Sometime in the Summer of 2017, Twitter user feldspath0id’s mom logged onto Facebook and was greeted with an advertisement that spoke to her soul.
It was a t-shirt. Not just any t-shirt, mind you — an incredibly niche work of art, adorned with a phrase that perfectly encapsulated who she was: “Never underestimate a MOTHER who listens to IRON MAIDEN and was born in AUGUST.”
That’s me, she thought. I’m a mom! I love Iron Maiden! I was born in August!
Without hesitation, she clicked through and bought it.
Chances are, you’ve seen similar products marketed to you on Facebook by people who seem to know exactly who you are, what you like, when you were born, where you live, who you love, and what you do.
These wares come in the form of t-shirts, coffee mugs, aprons, socks — all emblazoned with impossibly specific phrases like “These TITTIES belong to an ARMENIAN ACCOUNTANT,” or “Just a NEW JERSEY girl living in a WISCONSIN world.”
Who makes these products? How on Earth do they manage to generate such specific phrases? And what happens when things go wrong?
The algorithm merchants
In 2011, Michael Fowler, a 20-year veteran of the t-shirt business, began to experiment with ways to generate more designs.
At the time, his company, Solid Gold Bomb, had a catalog of around 1k t-shirts, each conceived by a human. But Fowler knew that the t-shirts were “a numbers game, a quantitative culture” — and to scale, he needed to dramatically increase his output.
So, he wrote a simple computer code that performed the following:
- Start with a phrase (e.g. “Kiss me, I’m a ____”)
- Scan a database of digital dictionaries, compile hundreds of thousands of words
- Formulate a massive list of phrase variations with these words
- Generate product images of t-shirts with phrases on them
Using a wide range of starting phrases, the algorithm could spit out an endless array of t-shirts. And by printing on demand, he could maintain a virtual inventory without printing shirts until they were actually ordered.
In short order, Solid Gold Bomb’s catalog ballooned to more than 22 million t-shirts.
On Amazon, the company listed 550k+ t-shirts. The hyper-specific phrases were hit or miss with customers — but small sales, aided by targeted Facebook ads, added up to a cumulatively large sum.
Soon, he was selling 800 shirts a day.
“It’s a ZACK who was born in FEBRUARY thing (you wouldn’t get it)”
The internet is rife with hundreds of fly-by-night t-shirt companies that operate in a similar fashion.
There’s a whole subreddit (r/TargetedShirts) with 29k users devoted to the weirdly specific t-shirts that show up in Facebook users’ feeds — shirts like “I love ANIME but JESUS always comes first,” or “I’m a VET who EATS BEEF and sings KARAOKE.”
After posting about alcohol and Harry Potter on his Facebook page, one user got an ad for a Beer-themed magic potion shirt. Another user who moved from Finland to Denmark starting getting personalized mugs in Finnish which hinted at her strained relationship with her mother.
Most of these businesses use algorithms to generate massive, almost unlimited digital inventories (sometimes, 25m+ designs), then rely on hyper-targeted Facebook ads to reach niche audiences in small volumes.
One site, Sunfrog, implores a user to enter a range of my data (name, city, birth month/year, hobbies, job), and then generates hundreds of customized t-shirts — “just for you!” — in seconds:
Another company boasts more than 10k variations of a single t-shirt phrase, with personalized names ranging from Aylin to Zara. Its catalog includes classics like “Never Underestimate A Woman Who Loves Stephen King And Was Born In April,” and “I’m a Tattooed Hippie Girl Born With a Mouth I Can’t Control.”
But as it turns out, the key to these operations (huge volume) can also be its curse — and oftentimes, these “algorithmically-generated” products can go terribly, terribly wrong.
Keep Calm and… destroy your company
He began with the phrase “Keep Calm and ____,” then compiled huge lists of verbs (to replace “carry”), and prepositions/pronouns (him/her, on/off, etc.). In the end, he generated about 700 variations of the phrase on t-shirts, and put them up on Amazon.
Unfortunately, things didn’t go according to plan.
As it turns out, Fowler’s algorithm had served as a sort of demented Mad Libs, generating phrases like “Keep Calm and Rape Them,” and “Keep Calm and Grope On.”
In a since-deleted apology letter, he harped on the downside of relying heavily on an algorithm with little human oversight — “The ‘Keep Calm’ shirts were computer generated, and we didn’t even know we had a shirt that says that,” he wrote — but it did little to assuage the internet’s fury.
Amazon swiftly removed the offending t-shirts, and a few months later, Solid Gold Bomb went out of business. Fowler, a father of 3, was left wondering how his algorithm had betrayed him.
This wasn’t the only time bot-generated products caused an uproar.
Last year, an Amazon retailer by the name of “my-handy-design” made an unwelcome splash on the internet over its questionable iPhone accessories.
A series of cases featured a seemingly random (and, consequently, NSFW) variance of images, including old men suffering from diarrhea, heroin spoons, toenail fungus, and “a three year old biracial boy in a medical stroller.”
The man behind the cases, a German computer consultant named Tobias Hartmann, had generated more that 31k products using a database of stock images.
“We have access to 40 million images, which include motifs of nearly anything imaginable,” he told OMR. “So, whenever a customer makes an order, we purchase the selected motif for them and then print it on the case.”
These mishaps beg an important question: in an age of retail governed by volume and scale, what happens to quality control?
Big data = big responsibility
In his 2006 book, The Long Tail, Chris Anderson argued that retail was moving away from a model where only a small number of popular products were sold, and toward a system with billions of niche products. The future, he wrote, would be “selling less of more.”
Back in the day, shelf space was expensive and retailers had to be selective about what they sold. Today’s digital retail space is an unfettered testing ground with virtually no limitations on volume. Amazon alone lists more than 580m products.
The atomization of culture and business is nothing new. But as algorithms are making it easier to saturate the market with low-quality products, entrepreneurs should be wary of scaling virtual inventory without oversight.
As Michael Fowler and others learned, big data comes with big responsibility — and big potential consequences.
After Solid Gold Bomb collapsed, Fowler served stints as a stray dog catcher and a traffic guard. Today, he’s back in the t-shirt business, and continues to use algorithms to generate millions of phrases. But now, he only pulls words from popular name lists and operates with a healthy “element of scrutiny.”
“If I wanted to, I could scale my current business up tomorrow,” he told BBC. “But I think I just have a more conservative approach now. I’m just trying to survive.”
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