Well, it’s Saturday the 14th now but who’s counting?

It’s been a hot minute since I bad mouthed this franchise but since it was Friday the 13th yesterday, why not dive right back in? I’m still trying to slowly work my through and this marks the halfway point. We do have another Friday the 13th in November but then the next ones aren’t until August 2021 and May 2022 so it might take a while at this pace.

Let’s make no bones about it though, it’s still not good and pretty boring throughout, suffering as Halloween did in its need to do something new that’s exactly the same as it shuns the attempt to make Tommy the new killer and instead brings back Jason from the dead. But that also underlines the saving grace of the film as it pushes slightly into the realm of the absurd which brings some humour and charm to it.

For as much as this movie distances itself from Part V, the opening is very reminiscent of it as two guys go to dig Jason up. Only this time one of them is Tommy Jarvis who is out to exorcise some demons by giving Jason an overdue cremation. I wasn’t sure at first how much retconning was going on, like maybe this was child Jason’s body in the grave but this is adult Jason so presumably this is where they buried his body after Part IV. I don’t know why you would bury him at all though. Later on in the movie, the town sheriff is chewing out Tommy for coming around shouting about how Jason is back from the dead, that the town changed it’s name specifically to move on from the past and the stigma of the Jason killings. So why would you put him in a marked grave? It’s like when they buried Osama Bin Laden at sea to avoid his gravesite becoming some sort of shrine, you just know that every Goth in a 50 mile radius would be coming to hang out at the grave of Jason Vorhees.

Turns out there is a much graver danger attached to having his body laying around though when Tommy digs him up with the intention to burn his body and ‘send him to Hell’. Only, his emotions get the better of him and he starts plunging a metal pole into his body instead. This inadvertently acts as a lightning rod and a sudden freak bolt of lightning serves as the appropriate catalyst to bring Jason back to life like he’s the Frankenstein monster or something. One has to wonder if they had that in mind considering a later scene features the Alice Cooper song ‘Teenage Frankenstein’ that was written for the movie.

This is all pre-title by the way. Upon realising the futility of fighting the monster, Tommy makes his escape and leaves Jason to don his mask as the camera zooms in on one of his eyes. Bizarrely, there’s an effect of his pupil dilating as Jason walks in from off screen in profile, before turning to the camera and slashing. Jason Vorhees taking on the role of 007 once Daniel Craig finally hangs up the Martini glass would be an interesting move...

There’s other moments of humour sprinkled throughout that help brighten things up, like Jason hunting down a bunch of paintballers out on some corporate retreat. One of them is especially nerdish with glasses and goggles, complete with his own comedy soundtrack that seems to follow him around wherever he goes. That is until Jason rips his arm off...

Or the two particularly melancholic kids who seem to have accepted their own fragile mortality at their young age, one suggesting that they’re ‘definitely dead meat’ whilst the other asks what he had wanted to be when he grew up.

But other than that, it is what it’s always been; another round of Jason killing another round of camp councillors. I will say though that still having Tommy around lends it a greater sense of continuity and gives you at least one character that you vaguely care about, everyone else might as well be nameless and faceless machete fodder.

They recast him again for this one, Thom Matthews of The Return of the Living Dead fame taking the role. He seems to be the prevailing image of Tommy given that it’s this version that was used in the Friday the 13th game that came out a few years ago. Personally I preferred John Shepherd in Part V as I think his appearance gave a greater sense of that unhinged part of Tommy’s character. It’s something that play up here with the sheriff talking about Tommy’s previous run in with Jason and how he’s meant to be in a psychiatric clinic. He spends the entire movie talking about how dangerous Tommy is and how he’s the one probably committing the murders in order to convince everyone Jason is back. This is my ‘shades of grey’ mindset talking again but that would have been neat to go into more, even if you didn’t want to commit to Tommy being the new killer, you could imply he was and then reveal that Jason was back but you see right from the off that Jason is alive and everything takes place concurrently with Tommy being locked up.

There does seem to be something of a connection between Tommy and Jason though, at the climax Tommy has a plan to rid the world of Jason once and for all and manages to goad him into a final showdown, Jason even abandons killing one girl in order to go after Tommy. It’s pretty obvious at this point that you can’t kill Jason, you can shoot him as much as you want, even point blank with a shotgun but it’s not going to do anything. But incapacitate him? Now that’s the ticket. That’s why Tommy is going to anchor him and let him sink to the bottom of Crystal Lake.

Either that or he’s just taking his boulder for a walk...

Speaking of the Universal Monsters though, this seems to poke at something of a Dracula/Vampire vibe as well with Tommy suggesting he has to lure Jason back to his original resting place. It’s almost bringing things full circle to his origins of drowning in the lake as a kid, an odd sense of symmetry for a series that has already disregarded that it called one of its previous entries ‘The Final Chapter’ and would spend the next few with pseudo reboot subtitles like ‘A New Beginning’, ‘Jason Lives’ and ‘The New Blood’.

But the final image of the movie is one that has been recurring throughout, the eyes of Jason still moving from behind his mask, showing he still has life in him yet as he will no doubt one day rise from his watery grave to wreak havoc on another bunch of teenagers around Crystal Lake. But that’s a story for another day in about 8 months time...

#Friday the 13th #Friday the 13th Part VI #Jason Lives #Paraskevidekatriaphobia

[doctorwhonews]

The Early Adventures: The Night Witches (Big Finish)

Latest Review: Written By: Roland Moore Directed By: Helen Goldwyn Cast Anneke Wills (Polly Wright/Narrator), Frazer Hines (Jamie McCrimmon/The Doctor), Elliot Chapman (Ben Jackson), Anjella Mackintosh(Tatiana Kregki), Wanda Opalinska (Nadia Vasney), Kristina Buikaite (Lilya Grankin). Producer David Richardson Script Editor John Dorney Executive Producers Jason Haigh-Ellery and Nicholas Briggs Cover: Tom Webster Originally Released: September 2017 Review can be a funny business. If you’re a reviewer working across a large canvas it’s likely you’ll regularly come across things you can’t stand. A newspaper cinema critic who hates horror films still has to review them; a book reviewer may still need to struggle through three volumes of Fifty Shades Made a Lot of Money Didn’t It So Why Not Me? even though they’d rather set fire to their eyelids. But the smaller and more specific your turf the more likely you are to, well, be predisposed to like the material. If you’re working on a Science Fiction magazine it would be odd if your every review began “As someone who loathes SF on principle…” If you’re looking at something even more singular, like a particular TV show, it’s pretty likely it’s a TV show you like. And if reviews of audio plays based on that TV show are being handed out, it’s to be expected if they’re given to people who don’t hate audio as a medium. The Early Adventures, though, exist in a niche within a niche within a niche. And it’s one, I confess, I’m not predisposed towards. When Big Finish decided to evolve their Companion Chronicles range by recasting crucial roles, I was instinctively not a fan of the concept. For me “the Second Doctor”, for instance, was not shorthand for “the Doctor sometime between the events at Snowcap Base and his being put on trial by the Time Lords” but for “the Doctor as portrayed by Patrick Troughton,” actor and performance too bound up in each to be substituted for anything else. I wish I could say that The Night Witches caused the scales to fall from my eyes and for me to be converted into a true believer but unfortunately I have to say doubts about the soundness of the concept still linger. The format of the Early Adventures leads to an odd mish-mash of voices that take a very long time to get used to. We’ve got original Polly Anneke Wills pulling double duty as Narrator and as Polly, Frazer Hines similarly playing both Jamie and the Doctor, while there’s a new Ben in the form of Elliot Chapman. Part of the essential suspension of disbelief with many Big Finish ranges is accepting that the actors sound older than they did at the time, but that’s made harder by pairing them with a Ben who’s genuinely forty years their junior. Hines’ double duty is a particularly strange listening experience as he actually now sounds more like the Doctor than Jamie, even when playing the Scotsman. And while his Doctor is a fair approximation of Troughton’s voice and accent it really misses the sense of the great man’s performance. Troughton was an actor who could seemingly effortlessly spin a line reading on its side half way through to do something unexpected and brilliant. It’s part of the reason why, in his hands, even the clunkiest of rushed scripts could sound compelling and witty when coming out of the Doctor’s mouth. And, as much of a legend as Frazer Hines is, there’s not much sense of that in his reading of the Doctor’s lines here. To an extent, it actually feels like a complete break with the past and a full recast – perhaps even with Hines’ Doctor opposite a ‘new’ Jamie – would work better than this halfway house. By the same token, the format feels held back by being a full cast audio, but with narration. The narration is redundant throughout and doesn’t actually add anything to proceedings. Wills’ Narrator, for example, describes our trio looking down a hillside towards some panzer tanks in the snow below, before we move to the cast’s dialogue establishing how they’re on a hillside looking down at some panzer tanks below. Hopefully future releases will cut that Narrator role as its completely unneeded and simply slows down the drama. Added on top of all this is a doppleganger for Polly, played by a different actor most of the time but sometimes by Wills – meaning that in some scenes Wills is giving voice to three different characters at once. And also that in some scenes the same character is played by two different actors from one line to the next. It’s to the credit of everyone involved that it’s not actually as hard to follow as that makes it sound. I have to admit though that by the end of the two hours, I did get used to the various voices, except possibly for the Doctor himself. Set into this format is a story perhaps best described as ‘Pure Historical Under Siege.’ The TARDIS lands our heroes in the days of WWII and quickly they become tied to the fate of the isolated base of the ‘Night Witches,’ as the steady advance of the Nazis towards Stalingrad draws ever closer to the base. And, typically of a Base Under Siege story, the base commander is deeply sceptical of the new arrivals before beginning to crack under the pressure and becoming as much a threat to her own people as the enemy at the gates. Indeed, we see very little of the Germans themselves in The Night Witches and the Doctor and his companions spend most of the runtime victims of commander Vasney’s attempts to expose them as German spies and, later on, use their deaths to the advantage of a mad propaganda scheme to demoralize the enemy forces. This leaves the play a little short of incident, and much of it is pretty predictable. Each cliffhanger focuses of a dramatic revelation clearly signposted as much as an episode and a half before. Everyone’s gasps of shock and disbelief when they see Polly in the first episode, for instance, makes it no surprise when her doppleganger shows up and the theme music kicks in. And with it established early on that not only is Tatiana a dead ringer for Polly, but a talented impressionist and mimic who was about to begin a stage career before the war who is sick of the fighting and desperate to find a way out, it’s easy to see where the plot will go an hour later. That said, first time contributor to Big Finish Roland Moore delivers a script that has all the right elements in all the right places but, like a piece of Ikea flat pack furniture, there are stress marks where the screwdriver has been applied a little too brutally in the effort to make it all fit together. The real life heroism of the Night Witches, who ran dozens of bombing missions a night in obsolete bi-planes under horrendous conditions is a great period of history to explore and fits nicely with Who’s old fashioned educational remit with lots of detail on the tactics and deployment of the Night Witches. And while there are no genuine Russians among the cast, it’s still lovely to hear some skilled voice work from the Anglo-Polish Wanda Opalinska as Vasney and Lithuanian Kristina Buikaite as Lilya, a young Night Witch smitten with Ben. It lends a nice sense of location to the performances, and of our regular TARDIS team as strangers in a strange land. And it comes wrapped in a cover that, even by Tom Webster's high standards, is a strikingly beautiful composition. A relatively slight story buoyed by sincere and convincing performances by the guest cast and a compellingly tense corner of history, The Night Witches highlights the unique challenges The Early Adventures present to listeners. It’s not to be forgotten, however, that when it comes to recapturing the brilliance of this era of Doctor Who, The Early Adventures are the only game in town. http://reviews.doctorwhonews.net/2017/11/the_early_adventures_the_night_witches_big_finish.html?utm_source=dlvr.it&utm_medium=tumblr

#Doctor Who

[annaxkeating]

Artificial Intelligence Will Change How You Do Marketing in 2021

How often do you reflect on the ways technology changes your life as a marketer? 

I’m not talking full-on paradigm shifts here. (“We do our marketing… on the internet.”) I mean the sly, step-by-way manner in which new tech slides neatly into your existing stack and subtly reframes the game on you. 

These changes don’t always alter your job in dramatic ways, but they eliminate the hassles and headaches. They may speed up your time to results, automate painful routines, and enable you to focus on what matters most. (Remember what collaborating on a document looked like ten years ago? Remember printed memos?)

Very rarely, these technologies also let you do things you’d never considered possible. 

No incoming martech makes a better case for this sort of incremental innovation than artificial intelligence. While new AI products are surely on the horizon—self-driving cars are coming any day now, possibly, maybe—AI’s most dramatic effect on your job today lies in adding new features across the tools that you’re already using. 

When you’re living it, of course, this type of change can be hard to notice. It’s like suddenly realizing you desperately need a haircut after three months in lockdown. 

But, one day soon, you’ll marvel at all the things AI sneakily helped pull off your plate. Because when marketing meets AI, magic happens. It can feel inevitable—but that doesn’t mean you don’t need to pay attention.

At Unbounce, we not only believe that applied AI is the future of marketing, we also think marketers tuned in to what’s happening now stand to benefit in a big way in 2020 and beyond.

To put it another way, marketing and AI is a love story for the ages.

Marketing and AI: A “Meet Cute”

For marketers interested in learning what AI can do for them, right now, debates and philosophy about artificial intelligence can be heady stuff. And, honestly, it’s kind of a distraction. So, instead of getting into the weeds, let’s start with the distinction that makes the most sense for marketers to learn: the one between AGI and ANI.

Artificial General Intelligence (AGI)

Strong AI or Artificial General Intelligence (AGI) is what most people think of when someone says AI.

This technology replicates neural networks (not necessarily human ones) to perform highly sophisticated cognitive tasks. AI researchers typically take this one step further, though. According to them, AGI “controls itself autonomously, with its own thoughts, worries, feelings, strengths, weaknesses, and predispositions.” 

Teams across the world are working on AGI, but the closest to a consensus from researchers is that we might see it sometime within our lifetime. And some skeptics doubt we’ll ever see AGI, let alone more advanced forms.

Artificial Narrow Intelligence (ANI)

So handing over your marketing campaigns—or, gulp, your job—to an AI is decades or centuries away. But weak AI or Artificial Narrow Intelligence (ANI), sometimes also called “applied” or “pragmatic” AI, is available to marketers today. Right now.

As the name suggests, ANI focuses on narrow problem-solving applications. In the world of marketing, this means taking on specific, repetitive tasks to deliver additional business value. It may learn and make decisions independent of your input, but mostly this AI tackles the work you’d rather not.

But here’s the thing: ANI might not challenge our fundamental conceptions in the same way AGI does, but it’s having a transformative impact on our lives (and jobs) nonetheless. It integrates so deeply into our everyday lives that we don’t have to think about it. Chances are good you’re already using ANI, whether you know it or not.

Don’t believe me? Let’s take a look at a few places you might be encountering ANI today, either as a consumer or as part of your job. I admit that here that this list is not even close to comprehensive, but that’s my point: AI is slowly but surely filling all the cracks in our marketing stacks. (And, hey, that rhymes, so it must be true.)

Product Recommendation and Content Curation

Companies like Amazon and Netflix made fortunes by pointing people at more things they might want to buy. Much of these efforts are powered by sophisticated algorithms that let them match the right products and content with the right customer.

Amazon, for example, runs on a recommendation engine that’s been driving significant business value for more than 20 years. From the early days of user-based collaborative filtering (i.e., an algorithm making recommendations based on similarities between users) to more scalable solutions driven by a deep learning framework called DSSTNE.

DSSTNE is pronounced “destiny,” by the way—as in “buy this jewel-encrusted toilet brush… because it’s your destiny.” They’re not subtle. 

Today, customer recommendations are a very small portion of Amazon’s total investment in AI.

Netflix doesn’t sell products, but they similarly credit the combination of contextually-aware recommendations and personalization (both powered by machine learning models) with saving them $1 billion a year. 

How does this work? By reducing one-month churn by several percentage points. In the crucial 60 to 90 seconds that a customer will spend browsing before quitting the app in frustration, Netflix serves up content most likely to appeal to people with similar tastes. And it works: 80% of what people watch comes from a recommendation.

By presenting customers with content they’re more likely to watch first, Netflix reduces churn. Even thumbnails are selected by a neural network based on predicted clickthrough. 

Say you’re not Amazon or Netflix, though. Say you’re part of a small team or a startup tight on resources. What can you do? 

The good news is that today’s marketers can similarly take advantage of AI-powered recommendation engines on a more affordable scale.

Not only is some of this tech available to your developers, but more than one tool exists right now that lets you deliver product and content recommendations based on audiences, their intents, and their interests. Their availability will only increase in the months and years to come.

AI-Enhanced PPC Campaigns

Like Amazon and Netflix, Google will stick AI almost anywhere, even before its fully baked—from Gmail’s Smart Compose, which lets you email platitudes at lightning speed, to the AI-based noise-canceling feature recently added to Google Meet. Then there’s BERT and RankBrain’s role in search, and TensorFlow’s application to encryption, translation, robotics, and more… (The ellipsis is well-earned here.)

For digital marketers, one of the most significant use cases for machine learning has been in Google Ads. In a couple of years, Google’s Smart Bidding technology has gone from a curiosity that, at best, once ruffled a few feathers to something that has PPC experts rethinking how they’re spending their time.

According to Workshop Digital’s Andrew Miller, this sort of tech has overturned a lot of longstanding PPC best practices.

AI and machine learning are enabling PPC analysts to spend less time manually crunching data and more time on strategy development. Our jobs are not in danger yet, but machines are allowing us to rethink and recast our roles as AI-driven tools augment our capacities.

Andrew Miller, Co-Founder, Workshop Digital

Smart Bidding was once a neat trick that couldn’t hold a candle to an experienced human. Experts like Andrew tried it out, and many wrote it off. (Some still do.) But many PPC’ers point out that automated bidding is increasingly reducing the time spent on manual bid management. 

Are agencies running for their lives because of AI-powered enhancements like Smart Bidding? Definitely not. But roles are changing as today’s PPC specialists spend more time on higher-level strategy and specialized growth tasks. For an industry that thrives on staying current, AI is a net positive.

Machine Learning and Conversion Rate Optimization

Roles are changing on the other end of the funnel too. When it comes to delivering more conversions from your landing pages, A/B testing is still very effective. But running tests also demands time, traffic, and expertise that marketers don’t always have. For small businesses especially, these minimum requirements put optimizing out of reach.

Enter artificial intelligence.

Around 2017, our R&D team realized machine learning has the potential to remove these hurdles from A/B testing—and free marketers to focus more on what humans do best. AI can even do things when testing that no human can do, making decisions on the fly about what version of a landing page is best for what type of visitor. 

We kept thinking, ‘it isn’t the page that converts. It’s the visitor.’ So we started looking at how different visitors convert across different landing pages. The team built and tested machine learning models to see how far we could extend this concept. Sure enough, it turned out that we could drive higher conversion rates beyond what would ever be possible with a one-page-fits all system. We started prototyping immediately.

Yosem Reichert-Sweet, CTO, Unbounce

After three years of training a machine learning model, and investigating different ways to apply it, we arrived at Smart Traffic, a feature that fulfills this promise and makes AI-powered optimization available to Unbounce customers.

Smart Traffic uses a contextual bandit algorithm to learn about your visitors based on attributes like location, device, browser, and timezone. Once you’ve created and published a few variants of your landing page—the only thing it can’t do at this point, frankly—Smart Traffic delivers each visitor to the one most likely to convert. 

There are two things that Smart Traffic shares with the best martech AI solutions today. First, our customers see results just by turning it on. (Nothing cuts through hype like actually getting stuff done.) And, second, it never stops learning, getting better at its task during the life of a campaign, and adapting to changes in traffic sources without human intervention. 

Editor’s note. If you’d like to learn more about how Smart Traffic works, take a look at our announcement or read a few stories about marketers who’ve used it. Garrett’s also got you covered with some advice on how to build landing page variants that’ll take advantage of it.

AI-Augmented Chatbots 

Chatbots are among the most common ways that your customers interact with AI. But even today’s strongest AI-powered chatbots are better at pulling relevant bits of data from specific contexts than they are detecting nuance. They’re humanlike, not human.

For business owners, however, this shouldn’t be a dealbreaker. Chatbots can be a lot more personable than asking your visitors to fill out a form, and interacting with them can foster engagement. They also let your customers self-serve, which saves everyone time.

I’ve always appreciated how Microsoft’s Purna Virji put it in an article for MarTech Today:

In one way, this is actually the future returning to the past. For years, internet users have sacrificed the personal touch for convenience. Now, we’re entering a world where we can have both. It’s the Personal Touch 2.0.

Purna Virji, Senior Manager, Global Engagement, Microsoft

Though fully custom chatbots are reserved for enterprise, small teams embrace the tech using solutions like Drift, MobileMonkey, Snatchbot, or even in Facebook Messenger. Juniper Research estimates that by 2023, retail chatbots will save the industry $11.5 billion in costs, and generate over $112 billion in revenue. 

Mitsuku, a five-time winner of the Loebner Prize, tells me she’s “the world’s most humanlike conversational AI.” But she doesn’t get my simple idiomatic question—unless, y’ know, she’s wicked sarcastic.

So, you’re unlikely to mistake a chatbot for another person long enough for true love to set in. But we shouldn’t define chatbots by the quirks and failures of today since they’re a rapidly developing technology. There’s a lot of promise in chatbots enhanced by natural language processing (NLP) and sentiment analysis. One day soon, you might just meet the chatbot of your dreams. (I’m not judging.)

AI-Generated Content 

When content creators read about AI-generated content, they begin to sweat. Buzzy articles with titles like “Ten Ways AI is Going to Replace Your Content Team and Leave Them Bankrupt and Unloved”… Well, let’s just say they don’t exactly alleviate our imposter syndrome. 

Michelle Halsey is ultimately skeptical, though, about the prospect of being replaced by a machine. She writes,

Talented writers have no need to worry about automation stealing their gigs. At least, not as long as our clients are more interested in engaging their audience than they are sucking up to search engines.

Michelle Halsey, Content Blogger and Copywriter

Note the emphasis on talent here. It’s much more likely that AI will first tackle templated and repetitive work that hardly calls for persuasive writing anyway.  These days, applied AI can also smooth out the rough edges in your podcast, remove some of the pain from meticulously editing videos, and gut-check your sentences for clarity.

Given the danger of AI-generated content flooding the net with misinformation and spun content, it’s also a use case we’re still grappling with. For now, AI appears to offer solutions to the very problems it creates, as developers teach tools like GROVER to generate “neural fake news” to detect it.

GROVER generated this article based on my own words. It’s not good, but it might be a sign of things to come.

AI-Driven Data Insights

Every growth-minded marketer loves data. It’s an addiction. We bring it into every meeting and include it in every strategy session. We spend hours staring at spreadsheets, analytics, and reports, even if there’s way too much data to digest.

But even when you’ve got a hotline straight to your data team, recognizing patterns and pulling opportunities from massive swathes of data is hard. Artificial narrow intelligence helps with that too.

Recently, Unbounce explored the role that copy plays in landing page conversions through deep learning research, including a modified version of Google’s BERT (Bidirectional Encoder Representations from Transformers).

Our Conversion Benchmark Report crunched the data from 34 thousand landing pages. It delivers insights about how reading ease, word count, and emotional language relate to conversion rates across 16 industries.

Sample benchmarks for home improvement landing pages.

The amount of data here (every word on every landing page) already put this analysis outside of human capability. But using machine learning allowed the team to dig deeper:

With data analysis and machine learning, we can take an unbiased look at what goes into a great landing page, and find opportunities for every landing page to improve. Machine learning allows us to look at significantly more data than a human being ever could, and find real, data-driven patterns that lead to higher conversion rates.

Tommy Levi, Director of Data Products, Unbounce

One question readers ask us about the report is why we included some niches (“pest control”) and not others (“model train enthusiasts”). The answer: the machine learning model generated these subcategories, on its own, from our aggregate data. Instead of imposing our arbitrary human bias, ML started with the data and sorted it from there.

Call me a nerd if you want, but that’s kinda mind-blowing. A lot of what’s happening in the Conversion Benchmark Report wouldn’t have been possible without pairing human intuition with the power of machines.

Want to see what our machine learning analysis revealed about your industry? Explore benchmarks and data-driven insights for 16 industries in Unbounce’s 2020 Conversion Benchmark Report.

AI Ain’t Perfect (and That’s Okay) 

If you’ve ever tripped over a Roomba or struggled to get Siri to do, well, anything sensible, you know artificial intelligence has a long way to go. (If you’re feeling masochistic, try asking Siri how to contact Unbounce. I dare ya.)

But does that mean it’s just hype? Not. A. Chance.

By any measure, we’re still in the early days of the long romance between AI and marketing. We’ve yet to see its full potential. The transformations that marketing is undergoing now aren’t always so easy to recognize or understand. As we’ve seen, applied artificial intelligence already penetrates our jobs, our strategies, and our campaigns on almost every level. 

You could just go with the flow, of course. Keep doin’ what you’re doing. Wait for AI to come to you and your stack. You’d be missing a trick, though.

Because by actively thinking about ways in which AI can enhance your marketing practice today, you’ve got the opportunity to get ahead of this thing. And by actively adopting it, you can start taking advantage of the freedom and new capabilities it delivers—before the competition gets there, as they inevitably will.

Why Unbounce Invested in AI for Your Landing Pages

Unbounce recently announced that we raised $52M (CDN) in funding to bring accessible AI-powered optimization to our customers. We’re investing now because we’re convinced using artificial intelligence to augment your marketing isn’t just aspirational, even for small businesses. It’s the future. This transformation is coming—really, it’s already here—and our customers will be a part of it.

The coming together of AI and marketing is tremendously valuable for businesses of all sizes. Whether it saves you time and money, highlights opportunities and patterns you didn’t know existed, or frees you to run slicker, higher-converting campaigns. As Rick Perreault, our co-founder and CEO, describes our ambition, the technology we’re developing today will eventually allow marketers to “set it and forget it through machine learning.”

It’s all part of our conversion intelligence mission.

What’s Conversion Intelligence?

At its core, it’s the conviction that the best use of AI lies in matching human savvy with the capabilities of a machine. It’s the idea that even small businesses—scratch that, especially small businesses—will stand to benefit from these enhancements. And it’s the belief that AI isn’t some far-flung concept—it’s an everyday tech that’s going to play an even more essential role in how you do marketing going forward.

Conversion intelligence is you, and your marketing know-how, augmented by machines. You can read more about it here.

In 2021 and beyond, AI insights will make it possible for you to create and optimize the highest-converting campaigns possible. Heck, in 2021 and beyond, AI just might rock the foundations of how you build, test, and optimize your landing pages.

Unbounce’s product teams are hard at work on these innovations, and we’re downright giddy with excitement about sharing progress and learnings with you here on the blog. 

Watch this space. The story continues.

from Digital https://unbounce.com/marketing-ai/artificial-intelligence-will-change-how-you-do-marketing-in-2021/ via http://www.rssmix.com/

#digital marketing