#BECAUSE I ONLY MODELLED THE BASICS BUT STILL HAD TO DRAW THE VAST MAJORITY OF EVERYTHING

[elbdot]

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WOW Gladion, very reliable, love that we finally got through to you, fwiends forever am I right 🫠

WE'RE BACK with a MEGA UPLOAD that was too big for one post so I had to part it in two, see you guys in a week with the second part (and the Webtoons update!) OR you can read the whole thing on my Patreon early! 👍

Patreon - And thank you guys so much for your patience for this update!! :D ☺️💖 It took AGES because of the backgrounds...

#els alolan adventures #guzma #pokemon #pokemon sm #pokemon sun and moon #hau #pokemon comic #alola #Latias #As you can clearly see from the CHAIRS I worked in BLENDER for this update #I made an ENTIRE 3D MODEL OF THE CAFÉ and found premade chairs and umbrellas and trashcans and ROCKS to place everywhere #Until I had a perfect reference model for the entire beach / town scenery #And then I traced over it #except I COULDN'T #BECAUSE I ONLY MODELLED THE BASICS BUT STILL HAD TO DRAW THE VAST MAJORITY OF EVERYTHING #AND IT BARELY SAVED ME ANY TIME AT ALL #AND THE SHADING NEARLY DROVE ME INSANE #AND CREATING THIS UPDATE WAS AN INSUFFERABLE NIGHTMARE #I am completely burned out btw I'm taking the entire week off gjfkjgfdkjgfjd #Once I'm recovered I'm gonna upload some more of my initial references and the storyboard to my Patreon page

[edwardelricsrightarm]

"A lesson without pain is meaningless. For you cannot gain anything without sacrificing something else in return, but once you have overcome it and made it your own...you will gain an irreplaceable fullmetal heart." - Edward Elric

In honor of disability month and the FMA 20 year anniversary I wanted to address some Thoughts™️ about the series.

It's not often you see a disabled protagonist in media where their disability is integral to the story without taking up their entire character, even more so with anime. Yet, Fullmetal Alchemist has not just one disabled Protagonist, but two. The Elric Brothers are an exemplary representation of disability in media that I find myself reflecting on often as a disabled person myself. If you haven't completed the manga or Brotherhood, skip this as it will be brimming with spoilers.

(Mangahood will be my point of reference because while 03 is good on its own merits it's not as fresh within my immediate memory, and I am far less familiar with it. Keep this in mind, I've watched FMAB 10 and a half times whereas I've finished 03 only once years ago.)

The story highlights their disabilities immediately, Edward being a double amputee and Alphonse being without his ENTIRE body, only having the senses of proprioception, sight, and hearing left. Yet, despite this being key to the story and an integral part of their characterization, it is only one facet of their motivations and doesn't take center in the narrative, which is refreshing. It's not inherently negative to make a narrative centered on the characters' disabilities, but often this model of a story goes very wrong very fast and starts to feel hollow (no pun intended). FMA avoids this by making their disabilities a clear part of the plot and their motivations without allowing it to consume the entire story, so the Elric Brothers don't suffer the "my disability is all of my character" problem that many disabled characters are relegated to in a vast portion of media, all while being strong and competent.

Recap:

The brothers wished to revive their mother, but their good intentions cannot change the atrocity of their mistake, Truth makes this abundantly clear from the start. Edward loses his leg first, a punishment for "stepping" into God's shoes and transgressing the place of humans in their world. Alphonse loses his entire body, unable to feel any warmth or simple comforts like food and rest, when all he wanted was to feel the warmth and comfort of his mother's embrace again. At first, Alphonse's entire being is consumed by the gate, but Edward acts immediately, refusing to lose his little brother and refusing to allow his arrogance in this plan to cause his brother's death for only following his lead. Edward gives his right arm to have the gate give back Alphonse's soul, and stated clearly in his panic that he'd give his entire self to save Alphonse if that's what it would take, but Truth took his dominant arm only, showing something akin to mercy, although the character of Truth is capriciously strict and hard to describe as "merciful".

Through giving up his right arm, Edward regains his Right Hand Man, his little brother and best friend. His only remaining family, who he feels responsible for protecting in the absence of their parents. He felt immediately that he'd made a grave mistake, instantly full of regret as he realized the gate had taken his brother. In that moment he was willing to give anything to take it back and undo the suffering his arrogance caused his brother, yet Alphonse was still to suffer more to come. Ed tied Alphonse's disembodied soul to one of Hohenheim's collected suits of armor, managing to at least keep his brother alive in some way. One could say that Alphonse's punishment functioned as a secondary punishment for Edward, showing him how easily his hubris could have cost him what he has left in his obsession with regaining what they'd lost, their mother. A very clear symbolic reminder of the weight of his actions and how he'd misled his brother in his own naive ignorance. Even in giving another limb away to drag his brother's soul back out of the gate, he couldn't offer enough to bring him back intact. Thus is the law of equivalent exchange.

Now that we've reviewed some of that basic symbolism and the motifs the story draws upon with limbs and body parts in relation to characters, let's move on to each individual brother and break it down, shall we?

Edward Elric is a very realistic protagonist, this is one thing a majority of us familiar with this series can agree upon. He feels like a believable teen boy, with layers of complexity to his character while also showing arrogance and immaturity that is unsurprising at his age. He expresses unwillingness to kill and avoidance of unjust violence from the beginning, and has a strong moral code after the ordeal of committing the taboo.

In some characters his cocky personality would typically become grating, yet the story explains in itself why he is this way, then builds upon this to develop him into an incredibly mature character who is willing to admit when he's absolutely wrong and adapts to new information and context for the crisis unfolding around him as it comes, even if he remains crass. This arrogance is shown from the start to be a manifestation of insecurity, self loathing, and repressed guilt. Edward is a logic driven person, he has a very unique thought process, which is where my interpretation of him as autistic comes in. Edward's awkward social demeanor, somewhat abrasive and cold approach to some, and his trouble coping with nonsensical societal structures all stand out in this way. Furthermore he clearly shows hyperfixation, hyperactivity, special interest, and infodumping behaviors that are all too familiar. He's picky with food (*cough* the milk thing), has very little filter and speaks his mind bluntly even if this can warrant conflicting responses, yet at the same time struggles with vulnerable emotions, and he is frustrated when his own routine or itinerary are interrupted by forces beyond his control. All of these things Scream autism with comorbid ADHD. Many traits are shared between the brothers, and I'm quite certain they're both on the autism spectrum based on behavioral patterns. Neurodivergence aside, Edward's physical disabilities are undeniable.

Despite his bratty persona, Edward is fundamentally kind and uncharacteristically gentle and soft around the edges for a shonen protagonist in many ways. He cries openly on many occasions even if he struggles talking about his trauma and burdens in words at times, he feels pain, grief, and compassion so intensely it throws him into action on a regular basis in the narrative. In this way he's also a fantastic example of non-toxic masculinity (though in other ways he has displayed more toxic traits, he's just a kid). He acts on his heart, even if he's led by his mind and logic in most things. His humanity, value for life, and care for others will always win over his logic, and he shows a sense of personal responsibility for doing the right thing even if it harms him in the process. Ed is clearly shown having ghost pains in his lost limbs which is honestly an interesting detail to include, I don't think I've ever seen that aspect of amputation shown in media aside from FMA. It's also shown that when Ed's automail arm breaks this is a HUGE problem for him, but he's also shown to be very good at working around this in difficult circumstances. He doesn't become completely helpless, even if majorly weakened.

Alphonse is an extremely lovable and compassionate boy, brimming with altruism and care for others. Even in his noncorporeal state he pursues a better future and he's not helpless by any stretch. Edward clearly states Alphonse is the superior fighter for example, and it's not just because of his armor body being so large. He's *talented*, that's a fact. Al is every bit as clever and capable as Ed, moreso in some ways, and I love that about his character *because* he's so clearly disabled. He has no sense of pain, he is completely incapable of sleeping, he can't eat, can't relax or find comfort, he can only exist and think. This causes him to overthink in all his time alone, this is debilitating. He clearly is absolutely sick of the loneliness this causes, and he often feels helpless though he's not. He has doubts and fears that consume him in relation to his armor body, he questions his own personhood, even. Yet, Edward is stubborn and staunch in affirming that no matter what he's dealing with, he is fundamentally still a human being that is loved and irreplaceable. Alphonse is powerful and his body gives him some advantages, but it also sets him back, and the brothers know this even when others claim Alphonse's state is somehow a good thing. I have hEDS, a disability that comes with advantages as well as the major downsides, so I can understand and relate to Alphonse here. I too am told my disability is a boon because of flexibility and because I'm less likely to fracture bones, but I'm twice as likely to injure my ligaments and joints, which people ignore.

The brothers are both disabled, both flawed, both show weaknesses, but they are competent, determined, and strong in their own right. They are rounded characters that exist for more than to be pitied or condescended to by able bodied characters around them. They put their entire being in everything that they do no matter what that is, and they don't know the meaning of giving up. These traits that they're made of truly make them a shining example of disability in protagonists for others to look to for reference when writing their own disabled characters.

Even though by the end Edward has regained one limb and Al has regained his body, this also doesn't just deus ex machina reverse their disability or make it go away. It's clear that Alphonse's body is weak and has to be rehabilitated upon recovery, and Edward is still missing his leg and bears the scars and pieces of the port from his automail arm. They weren't suddenly made able bodied upon recovering these things, they reclaimed what was lost through struggle and grit, but the narrative didn't give the impression that their disability in itself was something to be fixed, which is important. They wanted to recover their bodies, but this doesn't erase the effects of their disability.

It was about Edward atoning for leading Alphonse into their mistake and saving his brother from suffering further, it was about them proving they can keep moving forward no matter what, not about getting rid of their disability in itself or putting themselves down because of the disabilities. This, to me, as a mentally and physically disabled viewer, is so important. They achieve their goal, but this doesn't in any way erase or undo the effects of their initial losses, they find ways to adapt and move on but they're still affected and still disabled. They always will be. That can be so important to see in comfort characters, and as a disabled individual who's had both brothers as comfort characters since I was a child, their impact on my own journey is surprisingly tangible for fiction.

#fmab #fullmetal alchemist brotherhood #fma #edward elric #alphonse elric #elric brothers #character analysis #disability month #disability positivity #disabled #fma 20th anniversary

[carewyncromwell]

“A waltz when she walks in the room, She pulls back the hair from her face. She turns to the window to sway in the moonlight... Even her shadow has grace. A waltz for the girl out of reach, She lifts her hands up to the sky. She moves with the music; The song is her lover; The melody's making her cry... So she dances, in and out of the crowd, like a glance... This romance is from afar, calling me silently...”

~“So She Dances,” by Josh Groban

x~x~x~x

And to cap off my set of Valentine’s Day posts where I feature my MC’s and someone they care about...last but not least is my HPHL kelpie kid Ru! In the above picture, they’re pictured with Galen Stagg, who belongs to @cursebreakerfarrier, but this picture, this post, and this basic AF pencil test animation are actually about Ru’s relationship with their “keeper” and ttly-not-girlfriend Estrid Soelberg @that-ravenpuff-witch! (I wanted to overlay the two images, but the online sources I tried using to do so weren’t cooperating, so...eh. Here they are separately. XD)

When the kelpie who’d taken on the identity of the Ravenclaw student Rudolph Ollivander first encountered Estrid Soelberg, they did not like her. How could they, when it was because of her that they now wore a silver chain around their neck that she could use like a “leash” and keep them from transforming back into their true form and eating anything or anyone she disapproved of? Naturally Estrid didn’t care for Ru much either -- and really, considering that they nearly ate a first year, that also was pretty understandable. Over time, though, Estrid’s stance softened somewhat, upon realizing that there was an oddly sympathetic side to the carnivorous kelpie.

For one, Ru absolutely loved being at Hogwarts. It wasn’t obvious at first, given how laid-back and aloof they were, but their electric blue eyes were always bright and aware, never missing out on a single detail. Ru would spend hours and hours every day in the Hogwarts library, devouring every book they could. They would explore every corner of the castle grounds and memorize every shred of knowledge that came under their nose. They collected knick knacks and jewelry from Hogsmeade, even going so far as to pierce their ears in their third year, to the horror of all of the adults, both inside and outside of school. And this didn’t even touch on Ru’s great passion for history, magical creatures, Herbology, art, and especially photography. Their still Muggle photographs were always crystal clear and striking, from a view of the Black Lake taken from the Owlery to close-ups on the details of the winged boar statues near the front gates. Ru’s Muggle-style photography came alive in a way that magical photography -- which was still in its infancy and quite low in quality -- couldn’t capture. On the Christmas break of their third year, Ru also discovered and became very enamored with Muggle animation, which made crude drawings come to life -- Estrid, despite her best efforts, couldn’t bite back her laughter upon finding out that Ru had requested the permission of one of the snobbier girls in their year to use her as a model for an animation, only for the finished product to end up being of the girl picking her nose with her pinky finger.

As Estrid got to know Ru better, she decided to try showing them more compassion. For as inhuman as Ru was, and how eccentric, cold, and rude as they could be, their enrollment at Hogwarts truly didn’t seem to be motivated by anything malevolent -- it had truly just been the only way they saw for them to attend this school they’d been watching from afar and longed to see up close. And Estrid treating Ru with more respect and kindness, little by little, wore down Ru’s walls enough that they didn’t dislike her quite so much either. She not only was insightful enough to suss out that they didn’t like eating around other people and showed them the Hogwarts kitchens so that they’d have a place where they could eat in peace, but she didn’t see the need to fill the silence with worthless conversation the way so many of their classmates did. She could sometimes just let a moment be, let the emotions and time just rest for a while. With that, though, Estrid was actually a rather interesting person too, in her own way. She had her fair share of admirers for her appearance (which Ru acknowledged was decent enough, by human sensibilities), but she seemed actively disinterested and uncomfortable about it, instead being the type who was unafraid of being on her own. And yet despite this, Estrid truly wasn’t a loner like Ru was -- she had a gentle hand with creatures of all kinds, an artistic eye, and a soft smile that she rarely showed to much of anyone, but was always sincere. Most striking of all to Ru, though, was the way she moved when she danced. The way her limbs bent and stretched with such grace fascinated Ru. They wished they could slow down time sometimes, just to analyze every tiny little flick of her fingers or flourish of her ankle. Knowing that they couldn’t take enough pictures to capture the grace of her movements, and not yet having a camera that could take moving pictures, Ru settled on trying to animate Estrid. Most of the animations were very crude in the beginning, consisting of nothing but stick figures, but little by little, Ru studied the proportions of the human body (very different than that of a kelpie!) and tried to refine their technique. And before long, all of their animations ended up being modeled on Estrid some way or another -- the vast majority of them being her dancing ballet.

Another person who’d be in the room sometimes when Estrid was dancing was their yearmate Galen Stagg, who often practiced the piano while Estrid was dancing. Ru found the Gryffindor inoffensive for the most part -- like Ru and Estrid, he had a talent for Herbology and Care of Magical Creatures (Ru could sense that Galen in particular had a magical gift for communicating with creatures, even more than Ru themselves did, considering they were actually a kelpie), so sometimes the three of them would end up in the library studying at the same table before a test. Galen was a bit of pansy to Ru’s taste, given his dislike for conflict or confrontation, but he like Estrid was soft-spoken enough that he never gave Ru any real headaches.

One day while Estrid was dancing and Ru sat off on the sidelines (sitting with their legs crumpled up in such a manner that one could wonder if they’d ever learned how to cross their legs properly), Galen took a break from playing to come over and sit down next to the messily-dressed Ravenclaw on the floor. Although he himself really enjoyed drawing too, he’d always felt like Ru tolerated him more than liked him and so had been hesitant to ask Ru if he could see any of their artwork. This day, though, he finally mustered up the courage to ask.

“...May...may I see what you’re working on?”

Ru lowered the page they’d lifted to fine-tune and shot a look out the side of their eye at him.

“...It’s not finished,” they said bluntly.

“That’s all right!” said Galen self-consciously. “That is...I don’t mind, if it’s still sketchy.”

Ru considered him for a moment silently. Just when Galen opened his mouth, ready to say that Ru didn’t have to if they didn’t want to, the kelpie held their sketchbook out in one hand for Galen to take.

With a surprised, but relieved blink, Galen took it and looked at the top page. It was still only a cluster of loosely connected circles and ovals, but Galen could just barely make out what it was.

“It’s Estrid,” he realized, his jade-colored eyes lighting up. “Isn’t it?”

Ru nodded curtly, their gaze drifting off to watch Estrid at the barre.

“That’s just the last frame,” they said in a very low, nonchalant voice.

“Frame?”

“Of animation. Pick up the next eight pages and flip them one by one.”

Galen did so -- and to his delight, he watched as the little cluster of ovals and circles unfolded its arms and spread them in a graceful arc that flourished at the wrists.

“Wow, Ru,” said Galen, impressed, “it looks just like Estrid! I mean, the movement looks just like hers. You really captured the grace of her arms.”

Ru’s electric blue eyes swiveled absently in Galen’s direction, but they didn’t turn around or meet his eyes. Instead their gaze returned to Estrid as they brought up a hand and smoothed some of their long black hair behind their ear.

“...You reckon?” they asked, their quiet voice oddly contemplative.

Galen looked at Ru, surprised. Were they...blushing?

Feeling a wave of compassion for the Ravenclaw all of a sudden, Galen offered them a smile.

“...Yeah. It’s really nice, Ru. I’m sure it’ll be smashing when it’s done.”

Ru’s eyes stayed on Estrid, narrowing slightly.

“The way she moves...” they said lowly, “I’ve never seen anyone else move like that. Even other dancers. It...seems like something that shouldn’t just disappear into the void, when the moment is over...like everything does, sooner or later. I’ve tried to photograph her before, but it doesn’t capture the movement. Even when I take a lot of still pictures one right after another, or when I actively try to get shots that blur, it doesn’t work. And magical photographs...hmph! They’re an absolute joke. They deteriorate so easily, and their quality is atrocious.”

Galen smiled sympathetically. “Well, wizards really have only had them for a short while...I reckon they might need a little time to catch up, right?”

Ru scoffed loudly through their nose and mouth, sounding rather like an offended horse. “It’s pathetic.”

They rested their hands behind them on the floor, leaning back slightly.

“So...the only way I could try to capture the way she moves -- to make it last, past that moment, was to draw it. It’s not exactly easy to get her hands right, though,” they added sourly under their breath.

“Hands are every artist’s Achilles’s heel, I think,” said Galen with a quiet laugh.

His green eyes softened. “...You really care about Estrid a lot, don’t you?”

Ru’s face flushed a bit more darkly as they whirled on him with a glare.

“Don’t read too much into it, Stagg. I find her movements interesting. That’s all.”

Despite Ru’s denials, however, Galen thought to himself that Estrid was pretty lucky, to have someone in her life who’d put in so much effort to try to memorialize her in a lasting way. He wondered if Ru even realized just how sweet and selfless of an instinct that really was.

#hphl #hogwarts legacy #my art #my writing #ru ollivander #estrid soelberg #galen stagg #other people's mcs #I hope galen's written all right honey! #I couldn't find any writing samples for him so I kind of just used the characterization you put down for him as a kick-off point #of course galen is dressed like a proper student while ru is a friggin' mess #you might spot their silver 'bridle' chain around their neck under their collar #and yeah ru doesn't know how tf to sit properly with two legs even after all these years #this kid SLOUCHES CONSTANTLY #drawing their hair was fun though #I'd actually used some choreography done for the dance of the sugarplum fairy while doing that pencil test #it's basic as all get out but hey whatcha gonna do #it admittedly is still good practice for this one project I REALLY want to do for my blog's first anniversary coming up next month... #I love ru and their tsundereness regarding their feelings for estrid so much okay X3

[antagonistchan]

so, some basics on my Magical Girl story

in addition to being a Magical Girl story, it’s also. kinda an Isekai. but a kinda weird Isekai (i mean, Isekais aren’t usually also Magical Girl stories).

basically: one day, the entire population of Earth is transported into another reality. this reality’s kinda a sci-fi/fantasy deal. and when i say “sci-fi/fantasy”, i don’t just mean “really soft sci-fi with a spiritual edge” like Star Wars, i mean straight up “there are Elves and Dwarves and Orks and magic but also it’s in space and there’s hyper-advanced technology”.

anyways, there are also dragons. or at least, there were dragons. the dragons went extinct a long time ago. but also, they were really weird dragons. as in, the dragons in this setting were basically elder gods, just in dragon form. yeah, they were giant winged reptiles... but they were also a much higher form of existence that could comprehend so many more dimensions of reality than we can and warped reality just by their mere presence. and see, while the dragons are extinct.... death doesn’t really mean much to something on that level of existence. they’re all still aware, and all still have some level of ability to affect their surroundings. but the vast majority are content to just lie in their graves and not bother with the rest of the world.

but some aren’t.

one of the really notable ones is known as Skull. Skull might be dead, but he wants to continue living his life. and even in life, Skull was one of the more noble dragons, one of the dragons most willing to defend the “lesser” races like humans and elves and orks.

Skull is... also one of the more macabre parts of this story. he’s not particularly dark, just macabre, but come on, he’s basically a zombie elder god. he’s macabre by default.

anyways, his body, even as just a skeleton, still has lots of power. so he used that power to construct a starship around it. this starship is still vaguely dragon-shaped, and he has full control over it, so it’s kinda like just being a robot dragon. except now he’s kinda frozen solid and people can go inside him (and he’s really big, it’s practically like a city in there). but that’s just most of his body. he did set aside a few of his bones for another purpose.

the Magical Girls. we’re finally getting to that part.

he split up those bones into a bunch of small (like, about the size of a marble) pieces, and then built devices around and powered by them called Magites.

the normal inhabitants of this reality couldn’t really use them, so initially, he made a group of six genetically engineered people specifically designed to use the Magites. and they were.... kinda a success. but not quite. but he was also aware of the existence of other realities, and realized that our reality was A: perfect for his plans, as most of us were compatible with the Magites, and B: on the brink of collapse anyways. so he rescued the entire population of Earth.

and then, whenever an Earthling proved worthy, they’d receive a Magite.

and Magites are just Magical Girl transformation devices. like Intelligent Devices from Nanoha, or Relics from Symphogear, or the Moon Pen or whatever it’s called from Sailor Moon. their purpose is to transform the user into a state where they can draw from Skull’s power. and this state happens to wear frilly dresses.

our main cast is a group of five girls (initially just three) who are particularly close to Skull. like, Skull kinda considers them his personal strike force. the initial three are:

Stella Greenfield, who came to Skull’s attention before even becoming a Magical Girl for her keen analytical mind and the rapid pace at which she learned about this reality’s robotics tech (like, she’d only been here for a month before she was able to program a fully conscious and emotional AI, Eve, who she considers her assistant and daughter). she’s actually the last of the five (not even of the three, of all five) to become a Magical Girl, supporting the team from the sidelines at first with her robots and tactical advice. when she does become a Magical Girl, she uses strong gauntlets to punch good and special gear that lets her deploy robots more easily.

Madison (no last name), who was actually one of those initial six lab-grown Magite users, also making her one of the few non-human Magical Girls (she’s an Elf instead). she was just kinda pushed onto the group, and was initially the only actual Magical Girl of them, so the group was initially just kinda “Madison and her handlers”. she’s timid and skittish, but in a pinch she’s fiercely protective of anyone she considers family or anyone she sees as weaker than her. in Magical Girl form, she uses guns (particularly a sniper rifle) and stealth (particularly the ability to turn straight-up invisible).

Kyouko Tenjou, who initially just kinda tagged along with Stella out of coincidence but then was the second one to become a Magical Girl. she’s harsh and abrasive, and ultimately has serious self-confidence issues stemming from her internalized transphobia (because she’s trans), but she has a heart of gold deep down and she generally tries to be a good role model for Madison in particular. she’s also Stella’s love interest. as a Magical Girl, she uses swords and psychic powers. stuff like telepathy, limited precognition, pyrokinesis...

and then after a few adventures of Stella supporting Madison and later Kyouko from the sidelines, she actually gets separated from them for a period of time, during which she meets the remaining two, who aren’t initially Magical Girls but do become them soon enough, and the three agree to stick together for the time while they try to get back to society. these two are:

Venus Bhatia, a violent and boisterous delinquent who’s ultimately actually second only to Madison in terms of friendliness. sure she’s violent, but if you haven’t offended her, she’ll be friendly (though her brand of friendliness is a bit intense to some people). she’s also a bit theatrical. when she transform, her whole vibe changes. her personality stays exactly the same, sure, but it fits both vibes, and her appearance changing is what brings about the change in vibes. in Magical Girl form, she comes off as more of a Female Prince-type like Kaoru Seta. also, she uses explosives. it’s very weird and specific compared to fists, swords, and guns, but it’s still got a practical offensive use. which is why it’s good that she was the first of the two to become a Magical Girl, because the second is...

Luna Flowers, a smug memelord and actual trained doctor who’s also got a slightly-hidden bitter and misanthropic side. and by slightly-hidden, i mean she tries to keep it under wraps and is generally just the smug memelord, but it really doesn’t take much poking to break down those walls and get her to express her true feelings. she’s also an amputee; as a kid, she got into a horrible car accident and her right arm had to be amputated at the shoulder. so, she has a robotic right arm. and as a trained doctor? it’s fitting that in Magical Girl form, she’s the team healer. in her Magical Girl form, the main event is her robot arm, which suddenly has a bunch of support tech built into it. healing rays, buffing rays, diagnostic equipment, and even a forcefield generator.

anyways, after palling around with Venus and Luna for a bit and the two of them become Magical Girls, Stella is reunited with Kyouko and Madison, and Venus and Luna decide to stick around. and after that, Stella finally becomes a Magical Girl herself.

#antagonist originals #oc posting

[curiosity-killed]

super long rambling and a fair bit of whining abt my relationship with dance AUs bc this is what my brain chose to fixate on for my whole extremely sloggish run

Because I love dance and because I love writing and because I do rather a lot of both, I pretty consistently struggle with my complete and utter block on writing dance AUs and I’ve basically realized that it comes down to a three-prong barricade that gets progressively harder to overcome as you move through it

Because part of it is just technical. Writing about dance is hard from a dancer’s perspective. I know dance, I know the mechanics of it and the sensations of it. I can walk you through the technical details of a 3-minute variation and I can tell you how my heart lifts and body fills with light the moment I step onto the stage. I can give you the nitty gritty and I can give you the grand metaphors—and I cannot for the life of me balance the lens on the middle ground.

I got asked on bumble what my favorite dance step is and immediately answered tour jete (or entrelace, depending on your school). And then, because the person wasn’t a dancer, I followed up with, “it’s a big fun jump that makes you feel like you’re flying.”

Yeah. That clears everything up.

A story cannot be made by a Big Jump That Feels Like Flying. Do you know how many steps that could cover?? Hell, how many disciplines?? A barrel leap is a big jump that can feel like flying. So is an Italian pas de chat. All three of these are  w i l d l y  different steps.

So there’s the words but—how to translate a language of precise motion and sweeping emotion into plain language accessible to people who haven’t grown up in this pidgin tongue of bad French and weird metaphors. Tombe pas de bourre glissade pas de chat contre temps—this is my language of dance. This is not only clear instruction on what steps to take but also the rhythm of it conveyed in the syllables and accents. I read this and not only see the dance across stage but feel the sway of my torso as I mark along, the flick of my wrist as I shape the steps before they’re taken, physical reminders of 17 years of training and study.

A reader reads this and their eyes glaze over and roll back in their heads.

To go the opposite way, to lay it all out in the actual physical motions is, if possible, even worse. Fall (gracefully) onto your right leg while extending your left with pointed foot to cross your left behind your right to step your right to the side to— *gasp for breath* Yeah, no.

The solution to this, in theory, is the kind of checklist I go through while performing: emotion, motion, technique. (Incidentally, this is the opposite of my checklist while rehearsing or taking class) Draw the reader in with the feel of it, move them with familiar steps, punctuate with the details. In theory. I’ve yet to make it work.

And then there’s the fact that I have had a very weird education and career in dance. I grew up dancing in the rural Midwest US—not exactly a hub of performing arts (and if you mention Joffrey, I will kindly invite you to look up “rural” and then look at Chicago). 

The vast majority of dancers in the rural midwest (...RMWUS??) go to competition schools. Think Dance Moms, high kicks and tricks on Instagram, trophies and tiaras. 

I.....went to a university.

We learned more about kinesiology than kicks. My teachers were fascinated by the way I could “jump like a boy” and didn’t once mention my waist circumference. It would be a lie to say it was all daisies and sweetcakes. We were competitive. Sometimes we were brats. We learned to push through severe physical pain and turned perfectionism to a weapon. Teachers had favorites and older girls could be downright mean.

But, having now danced at a competition studio, it was wildly different. When there were tears in the dressing room, it was because we were graduating and going far across the country from each other—not because a teacher had come in and yelled at the entire cast for 15 minutes right before the show. When auditions came around, we discussed each other’s strengths and weaknesses and together determined what we thought the best casting would be (tbc we did not have a say in casting, it was all just a thought exercise). 

We learned about dance not as an isolated thing we do but as a part of life—dance as an expression of culture, dance as a remarkable maximization of the human body—and are still always welcomed home.

I do, if I’m totally honest, think I got a better education than people at competition schools. But when it comes to writing fanfic...this is not a model of dance that is super easily accessible. Competition dance is on TV, Instagram, it’s all over. A rigorous academic approach to modern ballet...is not.

Lastly and ultimately the biggest stumbling block is: dance has always been a very gendered experience for me. My weird university education was surprisingly queer and unsurprisingly liberal, but I am a ballerina—not a danseur, not a ballet dancer. I grew up huddling under the edge of the grand piano with my friends hastily sewing pointe shoes and tingling with anticipation when we were finally old enough to wear platter tutus. I grew up pulling my hair back in tight buns and only being allowed to wear small earrings in class when I was in high school. 

There’s some crossover of course. I’ve got (as Colorado Ballet says) Mad Hops so my teacher would make me do men’s tempo jumps while the rest of the girls stood on the side and caught their breath. My partner for a pas de deux fell sick one tech week so my best friend, female, partnered me instead. 

Men can (and increasingly do) train in pointe shoes and wear tutus. Look at James B. Whiteside and Harper Watters for some of the most obvious examples. It is wonderful and remarkable to see gender roles changing in ballet and dance and that should be expressed in fiction as well. Men dance. Men do ballet and not just to hold up the women or to do big jumps. They can point their feet too, y’all.

(Here is where the whining really begins. Just so you’re warned.)

But when I sit down to write, the stories I want to tell are the stories I know—queer women growing up and training and learning together and challenging and supporting each other. The way you are taught ballet is very dependent on your gender. Men can train in pointe shoes, but that’s not the classical or traditional route. 

While my friends and I were taping our toes and grimacing about dead shanks, the guys in our cohort were in a separate class learning how to perform big jumps and turns in second. While I was cinching tight my friend’s corset-back bodice, the guys were in tights and a shirt. Again with the jumps—it wasn’t that I was a good jumper or that I was a strong jumper, it was that I jumped like a man. It was a compliment, but it was also an exception.

Meanwhile, most of my fandoms are very heavily male. The one time I attempted to write a dance AU was for VLD and I immediately ran into the baffling problem of “There are too many boys.” As someone who’s danced my whole life...this is not (usually) a problem in the real world of dance. If I write AUs about the main characters, I am writing about male dancers. Again, great! We need more positive and varied depictions of men dancing—but it’s not what I want to write.

I wrote out an entire paragraph here only to realize that the crux of the problem is actually the usual crux of my problem with gender in fanfiction and it is, quite simply: I want more well-developed female characters. Because I can write a story about side characters, but there’s so much less to go on — and sometimes, that’s where the fun comes in. Getting to play with and create a wealth of history and character for a written-off member of the cast can be really fun. But, for me at least, the delight of AUs is slipping in and twisting around canon in a new context.

If I write a wangxian ballet AU, Wei Wuxian’s demonic cultivation can be traded for his switching abruptly to a new studio—one that uses harsh methods, demands too much from him, cuts him off from the people he used to dance with—all so that the money from his tuition can be turned to help Jiang Cheng continue at his chosen academy and pursue dance professionally. It’s a stretch, it’s a twist, but it’s within a frame readers recognize.

If I write a ballet AU with Jiang Yanli and Wen Qing...well, it’s all free form. We have so little to go on that you can make it work—Cloud Recesses becomes a summer intensive, Wen Ruohan’s conquest becomes the buying out and closing of the Jiang academy for some new development—but there’s less resonance. We’re on new ground and the reader has to offer up a lot more trust and disbelief. 

Which I suppose leads us to genderbends?? Good lord. I do not know my own feelings about that enough to go anywhere. b l a r g h

so i guess this is all to say: writing good, dance good, writing dance hard. pouty face pouty face pouty face :<

#long post #personal #BEHOLD A VERY VERY VERY RAMBLING LINE OF THOUGHT

[sonipanda]

Now let’s be creating some little statements with a new brand! This company got in touch and wanted me to test out their products. At first, I thought they were a little different to what I was used to (mainly because they’re a thicker denier with different designs) but I really had to give them a go.

I have to say their whole brand is pretty quirky – and it’s something that is right up my street as long as I can style them right!

Oh and this is also Blog 1 of 2 – I have another one coming up for you all tomorrow 🙂

  About 77Denari

77DENARI is an Italian line of tights & socks of Italian manufacture produced in limited edition.

The line has an experimental and at the same time ancient character: the tights, of an elastic nature, are in fact printed according to the original artisan method and with water colors, a technique in use for “still” supports of natural origin.

Every single graphic element has changed to a frame, thus becoming an absolutely prized piece, a unique piece, and the ethical-aesthetic choice of using water colors alone makes the product complex and innovative; therefore the study of colors, designs and print media are the result of a combination of ingenuity and magic, feasibility and disruption of the rules.

77denari was born in 2012 and is composed of 8 tights / stories per collection; starting from 2018, 77news grows and launches the Socks collection, and the “STRIPPANTI” Other Line.

The entire creative and printing process is carried out by the two founders of 77denari, Simona Berardi and Carla Armillei, and is inspired by the crude vision of geometric elements typical of the instinct of Nature.

77denari also boasts the collaboration of various artists working in the field of graphic design and illustration, photography, music, video and styling. Each of them supports the project becoming an integral part of the creative process; their participation opens the circle of possibilities towards still unexplored and seductive alchemies, and they contribute to creating, for the 77DENARI project, an imprint that is renewed over time.

The idea on which the project is based is the desire to give “beauty” an extra value, in which harmony and proportions of the parts go beyond the absolute, of time and memory, and focus on the “Physical soul” of intrigued consciences. In this case in fact the work is worn and moves: it walks, runs, dances and lives stories, reinterpreting the proposed contents with its own voice, and in the meantime creating a new identity.

Tights – talisman therefore, capable of breaking the classical scheme of gender and form and of ruffling with wonder.

A special thanks goes to the “DUEC Calzificio” and to our consultant Renato Altimani.

– taken from their website

The Spec

Colour: Cream

Style: #55

Size: One Size

Denier: 60

Materials: 85% polyamide, 15% elastane

Price: N/A

Website: 77Denari – A/W 18-19 #55

My Outfit

Instead of creating something loud, I thought I would incorporate the tights into my outfit. I wore my cream bodysuit paired with my teal skirt and added my mustard boots to finish off the look. You could easily pair any other colour footwear with them to create a colour block, but I wanted to fuse it altogether to create a piece 🙂

My Deets

Bodysuit: Pull & Bear

Skirt: H&M

Tights: 77Denari

Boots: New Look

    The Review

From The Website: 77denari, for autumn-winter 18/19, explores the vast world of feelings, and the multiple points of view they can generate. Thanks to the senses, the body in fact receives information from the interior and exterior environment. They are accessing the world itself within us. Each of them has the ability to form a perceptual opinion before the action of intelligence.

We have been taught that there are five senses: sight, hearing, taste, smell and touch, and that is anatomically, but also admits that we have a thermal sensitivity, and we know how to recognize the sense of well being, pain, or discomfort of the organism as a whole.

For this reason 77denarians have explored various currents, which have identified from 9 to 21. We have embraced 12 of them; precisely 7 more than the 5, through which we think we can fully experience our perception, and then transform us into what surrounds us, to try to increase that degree of cooperation, according to which individuals build together a reality and a shared truth.

– 100% made in Italy: the basic pantyhoses and socks are made by Italian manufacturer DUEC Calzificio located in Goffredo Castiglione;

– 100% handmade screen printing: no use of printer;

– composition: 85% polyamide and 15% elastane;

– one size fits all: the basic product is extremely elastic for sizes S-M-L;

– drawings only with water colors;

– limited edition: max 100 pieces for model;

– high resistance and durability of the design: hand washing at 30 degrees is recommended.

  The Packaging: now I have to say how impressed I was with their packaging. They were sent in a super padded envelope, in 2 small boxes.

Very simple, but they are certainly different and I love it. Even though there isn’t much detail to them in terms of model, sizing, blurb about the hosiery etc, they still aren’t bad at all.

  Getting Them On: now as the pattern is symmetrical on each leg, I took my time doing the scrunch and roll up the legs making sure I pair it as evenly as I can so I don’t have to do it again later.

These were fine rolling up the legs, and going over anklets. I had no issues at all – if anything they were super soft and so easily to glide right up.

  On The Legs:

well all I can say is how funky are these?!?!?!

The quality of these are really good I have to say. They are such a gorgeous fit on the legs; even if they are a one size pair! They have so much stretch to them and really do hug the legs well. I expected them to be slightly loose, but in actual fact that is not the case!

They look like they are a block cream colour, but if you stretch them (like how they stretch on my thighs) they do go slightly lighter. You still do get really good leg coverage overall, but it’s something to note if you want a true opaque block colour.

The design is super awesome; I have done something similar a while ago with a Jonathan Aston pair (called Dynamic) which was black sheer with a black design and they really rocked. I love how they have worked the black and goldy-yellow colour at the side of the legs, which gives you the opportunity to actually pair up colours easily with it. As I mentioned, I kept with my mustard boots, but I could have easily done purple or blue (with a different skirt too) and it would just enhance the colour and design even more.

The only downside I had was that the print was a little off on the left leg; it’s like it got stuck and slightly peeled off a little. It’s nothing major but if I’m going into the nitty gritty details, that is something I picked up on when I got them out the packaging.

The fit of these are great; as I said for a one size pair, these are fab. I do feel it could fit up to a large size but you would be looking at a sheerer cream colour than a block opaque.

The feel of them are super soft and so nice on the legs. They’re smooth (both inside and out), they’re soft to touch and they really do caress the legs.

  The Toes & Ankle: are also great. I expected some chunky seams around the toes creating little bumps around the ends but nothing of the sort. They fit and shape to the toes really nicely so you get a smooth looking finish. This also carries around the foot and up the ankles too.

You will find these will wrinkle slightly around the ankle due to the higher denier, but nothing too major.

I do think these are reinforced – and I will say that as the denier is quite thick so it would be pretty hard to create holes in these!

  The Waistband: is so soft and so comfortable I don’t wanna take these off! I love the way they sat on the waist and actually just moved with me. They don’t fall down or move out of place once you set them, and they certainly don’t lose elasticity quickly either no matter how many times you pull them down and back up again.

It’s a proper comfort band, and I really like it!

    My Thoughts?

I gotta say I really loved being in these. They were such an experience. I know most higher denier can be a hit or miss, but these are a pair which I would class as a luxe pair. I say this purely because of the way they are made, how they feel on the legs and the quality is just lovely. Trust me when I say when you roll these on, you instantly tell what they’re gonna be like for the next 10+ hours!

I am so looking forward to my 2nd pair I get to try out!

77Denari A/W 18-19 Cream Printed Tights Now let's be creating some little statements with a new brand! This company got in touch and wanted me to test out their products.

[vios-rockland-corner]

I attempted to draw my Rockland OC Sasha playing pool...it did not go well.  I hate the face.  I tried to draw a hand close up to make up for the disgrace, but I don’t think it does.

Oh well, it’s part of my rule that I can’t talk about Sasha unless I draw her.  Helps me practice (but does not guarantee the picture will turn out great).

Well to be exact, I actually just wanted to talk about another character I’m trying to develop who could be a friend of Sasha.

I’m usually not fantastic at making side characters, but this one’s been forming in my head pretty well over the last few days.

I might make Sasha’s best friend a guy name Pierce (name pending- especially if a canon Rockland character pops up with the same name soon).  He’d be someone that she’s known for a long time, either from elementary or middle school.  I don’t know their ages yet, so I can’t say exactly how long.  They’d be super tight though and comfortable with each other.

I was trying to think of what Sasha does in her spare time.  At first I was thinking she had a gal pal who had a tendency to drag Sasha around as her designated driver so they could go to bars.  Yeah, Sasha would be a good designated driver, but that doesn’t sound as fun.  However, lots of bars and pubs will sometimes have pool tables, and I thought, “Well I could see Sasha going to pubs/bars if she’s with a friend and they have a little something more to do than just chat or scope out the scene!”  So that’s where Pierce comes in.

Pierce is a fantastic pool/billiards player.  Loves to play and he’s great at it.  Sasha also loves pool, and is decent (but not as good as Pierce).  So Sasha actually enjoys playing against Pierce to get better at the game, and Pierce enjoys having someone with the persistence to keep playing him.

Funny thing is though, while both Sasha and Pierce would be friendly and helpful if they were playing anybody else, when these two play together they talk a lot of smack and start roasting each other.   These two have just known each other for so long that it’s more out of good fun and competitiveness than mean spirit.

Pierce wins the vast majority of the time, but on a rare occasion Sasha has pulled a couple wins (which just encourages her more to keep playing).

They may make small bets like, “You’re paying my tab if you lose,” though Pierce tends to avoid as many monetary bets because he known he’d starting draining Sasha’s wallet ;)  (To which Sasha would retort, “Oh we’ll see about that.”)

Couple of reasons I like this setup:

1) I think it’s a decent pastime that both keeps them active in their own space as well as opens up opportunities to meet/interact with other characters in the world

2) Pubs and bars I’m sure would be great places to hear lots of odds stories and rumors...like about people going missing >:)

3) This is a little extra reassurance to keep Sasha safe, having the two of them together a lot in a public space

4) It’s a funny setup considering these two are NOT dating, but they often get mistaken as boyfriend and girlfriend.

At the moment, both characters are single.  They don’t even consider dating each other.  When people ask, they basically both give the same answer: “I’ve just known them for too long.”  They often treat each other more like siblings than potential partners.  They’re at this point where literally either could be hanging out at the other’s place, walking around in a towel after a shower looking for something, and they’d just treat it as casual (maybe a little joke thrown in though).  It’s not that either of them are gay or lesbian, they just feel like they’re life friends, not partners.  Although if either has to find a roommate to save money on living expenses, they’re each other’s first choice.

But of course, to the public eye it might not be easy to tell.  It has DEFINITELY been problematic at times for each to find a boyfriend or girlfriend unless they’re hanging out by themselves.  There’s been some problems before where the person they’re dating doesn’t like how cozy Sasha and Pierce can get with one another.  Sasha and Pierce are the same though where, “If I’m dating someone who won’t accept my friendship with my childhood buddy, then they’re not worth dating.”  

Pierce would also probably make a joke that if he married Sasha, “But then I couldn’t be the uncle who can spoil her kids rotten and let her know when she’s getting fat!”

If people they’re not fond of start to bother them too much when they’re playing a game of billiards, their usual strategy is to just start upping the smack they talk with one another (still only to each other) to the point where the other people just can’t get a word in and feel like they’re not even part of the scene.  If they don’t know that Sasha and Pierce aren’t dating, Sasha and Pierce will also use each other as an “emergency girlfriend/boyfriend” if there’s someone they want to deter (obviously doesn’t work if somehow the other party is already aware they’re just friends).

Pierce and Sasha will watch each other’s backs though.  If it looks like someone bad is getting too close, they’ll find a pool stick shoved in their way.  Pierce might actually even smack a dude’s hand “on accident” with a pool stick if he saw them trying to get a little too handsy with Sasha.  Otherwise, they just leave and head to the next bar/pub if a place isn’t working for them.  People can look, but no touch (unless it’s obvious Sasha or Pierce is interesting in whoever new person they’re talking to).

Pierce is probably pretty good looking.  I don’t know what he looks like yet though 0.o I didn’t try to draw him because honestly I’m even worse with male characters (both drawing and coming up with something original).  Pierce probably gets more attention than Sasha though in public.  Thinking he’s maybe 5′9″, but still debating on that.

Seeing as I changed talking about Pierce as a “would be” to an “is” here, pretty sure I’m going to try to keep him, but he could change in some ways.

Bonus:

I guess I could share HOW I came up with Pierce because it’s...kind of funny.  I was in the mall and walking through one of the clothing departments when I passed by the lingerie section.  I am a woman, but I still always feel a little weird walking through there.  Some stuff looks nice, but I think I’m just shy, haha.

I thought for a moment would Sasha be more of the type to shop for lingerie?  I’m thinking...I don’t think so, but what if she was there with someone else?  Somehow it turned into me thinking about a serious conversation Sasha was having with a friend, who was advising her to basically be careful and keep herself safe (long story regarding a backstory I’m not sure I’m keeping).  Anyways, the end of the conversation goes something like this:

Pierce: “Alright, now that I’ve done my sacred duty as your friend, advising you to stay out of trouble...take me to the lingerie section.”

Sasha: “Why do you ALWAYS want to go see women’s underwear when we go to the mall together?”

Pierce: “First of all: Don’t call it underwear, that’s so undignified.  Second: Because if I go there by myself, either I get girls giving me a disgusted look or little old ladies creeping on me saying I must be such a good boyfriend looking to buy something for my girl.”

Sasha: “Well yeah, pretty sure it IS weird for a dude to walk around there alone...”

Pierce: “Yeah but if I’m with you we just look like we’re shopping as a couple.”

To clarify, Pierce thinks lingerie is basically like a work of art.  He just likes looking, he doesn’t have a reason to buy it.  He doesn’t like if Sasha calls it “underwear.”  He’s well aware Sasha wears either boring underwear or just oversized shirts to bed, which he feels is a waste.  He often says she needs to treat herself and “upgrade.”

I imagined one time Sasha got annoyed and offered to “model” for him at her place with some lingerie she just bought, just to get his opinion.  She purposefully picked something ugly though (I keep thinking “pineapple lingerie” for some reason because that sounds pretty unsexy to me).  Pierce was appalled and said, “Burn it.”  Would also be another fun reason why Pierce could never really view Sasha as sexy XD

Sometimes Sasha’s not entirely sure if Pierce is more interested in women wearing lingerie...or really just the lingerie itself, haha.

I’m not sure if I’ll keep the lingerie fascination.  It’s funny, but debatable whether it’s just perverted or an odd “sophisticated taste.”  I could throw it out and keep the stuff I mentioned earlier.  It’s just weird that’s how I came up with this character.

#rockland #sasha holmes #pierce #my OC #my art #billiards

[acoustic-accompaniment]

You realize 76 has a dedicated team and are working towards fixing the major issues right? This is a game they don't want to put down until both them and the community enjoy it to its full extent. Also you realize they had to COMPLETELY rework and remake the engine for it to work with multiplayer. It's not like they took the fallout 4 one and just added a bit. That's not how it works but for some reason ever since fallout 76 came out everyone's an expert on it fuckin lol

Hey, buddy ol pal, you do realize that fallout 76 is literally the same engine and they've admitted it since the beginning? Or how about the fact that they've also admitted that it was never meant for multiplayer? Or what about them admitting they've never had a different team to work on the games and always tried the same things because they work? Or how about the fact that no matter how much you rework an engine, it'll never be good if it was never meant for such things?

You don't need to be an expert on a game to realize the potential it could have reached given a better engine, team, or even proper time. A community has a full right to enjoy a game, but when the vast majority of players don't enjoy it, I think it's cause for alarm. It also doesn't help when bosses are copy paste and the quests hold no emotional grounds to keep the players interested.

I know you want the community to back off a game you enjoy, but the fact of the matter is that it's not a good game. I very much enjoyed Fallout 4, but I still have to admit it had many flaws, and the same goes for 76.

Also, your argument that they're "fixing the game" shouldn't even be an argument. The game was broken and buggy on launch and is still that way. A game should never launch in such a state to where it needs a 56 GB patch.

You're angry, I get it, but you have to understand that this is a bad game. I pointed out that it's okay to enjoy them before you got too scared to say anything worthwhile and decide to pester me on anon, but the fact that you had to even go on anon shows that even on some level, you know the game is bad too.

And again, you don't need to be an expert to know if a game is bad. Just like you don't need to be an expert to know if a book, a song, a drawing, or even an action is bad. Yes, there are subjective things to all of those, but there's also technical and objective things to bad things that anybody can notice.

Just lay down, have a glass of water, and come back when you're ready to point out the good things and have a discussion about it.

Edit because I should've included some of the actual problems:

The push to talk system was never implemented, the dialogue is even worse that Fallout 4, the audio logs can't be paused for replayed, and the world quests can interrupt them so you miss out on the only reason to actually play it.

The combat is way too easy, dying means nothing other than a little bit of lost progress, PvP boils down to either both of you slamming stim packs into yourselves till one of you dies or you stalemate or you end up one shotting them because there's no countdown for PvP combat and the one who initiates it does basically no damage till you fire back so you can go up with your strongest weapon and fire it off in their face to instantly kill them.

Or the biggest offender is that some of the quests go against precious lore so if you're actually following the most interesting things the game has to offer, it contradicts what's already in place.

The game has no encrypted data so you can literally track someone's IP address without even breaking a sweat and leaving all your important information open, the console isn't hidden very well, you can use script mods with little to no repercussions, sometimes mobs become invincible for no reason, sometimes mobs spawn in the ground, spawn times are that of 10 seconds sometimes, grenades will clip through the floor on slopes sometimes, and not even big slopes, power armor makes your model broken, sometimes your character will T-pose for no reason, the menus won't load sometimes and you won't be able to play the game, you can kill somebody just by taking them into your base and deleting the floor, you can get stuck in the ground, sometimes your model will be in the ground and if you go in first person you'll have to deal with something that could literally trigger epilepsy or become so nauseous that you'd have to quit playing, mobs will sometimes float in the air, mobs will sometimes become non-hostile no matter how many times they respawn after death, the micro transactions on a $60 game, which also means that your credit card information could get stolen because The Game Isn't Encrypted!

Need I go on anon?

[it-goes-both-ways]

Over the last few years I've been posting more and more of my actual views, which I'm not exactly ashamed of but realise they're not so much unpopular opinions as downright rejected ones. I pretty much know why I have them, I'm aware of my biases and make every effort to restrict them to words, not allowing them to affect my relationships or treatment of others, restricting the hyperbole and rants to this blog and my long suffering partner. Unfortunately I seem to attract the worst kind of women in real life, which is not at all helping. Every time I reveal something I worry about being rejected, told I'm a monster, a failure, a disgrace, an embarrassment, but each and every time I've gotten nothing but acceptance. I am greatly honoured by your support thus far, for tolerating my increasingly frustrated outbursts and hope I won't push you away with this, but it's been all consuming for almost my whole life, and part of “cleaning up my room” is putting all that baggage out there to be scrutinised and hopefully understood, sometimes all that is needed is a willing ear, suppression only breeding resentment and isolation.

All the bullshit feminism has caused, from protesting the male pill and shutting down shared parenting efforts to the Duluth model and erasing men who are raped by women or by counting them under "violence against women" stats to boost the female victim numbers. Mary Koss, the progenitor of the 1 in 5/4/3/-69/ π r2 stat claiming that it's "inappropriate" to consider male victims of forceful envelopment by women as they are merely ambivalent about their own desires. Lobbying for laws that regard mutually drunk sexual encounters as automatically rape by men, underage consensually sexually active couples (even if they're months away from age of consent or the girl is older) as child rape on the part of the boy, guilty until proven innocent, accusation is the evidence, kangaroo courts, sentencing discounts on top of the preexisting bias which causes a 63% disparity and difference in treatment to the point where if you take every step of the justice system into account the crime rate is pretty damned even (with women often using proxy violence so they have plausible deniability, and avoid responsibility/physical risk). Treating women as the definitive victims of prostitution no matter which side of the transaction they're on. Banning men from charity fundraising events, transpeople only allowed if they provide evidence that they are biologically female. Having the NHS class women choosing to have genital piercings as being victims of female genital mutilation, while male genital mutilation performed at birth is not so much as frowned upon let alone illegal by any single country on the entire twatting planet. In fact you can buy some baby foreskins if you want to, or rub them on your face, the target market being protected from the very process that brought them their anti-ageing face cream, complaining that it costs more than men's moisturiser.

The innate gynocentrism of humanity has always led to women being their top priority, now even above children, it tries to pander, and acquiesce to their every demand while being told it hates them. The cases like the woman who filmed herself raping her own baby and getting the oh so harsh sentence of community bloody service and house arrest. The "poor, neglected" woman whose husband had become distant from her (wonder why) so she raped her son's friend, whose punishment was being banned from his school, which she considered too harsh as she missed her son's graduation. An audience of hundreds of normal regular women cheering and celebrating a man being drugged by his wife, who then cut off his penis and threw it in the "garbage disposal" permanently destroying it, just for asking for a divorce (can't think why he'd want to leave), despite no further context it was declared "fabulous" to the ecstatic jubilation of the empathetic sex. There's the idea that men commit the vast majority of rapes while calling female teachers "seducing" their students mere trysts, shameful liaisons that do not deserve prison, female prison guards committing the overwhelming majority of rape of male children and youths in juvenile detention (89%), among other women who rape men and boys (my own mother being one of them), this in addition to the rape rate among female prisoners being 3 times that of male ones, not a single damned thing is done about the propagation of the bullshit narrative. Somehow the fact that female rapists tend to target children is irrelevant because male ones target adult women, and "you don't see women going around raping adult men" (even though the stats are still around 50/50 because it's a human problem, unless those women are exhibiting toxic masculinity or something). There's the 10,000 men and boys slaughtered in their schools by Boko Haram while girls were released and allowed to go home, the boys being set on fire, their throats slit, or shot if trying to escape, no one giving the slightest hint of the merest ghost of a toss, until they realised that they weren't getting the attention they craved so they kidnapped girls, causing an international outcry and the media/celebrities changing their motivation from "eradicate western education" to "oppress women and stop them getting an education". There's the refusal by both the left and the right to look beyond the plight of women when it comes to Islam, they not only ignore the laws which oppress men, but declare those men the "real" misogynist patriarchal oppressors and innately sociopathic rapists. There's the refusal to recognise that women are a part of society and have far more influence than anyone wants to admit. There's Muslim men's obligation towards women, the segregation in Saudi where they have many public places from which men are banned unless accompanied by a female family member, where they'll be arrested for accompanying a woman to whom he is not related while the woman is merely sent home, where men face potentially fatal consequences for the same "crimes". Where homeless boys in Pakistan are pretty much guaranteed to be repeatedly raped day after day.

Then in my own life, being 6 or 7 years old, my sister 8 or 9 and told to stay put as our Reliant Robin went up in flames, having to be pulled out by a stranger, a man, because we were more afraid of disobeying than of burning to death, mother not even sparing us a glance as she grieved the loss of her car, later keeping it in the garden like some sort of shrine. Around the same year, at an LRP event (Lorien Trust's The Gathering), being left in the tent alone late at night and going to look for her, finding her on top of an unconscious man, she at least picked up on the fact that I was revelling in her severe hangover the next morning. Sneaking downstairs one night to see the aftermath of one of her "encounters", the man was broken, so started my extreme protectiveness of men and distrust of women, to the point of being called a gender traitor for the first time at around 7 years old by my 60+ year old year 1 teacher (who also wouldn't allow me to use left handed scissors or to write left handed, unwittingly making me ambidextrous. Being left with a violent babysitter who made me sleep under the table, or on the floor beside her bed (despite having 4 bloody beds), who wouldn't let me eat since burning the toast, beat me for asking for a glass of water and wouldn't even allow me to drink out of the tap, she once threw me in a wheely bin and poured dishwater over me, mother was in the garden just a few doors down, yet did nothing. She’d always try and get her boyfriends to beat us but they always just laughed it off (they’d put up with abuse themselves but never lasted long after she started bringing us into it), one in particular was into BDSM and later got mother a job as a dominatrix (she was disappointed by our complete lack of surprise), and even he had to draw the line at demonstrating how sexual intercourse works to his girlfriend’s 6 and 8 year old daughters.

My sister and I as little more than toddlers, mother putting our onesies on backwards so we couldn't take them off, having to go to the loo with them still on. Having the door handles put on upside down so that we couldn't reach up enough to open it to get to the loo so we ended up pissing ourselves. Having a daily diet of four slices of bread and the cheapest of generic vegetable spread as we weren't allowed mother's butter, being starved as punishment or just because she felt like it (having won custody of us only to spite dad), leading to malabsorption and osteoarthritis at the grand old age of twenty bloody six (3 years ago now), once a week we got an actual meal. Being around 8 or 9, visiting my auntie who was in hospital after having a stroke, having already had MS she was left paralysed, just 23 years old, granddad put together a system for her to speak by grouping letters and having her blink once for the stated grouping or letter or twice for basically undo. I gave her my only teddy which I carried everywhere, a stuffed donkey I got from Spain, she kept it. Staying in her house, continuing my habit of accidentally setting fire to the toaster, being left alone most of the night and going to look for mother in the village pub, finding her in one of her drinking competitions, walking in and vagblocking her, much to her frustration and anger. Being treated like a replacement husband, even trying to talk me into having a sex change despite only mild dysphoria, which was later greatly lessened by having an implant which stopped periods, eliminating most of the feeling of wrong (most cases of sex change regret are people who were abused, either treated like shit for their biological sex, treated as if they are opposite sex, or sexual abuse). Hearing about how the only way she'd get any when she was with dad was when he was asleep. Why did he end up dying a slow, agonising death while she gets to carry on regardless? Asking me about who I liked, later discovering exactly why she wanted to know, a man I care about was raped because I didn’t pick up on her ulterior motives. Having mother and her friends try to teach me to manipulate men, get them to pay for me, trying to turn me into a gold digger, only making me hate them even more. Coming of age (16), no longer eligible for child benefit, mother having been visiting friends more and more often until she didn't come back, only finding out that she'd been gradually moving out when we got the eviction order.

I'd been training myself to eventually join the army from the age of 5, once when I was 6 mother had asked me to go to the supermarket to get a bag of potatoes, she usually got a 20kg sack, must have taken me an hour to get it home, a man helping me carry it some of the way. When I finally enlisted I had to stop taking codeine for the malabsorption, it wasn't as much of a problem if I was eating every day (I usually forget as my body had been conditioned by neglect, not even bothering to remind me to eat any more), my hips had always made crunching and cracking sounds when I move, but as my body adjusted to the lack of codiene the pain became unbearable, upon being diagnosed with osteoarthritis I had to give up any hope of ever being a soldier, I've lost my purpose, and have nothing to replace it with, couldn't even work a whole shift when I got a factory job, humiliating, I'd informed the woman of my condition and she'd assured me that it was just a machinist job. It wasn't. It was everything you shouldn't do if you have any sort of hip problems. I'd never felt such agony and I'd fractured my bloody skull (at an LRP event). The woman was such a nasty bitch about it, she went from compassionate and understanding to mocking me for being upset that I was so damned useless now. I offered to forfeit my pay but her colleague, who also had arthritis and could no longer work the floor, was obviously far more genuinely empathetic than the woman, my brief boss was also sympathetic and even paid for a taxi to take me home after I refused an ambulance. The pain didn't subside for days.

I've never had a female friend who hasn't betrayed me, my "best friend" in school found it hilarious to punch me in the back in the middle of class, causing me to yell inadvertently as the air was knocked out of me. In year 8 the other kids stepped up their game and went from throwing stones to a house brick, when I got back to school she asked where the stitches were, just so she could punch me and reopen the wound. I was never allowed to retaliate, it would always be me who would be threatened with expulsion even if I only snapped after years of beatings which everyone knew was happening. Every birthday the other kids would falsely accuse me of something so I'd have to spend break times stood outside the headmaster's office, the equivalent of the stocks. Whether it was asperger's making me so unlikeable or if I genuinely am just a massive thundercunt, I never found out what I did to provoke them. Every time I put my trust in a woman it gets thrown in my face. My neighbour decided she was my best friend for life and would call at all hours of the day and night to get me to pick up her bloody methadone twice a bloody week, go to the chippy at 11 o'bloody clock at night, she's always trying to get me to take the pills she buys off a disabled neighbour. There are three things I refuse to take, hormones, anti-depressants, and sleeping tablets and she's always trying to get me to take them. The last straw was when her husband, who I got on very well with and whom she abused constantly, died, I told her to be careful what she wished for. When I finally called her out on using me she leapt immediately to the "after all I've done for you" bollocks.

Time after bloody time it's the same damned story, even regular everyday normal women will talk about things that would get a man arrested or at least publicly lambasted, that erections equal consent, that MGM is not at all a violation of the right to bodily autonomy, that it's absolutely fine and dandy to hit your male partner only to call the police if he defends himself, that female paedophiles shouldn't be punished because boys always want sex no matter what age they are but girls mature younger, right the way back to "We should have the vote but not have to pay with our lives as men had to in their millions while we shamed men and even underage boys into doing the same". What terrified me as a child was women's ability to completely turn off their empathy, the "woman scorned" is seen as karmic justice, there are people defending even the most brutal crimes:  assault, murder, rape, mutilation, over something as minor as rejection, or an accidental drive by fart, or just the crime of being a man who wanted a divorce. Empathetic sex my absolute arse.

A fellow MRA publicly humiliated Adam on a livestream when we went to the men's day march and conference, we were staying in an air B&B, Adam and Will Styles still riding the high of giving their first speeches, only for the woman to dredge up shit that was no one's bloody business and ruin the whole mood for no bloody reason, she also attacked 6oodfella on one of the hangouts. Another one was giving private information, with a vicious twist, poisoning the community against one of our group, Paul Elam didn't want to get involved and Janice Fiamengo immediately cut ties, treating him like a bloody criminal, what the hell did the woman say to her? I could see the Woolly Bumblebee thing coming a mile off, I worry whenever youtubers I like get girlfriends because they seem to either completely change or disappear, like Spino and Bread and Circuses respectively. I'm suspicious of female MRAs, I don't want to be but often even the sane ones are just tradcons. If it weren't for the Honeybadgers and you lot I'd have no hope at all.

The constant stream of "toxic masculinity", oppression, patriarchy, of women complaining that their air conditioned (which is also bloody sexist somehow), seated jobs at a till are paid less than the men (and women but they're not going to mention that) carrying heavy boxes, driving forklifts, working in a cold warehouse, and risking serious injury or death infinitely more than they ever will. The selfishness, solipsism, and sociopathy is too much. Throughout history women have never cared about men aside from ones they have a bond with, have never appreciated a damned thing men have done yet they demand that men prioritise them. Why should they?

I’ve seen and experienced the worst examples of female nature in action, “toxic femininity” if you will, and the difference in reaction to it, never being believed as a child no matter how many times I begged other family members and even strangers to please let me live with them instead, I’ll sleep in a tent, look I brought it with me. Pathetic, but you’d have thought someone would have cottoned on. I'm not going down the anti-women route as my sister has, given her own treatment of her partners and her own admission, she’s not so much pro male as anti-female, but it’s increasingly difficult not to resent them even if everything has a biological explanation. I still defend women if the facts bear it out, even if I don’t necessarily agree on a personal level, reals over feels, the people I agree with most also being female has definitely helped me not fall over the edge, one of whom feels very much as I do to the point where she doesn’t consider herself to be a woman due to her own observations and experiences. But the longer this goes on, the more laws are changed, media is poisoned, speech is suppressed, how the hell do I stop myself from just giving up entirely? How on earth can I stop myself from becoming an all out misogynist? Because it is women, not just feminists. It’s female nature being allowed to go unchecked, even when the same happens with male nature women are still prioritised. There are exceptions on both sides but it’s not enough to change the overall trend. There’s never been a balance, and because of human nature there never will be, which is where the problem lies. I know there’s no hope, that it’s utterly futile, completely pointless, and it’s driving me more towards extremism. I completely understand why we’ve lost so many MRAs to suicide. But I’m still going, even if the only way to make even the slightest change is to appeal to female self interest I’ll still do it. Everything I’ve been passionate about throughout my life is a pointless endeavour, I can’t stop myself from caring or change my fundamental character, it’s a downward spiral and there doesn’t seem to be anything I can do about it.

#Personal #Very personal

[lakelandseo]

SEO Forecasting in Google Sheets

Posted by Tom.Capper

Way back in 2015, I published an article giving away a free, simple, forecasting tool, and talking through use cases for forecasting in SEO. It was a quick, effective way to see if a change to your site traffic is some kind of seasonality you can ignore, something to celebrate, or a worrying sign of traffic loss.

In short: you could enter in a series of data, and it would plot it out on a graph like the image above.

Five years later, I still get people — from former colleagues to complete strangers — asking me about this tool, and more often than not, I’m asked for a version that works directly in spreadsheets.

I find this easy to sympathize with: a spreadsheet is more flexible, easier to debug, easier to expand upon, easier to maintain, and a format that people are very familiar with.

The tradeoff when optimizing for those things is, although I’ve improved on that tool from a few years ago, I’ve still had to keep things manageable in the famously fickle programming environment that is Excel/Google Sheets. That means the template shared in this post uses a simpler, slightly less performant model than some tools with external code execution (e.g. Forecast Forge).

In this post, I’m going to give away a free template, show you how it works and how to use it, and then show you how to build your own (better?) version. (If you need a refresher on when to use forecasting in general, and concepts like confidence intervals, refer to the original article linked above.).

Types of SEO forecast

There is one thing I want to expand on before we get into the spreadsheet stuff: the different types of SEO forecast.

Broadly, I think you can put SEO forecasts into three groups:

“I’m feeling optimistic — add 20% to this year” or similar flat changes to existing figures. More complex versions might only add 20% to certain groups of pages or keywords. I think a lot of agencies use this kind of forecast in pitches, and it comes down to drawing on experience.

Keyword/CTR models, when you estimate a ranking change (or sweeping set of ranking changes), then extrapolate the resulting change in traffic from search volume and CTR data (you can see a similar methodology here). Again, more complex versions might have some basis for the ranking change (e.g. “What if we swapped places with competitor A in every keyword of group X where they currently outrank us?”).

Statistical forecast based on historical data, when you extrapolate from previous trends and seasonality to see what would happen if everything remained constant (same level of marketing activity by you and competitors, etc.).

Type two has its merits, but if you compare the likes of Ahrefs/SEMRush/Sistrix data to your own analytics, you’ll see how hard this is to generalize. As an aside, I don’t think type one is as ridiculous as it looks, but it’s not something I’ll be exploring any further in this post. In any case, the template in this post fits into type three.

What makes this an SEO forecast?

Why, nothing at all. One thing you’ll notice about my description of type three above is that it doesn’t mention anything SEO-specific. It could equally apply to direct traffic, for example. That said, there are a couple of reasons I’m suggesting this specifically as an SEO forecast:

We’re on the Moz Blog and I’m an SEO consultant.

There are better methodologies available for a lot of other channels.

I mentioned that type two above is very challenging, and this is because of the highly non-deterministic nature of SEO and the generally poor quality of detailed data in Search Console and other SEO-specific platforms. In addition, to get an accurate idea of seasonality, you’d need to have been warehousing your Search Console data for at least a couple of years.

For many other channels, high quality, detailed historic data does exist, and relationships are far more predictable, allowing more granular forecasts. For example, for paid search, the Forecast Forge tool I mentioned above builds in factors like keyword-level conversion data and cost-per-click based on your historical data, in a way that would be wildly impractical for SEO.

That said, we can still combine multiple types of forecast in the template below. For example, rather than forecasting the traffic of your site as a whole, you might forecast subfolders separately, or brand/non-brand separately, and you might then apply percentage growth to certain areas or build in anticipated ranking changes. But, we’re getting ahead of ourselves…

How to use the template

FREE TEMPLATE

The first thing you’ll need to do is make a copy (under the “File” menu in the top left, but automatic with the link I’ve included). This means you can enter your own data and play around to your heart’s content, and you can always come back and get a fresh copy later if you need one.

Then, on the first tab, you’ll notice some cells have a green or blue highlight:

You should only be changing values in the colored cells.

The blue cells in column E are basically to make sure everything ends up correctly labelled in the output. So, for example, if you’re pasting session data, or click data, or revenue data, you can set that label. Similarly, if you enter a start month of 2018-01 and 36 months of historic data, the forecast output will begin in January 2021.

On that note, it needs to be monthly data — that’s one of the tradeoffs for simplicity I mentioned earlier. You can paste up to a decade of historic monthly data into column B, starting at cell B2, but there are a couple of things you need to be careful of:

You need at least 24 months of data for the model to have a good idea of seasonality. (If there’s only one January in your historic data, and it was a traffic spike, how am I supposed to know if it was a one-off thing, or an annual thing?)

You need complete months. So if it’s March 25, 2021 when you’re reading this, the last month of data you should include is February 2021.

Make sure you also delete any leftovers of my example data in column B.

Outputs

Once you’ve done that, you can head over to the “Outputs” tab, where you’ll see something like this:

Column C is probably the one you’re interested in. Keep in mind that it’s full of formulas here, but you can copy and paste as values into another sheet, or just go to File > Download > Comma-separated values to get the raw data.

You’ll notice I’m only showing 15 months of forecast in that graph by default, and I’d recommend you do the same. As I mentioned above, the implicit assumption of a forecast is that historical context carries over, unless you explicitly include changed scenarios like COVID lockdowns into your model (more on that in a moment!). The chance of this assumption holding two or three years into the future is low, so even though I’ve provided forecast values further into the future, you should keep that in mind.

The upper and lower bounds shown are 95% confidence intervals — again, you can recap on what that means in my previous post if you so wish.

Advanced use cases

You may by now have noticed the “Advanced” tab:

Although I said I wanted to keep this simple, I felt that given everything that happened in 2020, many people would need to incorporate major external factors into their model.

In the example above, I’ve filled in column B with a variable for whether or not the UK was under COVID lockdown. I’ve used “0.5” to represent that we entered lockdown halfway through March.

You can probably make a better go of this for the relevant factors for your business, but there are a few important things to keep in mind with this tab:

It’s fine to leave it completely untouched if you don’t want to add these extra variables.

Go from left to right — it’s fine to leave column C blank if you’re using column B, but it’s not fine to leave B blank if you’re using C.

If you’re using a “dummy” variable (e.g. “1” for something being active), you need to make sure you fill in the 0s in other cells for at least the period of your historic data.

You can enter future values — for example, if you predict a COVID lockdown in March 2021 (you bastard!), you can enter something in that cell so it’s incorporated into the forecast.

If you don’t enter future values, the model will predict based on this number being zero in the future. So if you’ve entered “branded PPC active” as a dummy variable for historic data, and then left it blank for future periods, the model will assume you have branded PPC turned off in the future.

Adding too much data here for too few historic periods will result in something called “overfit” — I don’t want to get into detail on this, which is why this tab is called “Advanced”, but try not to get carried away.

Here’s some example use cases of this tab for you to consider:

Enter whether branded PPC was active (0 or 1)

Enter whether you’re running TV ads or not

Enter COVID lockdowns

Enter algorithm updates that were significant to your business (one column per update)

Why are my estimates different to your old tool? Is one of them wrong?

There’s two major differences in method between this template and my old tool:

The old tool used Google’s Causal Impact library, the new template uses an Ordinary Least Squares regression.

The old tool captured non-linear trends by using time period squared as a predictive variable (e.g. month 1 = 1, month 2 = 4, month 3 = 9, etc.) and trying to fit the traffic curve to that curve. This is called a quadratic regression. The new tool captures non-linear trends by fitting each time period as a multiple of the previous time period (e.g. month 1 = X * month 2 where X can be any value). This is called an AR(1) model.

If you’re seeing a significant difference in the forecast values between the two, it almost certainly comes down to the second reason, and although it adds a little complexity, in the vast majority of cases the new technique is more realistic and flexible.

It’s also far less likely to predict zero or negative traffic in the case of a severe downwards trend, which is nice.

How does it work?

There’s a hidden tab in the template where you can take a peek, but the short version is the “LINEST()” spreadsheet formula.

The inputs I’m using are:

Dependent variables

Whatever you put as column B in the inputs tab (like traffic)

Independent variables

Linear passing of time

Previous period’s traffic

Dummy variables for 11 months (12th month is represented by the other 11 variables all being 0)

Up to three “advanced” variables

The formula then gives a series of “coefficients” as outputs, which can be multiplied with values and added together to form a prediction like:

“Time period 10” traffic = Intercept + (Time Coefficient * 10) + (Previous Period Coefficient * Period 9 traffic)

You can see in that hidden sheet I’ve labelled and color-coded a lot of the outputs from the Linest formula, which may help you to get started if you want to play around with it yourself.

Potential extensions

If you do want to play around with this yourself, here are some areas I personally have in mind for further expansion that you might find interesting:

Daily data instead of monthly, with weekly seasonality (e.g. dip every Sunday)

Built-in growth targets (e.g. enter 20% growth by end of 2021)

Richard Fergie, whose Forecast Forge tool I mentioned a couple of times above, also provided some great suggestions for improving forecast accuracy with fairly limited extra complexity:

Smooth data and avoid negative predictions in extreme cases by taking the log() of inputs, and providing an exponent of outputs (smoothing data may or may not be a good thing depending on your perspective!).

Regress on the previous 12 months, instead of using the previous 1 month + seasonality (this requires 3 years’ minimum historical data)

I may or may not include some or all of the above myself over time, but if so I’ll make sure I use the same link and make a note of it in the spreadsheet, so this article always links to the most up-to-date version.

If you’ve made it this far, what would you like to see? Let me know in the comments!

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[epackingvietnam]

SEO Forecasting in Google Sheets

Posted by Tom.Capper

Way back in 2015, I published an article giving away a free, simple, forecasting tool, and talking through use cases for forecasting in SEO. It was a quick, effective way to see if a change to your site traffic is some kind of seasonality you can ignore, something to celebrate, or a worrying sign of traffic loss.

In short: you could enter in a series of data, and it would plot it out on a graph like the image above.

Five years later, I still get people — from former colleagues to complete strangers — asking me about this tool, and more often than not, I’m asked for a version that works directly in spreadsheets.

I find this easy to sympathize with: a spreadsheet is more flexible, easier to debug, easier to expand upon, easier to maintain, and a format that people are very familiar with.

The tradeoff when optimizing for those things is, although I’ve improved on that tool from a few years ago, I’ve still had to keep things manageable in the famously fickle programming environment that is Excel/Google Sheets. That means the template shared in this post uses a simpler, slightly less performant model than some tools with external code execution (e.g. Forecast Forge).

In this post, I’m going to give away a free template, show you how it works and how to use it, and then show you how to build your own (better?) version. (If you need a refresher on when to use forecasting in general, and concepts like confidence intervals, refer to the original article linked above.).

Types of SEO forecast

There is one thing I want to expand on before we get into the spreadsheet stuff: the different types of SEO forecast.

Broadly, I think you can put SEO forecasts into three groups:

“I’m feeling optimistic — add 20% to this year” or similar flat changes to existing figures. More complex versions might only add 20% to certain groups of pages or keywords. I think a lot of agencies use this kind of forecast in pitches, and it comes down to drawing on experience.

Keyword/CTR models, when you estimate a ranking change (or sweeping set of ranking changes), then extrapolate the resulting change in traffic from search volume and CTR data (you can see a similar methodology here). Again, more complex versions might have some basis for the ranking change (e.g. “What if we swapped places with competitor A in every keyword of group X where they currently outrank us?”).

Statistical forecast based on historical data, when you extrapolate from previous trends and seasonality to see what would happen if everything remained constant (same level of marketing activity by you and competitors, etc.).

Type two has its merits, but if you compare the likes of Ahrefs/SEMRush/Sistrix data to your own analytics, you’ll see how hard this is to generalize. As an aside, I don’t think type one is as ridiculous as it looks, but it’s not something I’ll be exploring any further in this post. In any case, the template in this post fits into type three.

What makes this an SEO forecast?

Why, nothing at all. One thing you’ll notice about my description of type three above is that it doesn’t mention anything SEO-specific. It could equally apply to direct traffic, for example. That said, there are a couple of reasons I’m suggesting this specifically as an SEO forecast:

We’re on the Moz Blog and I’m an SEO consultant.

There are better methodologies available for a lot of other channels.

I mentioned that type two above is very challenging, and this is because of the highly non-deterministic nature of SEO and the generally poor quality of detailed data in Search Console and other SEO-specific platforms. In addition, to get an accurate idea of seasonality, you’d need to have been warehousing your Search Console data for at least a couple of years.

For many other channels, high quality, detailed historic data does exist, and relationships are far more predictable, allowing more granular forecasts. For example, for paid search, the Forecast Forge tool I mentioned above builds in factors like keyword-level conversion data and cost-per-click based on your historical data, in a way that would be wildly impractical for SEO.

That said, we can still combine multiple types of forecast in the template below. For example, rather than forecasting the traffic of your site as a whole, you might forecast subfolders separately, or brand/non-brand separately, and you might then apply percentage growth to certain areas or build in anticipated ranking changes. But, we’re getting ahead of ourselves…

How to use the template

FREE TEMPLATE

The first thing you’ll need to do is make a copy (under the “File” menu in the top left, but automatic with the link I’ve included). This means you can enter your own data and play around to your heart’s content, and you can always come back and get a fresh copy later if you need one.

Then, on the first tab, you’ll notice some cells have a green or blue highlight:

You should only be changing values in the colored cells.

The blue cells in column E are basically to make sure everything ends up correctly labelled in the output. So, for example, if you’re pasting session data, or click data, or revenue data, you can set that label. Similarly, if you enter a start month of 2018-01 and 36 months of historic data, the forecast output will begin in January 2021.

On that note, it needs to be monthly data — that’s one of the tradeoffs for simplicity I mentioned earlier. You can paste up to a decade of historic monthly data into column B, starting at cell B2, but there are a couple of things you need to be careful of:

You need at least 24 months of data for the model to have a good idea of seasonality. (If there’s only one January in your historic data, and it was a traffic spike, how am I supposed to know if it was a one-off thing, or an annual thing?)

You need complete months. So if it’s March 25, 2021 when you’re reading this, the last month of data you should include is February 2021.

Make sure you also delete any leftovers of my example data in column B.

Outputs

Once you’ve done that, you can head over to the “Outputs” tab, where you’ll see something like this:

Column C is probably the one you’re interested in. Keep in mind that it’s full of formulas here, but you can copy and paste as values into another sheet, or just go to File > Download > Comma-separated values to get the raw data.

You’ll notice I’m only showing 15 months of forecast in that graph by default, and I’d recommend you do the same. As I mentioned above, the implicit assumption of a forecast is that historical context carries over, unless you explicitly include changed scenarios like COVID lockdowns into your model (more on that in a moment!). The chance of this assumption holding two or three years into the future is low, so even though I’ve provided forecast values further into the future, you should keep that in mind.

The upper and lower bounds shown are 95% confidence intervals — again, you can recap on what that means in my previous post if you so wish.

Advanced use cases

You may by now have noticed the “Advanced” tab:

Although I said I wanted to keep this simple, I felt that given everything that happened in 2020, many people would need to incorporate major external factors into their model.

In the example above, I’ve filled in column B with a variable for whether or not the UK was under COVID lockdown. I’ve used “0.5” to represent that we entered lockdown halfway through March.

You can probably make a better go of this for the relevant factors for your business, but there are a few important things to keep in mind with this tab:

It’s fine to leave it completely untouched if you don’t want to add these extra variables.

Go from left to right — it’s fine to leave column C blank if you’re using column B, but it’s not fine to leave B blank if you’re using C.

If you’re using a “dummy” variable (e.g. “1” for something being active), you need to make sure you fill in the 0s in other cells for at least the period of your historic data.

You can enter future values — for example, if you predict a COVID lockdown in March 2021 (you bastard!), you can enter something in that cell so it’s incorporated into the forecast.

If you don’t enter future values, the model will predict based on this number being zero in the future. So if you’ve entered “branded PPC active” as a dummy variable for historic data, and then left it blank for future periods, the model will assume you have branded PPC turned off in the future.

Adding too much data here for too few historic periods will result in something called “overfit” — I don’t want to get into detail on this, which is why this tab is called “Advanced”, but try not to get carried away.

Here’s some example use cases of this tab for you to consider:

Enter whether branded PPC was active (0 or 1)

Enter whether you’re running TV ads or not

Enter COVID lockdowns

Enter algorithm updates that were significant to your business (one column per update)

Why are my estimates different to your old tool? Is one of them wrong?

There’s two major differences in method between this template and my old tool:

The old tool used Google’s Causal Impact library, the new template uses an Ordinary Least Squares regression.

The old tool captured non-linear trends by using time period squared as a predictive variable (e.g. month 1 = 1, month 2 = 4, month 3 = 9, etc.) and trying to fit the traffic curve to that curve. This is called a quadratic regression. The new tool captures non-linear trends by fitting each time period as a multiple of the previous time period (e.g. month 1 = X * month 2 where X can be any value). This is called an AR(1) model.

If you’re seeing a significant difference in the forecast values between the two, it almost certainly comes down to the second reason, and although it adds a little complexity, in the vast majority of cases the new technique is more realistic and flexible.

It’s also far less likely to predict zero or negative traffic in the case of a severe downwards trend, which is nice.

How does it work?

There’s a hidden tab in the template where you can take a peek, but the short version is the “LINEST()” spreadsheet formula.

The inputs I’m using are:

Dependent variables

Whatever you put as column B in the inputs tab (like traffic)

Independent variables

Linear passing of time

Previous period’s traffic

Dummy variables for 11 months (12th month is represented by the other 11 variables all being 0)

Up to three “advanced” variables

The formula then gives a series of “coefficients” as outputs, which can be multiplied with values and added together to form a prediction like:

“Time period 10” traffic = Intercept + (Time Coefficient * 10) + (Previous Period Coefficient * Period 9 traffic)

You can see in that hidden sheet I’ve labelled and color-coded a lot of the outputs from the Linest formula, which may help you to get started if you want to play around with it yourself.

Potential extensions

If you do want to play around with this yourself, here are some areas I personally have in mind for further expansion that you might find interesting:

Daily data instead of monthly, with weekly seasonality (e.g. dip every Sunday)

Built-in growth targets (e.g. enter 20% growth by end of 2021)

Richard Fergie, whose Forecast Forge tool I mentioned a couple of times above, also provided some great suggestions for improving forecast accuracy with fairly limited extra complexity:

Smooth data and avoid negative predictions in extreme cases by taking the log() of inputs, and providing an exponent of outputs (smoothing data may or may not be a good thing depending on your perspective!).

Regress on the previous 12 months, instead of using the previous 1 month + seasonality (this requires 3 years’ minimum historical data)

I may or may not include some or all of the above myself over time, but if so I’ll make sure I use the same link and make a note of it in the spreadsheet, so this article always links to the most up-to-date version.

If you’ve made it this far, what would you like to see? Let me know in the comments!

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

#túi_giấy_epacking_việt_nam #túi_giấy_epacking #in_túi_giấy_giá_rẻ #in_túi_giấy #epackingvietnam #tuigiayepacking

[bfxenon]

SEO Forecasting in Google Sheets

Posted by Tom.Capper

Way back in 2015, I published an article giving away a free, simple, forecasting tool, and talking through use cases for forecasting in SEO. It was a quick, effective way to see if a change to your site traffic is some kind of seasonality you can ignore, something to celebrate, or a worrying sign of traffic loss.

In short: you could enter in a series of data, and it would plot it out on a graph like the image above.

Five years later, I still get people — from former colleagues to complete strangers — asking me about this tool, and more often than not, I’m asked for a version that works directly in spreadsheets.

I find this easy to sympathize with: a spreadsheet is more flexible, easier to debug, easier to expand upon, easier to maintain, and a format that people are very familiar with.

The tradeoff when optimizing for those things is, although I’ve improved on that tool from a few years ago, I’ve still had to keep things manageable in the famously fickle programming environment that is Excel/Google Sheets. That means the template shared in this post uses a simpler, slightly less performant model than some tools with external code execution (e.g. Forecast Forge).

In this post, I’m going to give away a free template, show you how it works and how to use it, and then show you how to build your own (better?) version. (If you need a refresher on when to use forecasting in general, and concepts like confidence intervals, refer to the original article linked above.).

Types of SEO forecast

There is one thing I want to expand on before we get into the spreadsheet stuff: the different types of SEO forecast.

Broadly, I think you can put SEO forecasts into three groups:

“I’m feeling optimistic — add 20% to this year” or similar flat changes to existing figures. More complex versions might only add 20% to certain groups of pages or keywords. I think a lot of agencies use this kind of forecast in pitches, and it comes down to drawing on experience.

Keyword/CTR models, when you estimate a ranking change (or sweeping set of ranking changes), then extrapolate the resulting change in traffic from search volume and CTR data (you can see a similar methodology here). Again, more complex versions might have some basis for the ranking change (e.g. “What if we swapped places with competitor A in every keyword of group X where they currently outrank us?”).

Statistical forecast based on historical data, when you extrapolate from previous trends and seasonality to see what would happen if everything remained constant (same level of marketing activity by you and competitors, etc.).

Type two has its merits, but if you compare the likes of Ahrefs/SEMRush/Sistrix data to your own analytics, you’ll see how hard this is to generalize. As an aside, I don’t think type one is as ridiculous as it looks, but it’s not something I’ll be exploring any further in this post. In any case, the template in this post fits into type three.

What makes this an SEO forecast?

Why, nothing at all. One thing you’ll notice about my description of type three above is that it doesn’t mention anything SEO-specific. It could equally apply to direct traffic, for example. That said, there are a couple of reasons I’m suggesting this specifically as an SEO forecast:

We’re on the Moz Blog and I’m an SEO consultant.

There are better methodologies available for a lot of other channels.

I mentioned that type two above is very challenging, and this is because of the highly non-deterministic nature of SEO and the generally poor quality of detailed data in Search Console and other SEO-specific platforms. In addition, to get an accurate idea of seasonality, you’d need to have been warehousing your Search Console data for at least a couple of years.

For many other channels, high quality, detailed historic data does exist, and relationships are far more predictable, allowing more granular forecasts. For example, for paid search, the Forecast Forge tool I mentioned above builds in factors like keyword-level conversion data and cost-per-click based on your historical data, in a way that would be wildly impractical for SEO.

That said, we can still combine multiple types of forecast in the template below. For example, rather than forecasting the traffic of your site as a whole, you might forecast subfolders separately, or brand/non-brand separately, and you might then apply percentage growth to certain areas or build in anticipated ranking changes. But, we’re getting ahead of ourselves…

How to use the template

FREE TEMPLATE

The first thing you’ll need to do is make a copy (under the “File” menu in the top left, but automatic with the link I’ve included). This means you can enter your own data and play around to your heart’s content, and you can always come back and get a fresh copy later if you need one.

Then, on the first tab, you’ll notice some cells have a green or blue highlight:

You should only be changing values in the colored cells.

The blue cells in column E are basically to make sure everything ends up correctly labelled in the output. So, for example, if you’re pasting session data, or click data, or revenue data, you can set that label. Similarly, if you enter a start month of 2018-01 and 36 months of historic data, the forecast output will begin in January 2021.

On that note, it needs to be monthly data — that’s one of the tradeoffs for simplicity I mentioned earlier. You can paste up to a decade of historic monthly data into column B, starting at cell B2, but there are a couple of things you need to be careful of:

You need at least 24 months of data for the model to have a good idea of seasonality. (If there’s only one January in your historic data, and it was a traffic spike, how am I supposed to know if it was a one-off thing, or an annual thing?)

You need complete months. So if it’s March 25, 2021 when you’re reading this, the last month of data you should include is February 2021.

Make sure you also delete any leftovers of my example data in column B.

Outputs

Once you’ve done that, you can head over to the “Outputs” tab, where you’ll see something like this:

Column C is probably the one you’re interested in. Keep in mind that it’s full of formulas here, but you can copy and paste as values into another sheet, or just go to File > Download > Comma-separated values to get the raw data.

You’ll notice I’m only showing 15 months of forecast in that graph by default, and I’d recommend you do the same. As I mentioned above, the implicit assumption of a forecast is that historical context carries over, unless you explicitly include changed scenarios like COVID lockdowns into your model (more on that in a moment!). The chance of this assumption holding two or three years into the future is low, so even though I’ve provided forecast values further into the future, you should keep that in mind.

The upper and lower bounds shown are 95% confidence intervals — again, you can recap on what that means in my previous post if you so wish.

Advanced use cases

You may by now have noticed the “Advanced” tab:

Although I said I wanted to keep this simple, I felt that given everything that happened in 2020, many people would need to incorporate major external factors into their model.

In the example above, I’ve filled in column B with a variable for whether or not the UK was under COVID lockdown. I’ve used “0.5” to represent that we entered lockdown halfway through March.

You can probably make a better go of this for the relevant factors for your business, but there are a few important things to keep in mind with this tab:

It’s fine to leave it completely untouched if you don’t want to add these extra variables.

Go from left to right — it’s fine to leave column C blank if you’re using column B, but it’s not fine to leave B blank if you’re using C.

If you’re using a “dummy” variable (e.g. “1” for something being active), you need to make sure you fill in the 0s in other cells for at least the period of your historic data.

You can enter future values — for example, if you predict a COVID lockdown in March 2021 (you bastard!), you can enter something in that cell so it’s incorporated into the forecast.

If you don’t enter future values, the model will predict based on this number being zero in the future. So if you’ve entered “branded PPC active” as a dummy variable for historic data, and then left it blank for future periods, the model will assume you have branded PPC turned off in the future.

Adding too much data here for too few historic periods will result in something called “overfit” — I don’t want to get into detail on this, which is why this tab is called “Advanced”, but try not to get carried away.

Here’s some example use cases of this tab for you to consider:

Enter whether branded PPC was active (0 or 1)

Enter whether you’re running TV ads or not

Enter COVID lockdowns

Enter algorithm updates that were significant to your business (one column per update)

Why are my estimates different to your old tool? Is one of them wrong?

There’s two major differences in method between this template and my old tool:

The old tool used Google’s Causal Impact library, the new template uses an Ordinary Least Squares regression.

The old tool captured non-linear trends by using time period squared as a predictive variable (e.g. month 1 = 1, month 2 = 4, month 3 = 9, etc.) and trying to fit the traffic curve to that curve. This is called a quadratic regression. The new tool captures non-linear trends by fitting each time period as a multiple of the previous time period (e.g. month 1 = X * month 2 where X can be any value). This is called an AR(1) model.

If you’re seeing a significant difference in the forecast values between the two, it almost certainly comes down to the second reason, and although it adds a little complexity, in the vast majority of cases the new technique is more realistic and flexible.

It’s also far less likely to predict zero or negative traffic in the case of a severe downwards trend, which is nice.

How does it work?

There’s a hidden tab in the template where you can take a peek, but the short version is the “LINEST()” spreadsheet formula.

The inputs I’m using are:

Dependent variables

Whatever you put as column B in the inputs tab (like traffic)

Independent variables

Linear passing of time

Previous period’s traffic

Dummy variables for 11 months (12th month is represented by the other 11 variables all being 0)

Up to three “advanced” variables

The formula then gives a series of “coefficients” as outputs, which can be multiplied with values and added together to form a prediction like:

“Time period 10” traffic = Intercept + (Time Coefficient * 10) + (Previous Period Coefficient * Period 9 traffic)

You can see in that hidden sheet I’ve labelled and color-coded a lot of the outputs from the Linest formula, which may help you to get started if you want to play around with it yourself.

Potential extensions

If you do want to play around with this yourself, here are some areas I personally have in mind for further expansion that you might find interesting:

Daily data instead of monthly, with weekly seasonality (e.g. dip every Sunday)

Built-in growth targets (e.g. enter 20% growth by end of 2021)

Richard Fergie, whose Forecast Forge tool I mentioned a couple of times above, also provided some great suggestions for improving forecast accuracy with fairly limited extra complexity:

Smooth data and avoid negative predictions in extreme cases by taking the log() of inputs, and providing an exponent of outputs (smoothing data may or may not be a good thing depending on your perspective!).

Regress on the previous 12 months, instead of using the previous 1 month + seasonality (this requires 3 years’ minimum historical data)

I may or may not include some or all of the above myself over time, but if so I’ll make sure I use the same link and make a note of it in the spreadsheet, so this article always links to the most up-to-date version.

If you’ve made it this far, what would you like to see? Let me know in the comments!

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[nutrifami]

SEO Forecasting in Google Sheets

Posted by Tom.Capper

Way back in 2015, I published an article giving away a free, simple, forecasting tool, and talking through use cases for forecasting in SEO. It was a quick, effective way to see if a change to your site traffic is some kind of seasonality you can ignore, something to celebrate, or a worrying sign of traffic loss.

In short: you could enter in a series of data, and it would plot it out on a graph like the image above.

Five years later, I still get people — from former colleagues to complete strangers — asking me about this tool, and more often than not, I’m asked for a version that works directly in spreadsheets.

I find this easy to sympathize with: a spreadsheet is more flexible, easier to debug, easier to expand upon, easier to maintain, and a format that people are very familiar with.

The tradeoff when optimizing for those things is, although I’ve improved on that tool from a few years ago, I’ve still had to keep things manageable in the famously fickle programming environment that is Excel/Google Sheets. That means the template shared in this post uses a simpler, slightly less performant model than some tools with external code execution (e.g. Forecast Forge).

In this post, I’m going to give away a free template, show you how it works and how to use it, and then show you how to build your own (better?) version. (If you need a refresher on when to use forecasting in general, and concepts like confidence intervals, refer to the original article linked above.).

Types of SEO forecast

There is one thing I want to expand on before we get into the spreadsheet stuff: the different types of SEO forecast.

Broadly, I think you can put SEO forecasts into three groups:

“I’m feeling optimistic — add 20% to this year” or similar flat changes to existing figures. More complex versions might only add 20% to certain groups of pages or keywords. I think a lot of agencies use this kind of forecast in pitches, and it comes down to drawing on experience.

Keyword/CTR models, when you estimate a ranking change (or sweeping set of ranking changes), then extrapolate the resulting change in traffic from search volume and CTR data (you can see a similar methodology here). Again, more complex versions might have some basis for the ranking change (e.g. “What if we swapped places with competitor A in every keyword of group X where they currently outrank us?”).

Statistical forecast based on historical data, when you extrapolate from previous trends and seasonality to see what would happen if everything remained constant (same level of marketing activity by you and competitors, etc.).

Type two has its merits, but if you compare the likes of Ahrefs/SEMRush/Sistrix data to your own analytics, you’ll see how hard this is to generalize. As an aside, I don’t think type one is as ridiculous as it looks, but it’s not something I’ll be exploring any further in this post. In any case, the template in this post fits into type three.

What makes this an SEO forecast?

Why, nothing at all. One thing you’ll notice about my description of type three above is that it doesn’t mention anything SEO-specific. It could equally apply to direct traffic, for example. That said, there are a couple of reasons I’m suggesting this specifically as an SEO forecast:

We’re on the Moz Blog and I’m an SEO consultant.

There are better methodologies available for a lot of other channels.

I mentioned that type two above is very challenging, and this is because of the highly non-deterministic nature of SEO and the generally poor quality of detailed data in Search Console and other SEO-specific platforms. In addition, to get an accurate idea of seasonality, you’d need to have been warehousing your Search Console data for at least a couple of years.

For many other channels, high quality, detailed historic data does exist, and relationships are far more predictable, allowing more granular forecasts. For example, for paid search, the Forecast Forge tool I mentioned above builds in factors like keyword-level conversion data and cost-per-click based on your historical data, in a way that would be wildly impractical for SEO.

That said, we can still combine multiple types of forecast in the template below. For example, rather than forecasting the traffic of your site as a whole, you might forecast subfolders separately, or brand/non-brand separately, and you might then apply percentage growth to certain areas or build in anticipated ranking changes. But, we’re getting ahead of ourselves…

How to use the template

FREE TEMPLATE

The first thing you’ll need to do is make a copy (under the “File” menu in the top left, but automatic with the link I’ve included). This means you can enter your own data and play around to your heart’s content, and you can always come back and get a fresh copy later if you need one.

Then, on the first tab, you’ll notice some cells have a green or blue highlight:

You should only be changing values in the colored cells.

The blue cells in column E are basically to make sure everything ends up correctly labelled in the output. So, for example, if you’re pasting session data, or click data, or revenue data, you can set that label. Similarly, if you enter a start month of 2018-01 and 36 months of historic data, the forecast output will begin in January 2021.

On that note, it needs to be monthly data — that’s one of the tradeoffs for simplicity I mentioned earlier. You can paste up to a decade of historic monthly data into column B, starting at cell B2, but there are a couple of things you need to be careful of:

You need at least 24 months of data for the model to have a good idea of seasonality. (If there’s only one January in your historic data, and it was a traffic spike, how am I supposed to know if it was a one-off thing, or an annual thing?)

You need complete months. So if it’s March 25, 2021 when you’re reading this, the last month of data you should include is February 2021.

Make sure you also delete any leftovers of my example data in column B.

Outputs

Once you’ve done that, you can head over to the “Outputs” tab, where you’ll see something like this:

Column C is probably the one you’re interested in. Keep in mind that it’s full of formulas here, but you can copy and paste as values into another sheet, or just go to File > Download > Comma-separated values to get the raw data.

You’ll notice I’m only showing 15 months of forecast in that graph by default, and I’d recommend you do the same. As I mentioned above, the implicit assumption of a forecast is that historical context carries over, unless you explicitly include changed scenarios like COVID lockdowns into your model (more on that in a moment!). The chance of this assumption holding two or three years into the future is low, so even though I’ve provided forecast values further into the future, you should keep that in mind.

The upper and lower bounds shown are 95% confidence intervals — again, you can recap on what that means in my previous post if you so wish.

Advanced use cases

You may by now have noticed the “Advanced” tab:

Although I said I wanted to keep this simple, I felt that given everything that happened in 2020, many people would need to incorporate major external factors into their model.

In the example above, I’ve filled in column B with a variable for whether or not the UK was under COVID lockdown. I’ve used “0.5” to represent that we entered lockdown halfway through March.

You can probably make a better go of this for the relevant factors for your business, but there are a few important things to keep in mind with this tab:

It’s fine to leave it completely untouched if you don’t want to add these extra variables.

Go from left to right — it’s fine to leave column C blank if you’re using column B, but it’s not fine to leave B blank if you’re using C.

If you’re using a “dummy” variable (e.g. “1” for something being active), you need to make sure you fill in the 0s in other cells for at least the period of your historic data.

You can enter future values — for example, if you predict a COVID lockdown in March 2021 (you bastard!), you can enter something in that cell so it’s incorporated into the forecast.

If you don’t enter future values, the model will predict based on this number being zero in the future. So if you’ve entered “branded PPC active” as a dummy variable for historic data, and then left it blank for future periods, the model will assume you have branded PPC turned off in the future.

Adding too much data here for too few historic periods will result in something called “overfit” — I don’t want to get into detail on this, which is why this tab is called “Advanced”, but try not to get carried away.

Here’s some example use cases of this tab for you to consider:

Enter whether branded PPC was active (0 or 1)

Enter whether you’re running TV ads or not

Enter COVID lockdowns

Enter algorithm updates that were significant to your business (one column per update)

Why are my estimates different to your old tool? Is one of them wrong?

There’s two major differences in method between this template and my old tool:

The old tool used Google’s Causal Impact library, the new template uses an Ordinary Least Squares regression.

The old tool captured non-linear trends by using time period squared as a predictive variable (e.g. month 1 = 1, month 2 = 4, month 3 = 9, etc.) and trying to fit the traffic curve to that curve. This is called a quadratic regression. The new tool captures non-linear trends by fitting each time period as a multiple of the previous time period (e.g. month 1 = X * month 2 where X can be any value). This is called an AR(1) model.

If you’re seeing a significant difference in the forecast values between the two, it almost certainly comes down to the second reason, and although it adds a little complexity, in the vast majority of cases the new technique is more realistic and flexible.

It’s also far less likely to predict zero or negative traffic in the case of a severe downwards trend, which is nice.

How does it work?

There’s a hidden tab in the template where you can take a peek, but the short version is the “LINEST()” spreadsheet formula.

The inputs I’m using are:

Dependent variables

Whatever you put as column B in the inputs tab (like traffic)

Independent variables

Linear passing of time

Previous period’s traffic

Dummy variables for 11 months (12th month is represented by the other 11 variables all being 0)

Up to three “advanced” variables

The formula then gives a series of “coefficients” as outputs, which can be multiplied with values and added together to form a prediction like:

“Time period 10” traffic = Intercept + (Time Coefficient * 10) + (Previous Period Coefficient * Period 9 traffic)

You can see in that hidden sheet I’ve labelled and color-coded a lot of the outputs from the Linest formula, which may help you to get started if you want to play around with it yourself.

Potential extensions

If you do want to play around with this yourself, here are some areas I personally have in mind for further expansion that you might find interesting:

Daily data instead of monthly, with weekly seasonality (e.g. dip every Sunday)

Built-in growth targets (e.g. enter 20% growth by end of 2021)

Richard Fergie, whose Forecast Forge tool I mentioned a couple of times above, also provided some great suggestions for improving forecast accuracy with fairly limited extra complexity:

Smooth data and avoid negative predictions in extreme cases by taking the log() of inputs, and providing an exponent of outputs (smoothing data may or may not be a good thing depending on your perspective!).

Regress on the previous 12 months, instead of using the previous 1 month + seasonality (this requires 3 years’ minimum historical data)

I may or may not include some or all of the above myself over time, but if so I’ll make sure I use the same link and make a note of it in the spreadsheet, so this article always links to the most up-to-date version.

If you’ve made it this far, what would you like to see? Let me know in the comments!

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

[xaydungtruonggia]

SEO Forecasting in Google Sheets

Posted by Tom.Capper

Way back in 2015, I published an article giving away a free, simple, forecasting tool, and talking through use cases for forecasting in SEO. It was a quick, effective way to see if a change to your site traffic is some kind of seasonality you can ignore, something to celebrate, or a worrying sign of traffic loss.

In short: you could enter in a series of data, and it would plot it out on a graph like the image above.

Five years later, I still get people — from former colleagues to complete strangers — asking me about this tool, and more often than not, I’m asked for a version that works directly in spreadsheets.

I find this easy to sympathize with: a spreadsheet is more flexible, easier to debug, easier to expand upon, easier to maintain, and a format that people are very familiar with.

The tradeoff when optimizing for those things is, although I’ve improved on that tool from a few years ago, I’ve still had to keep things manageable in the famously fickle programming environment that is Excel/Google Sheets. That means the template shared in this post uses a simpler, slightly less performant model than some tools with external code execution (e.g. Forecast Forge).

In this post, I’m going to give away a free template, show you how it works and how to use it, and then show you how to build your own (better?) version. (If you need a refresher on when to use forecasting in general, and concepts like confidence intervals, refer to the original article linked above.).

Types of SEO forecast

There is one thing I want to expand on before we get into the spreadsheet stuff: the different types of SEO forecast.

Broadly, I think you can put SEO forecasts into three groups:

“I’m feeling optimistic — add 20% to this year” or similar flat changes to existing figures. More complex versions might only add 20% to certain groups of pages or keywords. I think a lot of agencies use this kind of forecast in pitches, and it comes down to drawing on experience.

Keyword/CTR models, when you estimate a ranking change (or sweeping set of ranking changes), then extrapolate the resulting change in traffic from search volume and CTR data (you can see a similar methodology here). Again, more complex versions might have some basis for the ranking change (e.g. “What if we swapped places with competitor A in every keyword of group X where they currently outrank us?”).

Statistical forecast based on historical data, when you extrapolate from previous trends and seasonality to see what would happen if everything remained constant (same level of marketing activity by you and competitors, etc.).

Type two has its merits, but if you compare the likes of Ahrefs/SEMRush/Sistrix data to your own analytics, you’ll see how hard this is to generalize. As an aside, I don’t think type one is as ridiculous as it looks, but it’s not something I’ll be exploring any further in this post. In any case, the template in this post fits into type three.

What makes this an SEO forecast?

Why, nothing at all. One thing you’ll notice about my description of type three above is that it doesn’t mention anything SEO-specific. It could equally apply to direct traffic, for example. That said, there are a couple of reasons I’m suggesting this specifically as an SEO forecast:

We’re on the Moz Blog and I’m an SEO consultant.

There are better methodologies available for a lot of other channels.

I mentioned that type two above is very challenging, and this is because of the highly non-deterministic nature of SEO and the generally poor quality of detailed data in Search Console and other SEO-specific platforms. In addition, to get an accurate idea of seasonality, you’d need to have been warehousing your Search Console data for at least a couple of years.

For many other channels, high quality, detailed historic data does exist, and relationships are far more predictable, allowing more granular forecasts. For example, for paid search, the Forecast Forge tool I mentioned above builds in factors like keyword-level conversion data and cost-per-click based on your historical data, in a way that would be wildly impractical for SEO.

That said, we can still combine multiple types of forecast in the template below. For example, rather than forecasting the traffic of your site as a whole, you might forecast subfolders separately, or brand/non-brand separately, and you might then apply percentage growth to certain areas or build in anticipated ranking changes. But, we’re getting ahead of ourselves…

How to use the template

FREE TEMPLATE

The first thing you’ll need to do is make a copy (under the “File” menu in the top left, but automatic with the link I’ve included). This means you can enter your own data and play around to your heart’s content, and you can always come back and get a fresh copy later if you need one.

Then, on the first tab, you’ll notice some cells have a green or blue highlight:

You should only be changing values in the colored cells.

The blue cells in column E are basically to make sure everything ends up correctly labelled in the output. So, for example, if you’re pasting session data, or click data, or revenue data, you can set that label. Similarly, if you enter a start month of 2018-01 and 36 months of historic data, the forecast output will begin in January 2021.

On that note, it needs to be monthly data — that’s one of the tradeoffs for simplicity I mentioned earlier. You can paste up to a decade of historic monthly data into column B, starting at cell B2, but there are a couple of things you need to be careful of:

You need at least 24 months of data for the model to have a good idea of seasonality. (If there’s only one January in your historic data, and it was a traffic spike, how am I supposed to know if it was a one-off thing, or an annual thing?)

You need complete months. So if it’s March 25, 2021 when you’re reading this, the last month of data you should include is February 2021.

Make sure you also delete any leftovers of my example data in column B.

Outputs

Once you’ve done that, you can head over to the “Outputs” tab, where you’ll see something like this:

Column C is probably the one you’re interested in. Keep in mind that it’s full of formulas here, but you can copy and paste as values into another sheet, or just go to File > Download > Comma-separated values to get the raw data.

You’ll notice I’m only showing 15 months of forecast in that graph by default, and I’d recommend you do the same. As I mentioned above, the implicit assumption of a forecast is that historical context carries over, unless you explicitly include changed scenarios like COVID lockdowns into your model (more on that in a moment!). The chance of this assumption holding two or three years into the future is low, so even though I’ve provided forecast values further into the future, you should keep that in mind.

The upper and lower bounds shown are 95% confidence intervals — again, you can recap on what that means in my previous post if you so wish.

Advanced use cases

You may by now have noticed the “Advanced” tab:

Although I said I wanted to keep this simple, I felt that given everything that happened in 2020, many people would need to incorporate major external factors into their model.

In the example above, I’ve filled in column B with a variable for whether or not the UK was under COVID lockdown. I’ve used “0.5” to represent that we entered lockdown halfway through March.

You can probably make a better go of this for the relevant factors for your business, but there are a few important things to keep in mind with this tab:

It’s fine to leave it completely untouched if you don’t want to add these extra variables.

Go from left to right — it’s fine to leave column C blank if you’re using column B, but it’s not fine to leave B blank if you’re using C.

If you’re using a “dummy” variable (e.g. “1” for something being active), you need to make sure you fill in the 0s in other cells for at least the period of your historic data.

You can enter future values — for example, if you predict a COVID lockdown in March 2021 (you bastard!), you can enter something in that cell so it’s incorporated into the forecast.

If you don’t enter future values, the model will predict based on this number being zero in the future. So if you’ve entered “branded PPC active” as a dummy variable for historic data, and then left it blank for future periods, the model will assume you have branded PPC turned off in the future.

Adding too much data here for too few historic periods will result in something called “overfit” — I don’t want to get into detail on this, which is why this tab is called “Advanced”, but try not to get carried away.

Here’s some example use cases of this tab for you to consider:

Enter whether branded PPC was active (0 or 1)

Enter whether you’re running TV ads or not

Enter COVID lockdowns

Enter algorithm updates that were significant to your business (one column per update)

Why are my estimates different to your old tool? Is one of them wrong?

There’s two major differences in method between this template and my old tool:

The old tool used Google’s Causal Impact library, the new template uses an Ordinary Least Squares regression.

The old tool captured non-linear trends by using time period squared as a predictive variable (e.g. month 1 = 1, month 2 = 4, month 3 = 9, etc.) and trying to fit the traffic curve to that curve. This is called a quadratic regression. The new tool captures non-linear trends by fitting each time period as a multiple of the previous time period (e.g. month 1 = X * month 2 where X can be any value). This is called an AR(1) model.

If you’re seeing a significant difference in the forecast values between the two, it almost certainly comes down to the second reason, and although it adds a little complexity, in the vast majority of cases the new technique is more realistic and flexible.

It’s also far less likely to predict zero or negative traffic in the case of a severe downwards trend, which is nice.

How does it work?

There’s a hidden tab in the template where you can take a peek, but the short version is the “LINEST()” spreadsheet formula.

The inputs I’m using are:

Dependent variables

Whatever you put as column B in the inputs tab (like traffic)

Independent variables

Linear passing of time

Previous period’s traffic

Dummy variables for 11 months (12th month is represented by the other 11 variables all being 0)

Up to three “advanced” variables

The formula then gives a series of “coefficients” as outputs, which can be multiplied with values and added together to form a prediction like:

“Time period 10” traffic = Intercept + (Time Coefficient * 10) + (Previous Period Coefficient * Period 9 traffic)

You can see in that hidden sheet I’ve labelled and color-coded a lot of the outputs from the Linest formula, which may help you to get started if you want to play around with it yourself.

Potential extensions

If you do want to play around with this yourself, here are some areas I personally have in mind for further expansion that you might find interesting:

Daily data instead of monthly, with weekly seasonality (e.g. dip every Sunday)

Built-in growth targets (e.g. enter 20% growth by end of 2021)

Richard Fergie, whose Forecast Forge tool I mentioned a couple of times above, also provided some great suggestions for improving forecast accuracy with fairly limited extra complexity:

Smooth data and avoid negative predictions in extreme cases by taking the log() of inputs, and providing an exponent of outputs (smoothing data may or may not be a good thing depending on your perspective!).

Regress on the previous 12 months, instead of using the previous 1 month + seasonality (this requires 3 years’ minimum historical data)

I may or may not include some or all of the above myself over time, but if so I’ll make sure I use the same link and make a note of it in the spreadsheet, so this article always links to the most up-to-date version.

If you’ve made it this far, what would you like to see? Let me know in the comments!

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