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In an era where runway shows, highly anticipated drops, and celebrity photo shoots are all but inescapable, fashion forecasting and trend tracking is an endurance game. Identifying recurring themes is akin to a multilayered research project. But maybe the true results can only be found by looking beyond the confines of our micro-trend-ridden feeds for cold, hard data. That’s why Madé Lapuerta, the creator behind Data But Make It Fashion, is applying formulas to fashion.
“Putting quantifiable meaning behind trends has made the world of fashion feel more approachable for me,” Lapuerta says. “I wanted to bring logic and reasoning into something that is inherently subjective.” Her endeavor to translate fashion content into clear, conclusive metrics began in 2019. After watching McQueen, the documentary based on the life and career of Alexander McQueen, the data scientist felt moved to combine her knowledge in computer science and her passion for clothing. Lapuerta began experimenting with image-recognition models to detect recurring silhouettes, colors, and patterns in runway photos and sharing what she found on social media. “At first, it took a lot of throwing stuff at the wall to find out what people are really drawn to,” she shares. “I wanted to see what new, interesting insights I could form on this industry, and I learned that, like me, people want to see a concrete depiction of trends.”
Today, the 25-year-old creator conducts and shares studies on buzzworthy topics such as Taylor Swift’s complete history of Grammy gowns, fashion trends as recession indicators, and even average site-loading times of large luxury brands (Chanel wins for fastest) with her combined 280,000 followers across Instagram and TikTok. She creates engaging memes, graphs, and videos that break down her takeaways clear as day, leaving no room for trend confusion. For example, a pensive photo of Cher Horowitz from Clueless is captioned, “When people r saying denim maxi skirts are in style but u know interest in them has decreased by 20 percent this past month.” In another post, a photo from the ’90s of Kate Moss and Naomi Campbell dancing is captioned, “When people say Chanel bags are a bad investment but u know prices have increased over 660 percent since 1990.”
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Of course, a knack for creating shareable content is not Lapuerta’s only secret weapon. Her analysis method involves image recognition and manual tagging in code with the aid of AI recognition models she developed herself. This is what the data analyst uses to determine what’s inarguably in style. (Perhaps to no one’s surprise, Lapuerta graduated from Harvard’s school of engineering.)
The Olympics of Lapuerta’s metrics-driven deep dives is fashion month, and the gold medal is her highly engaged audience. So, what is it about fashion’s current landscape that leads us to crave evidence around what is or isn’t actually trending? According to social media’s most unbiased fashion forecaster, an influx of subjective opinions and hot takes has created a call for black-and-white information.
“There’s nothing wrong with this, but a lot of creators or fashion folks are sharing their opinions online. And when I was starting to become interested in fashion, as someone who feels very nerdy and into computer science, it was hard for me personally to know what is actually going on here,” Lapuerta shares. “One moment maxiskirts are cute, and the next they’re out. But when I turn to data, I can form my own opinion based on facts.”
There’s a limit to what data can tell one about their own taste—personal style can and should be nuanced — but at the very least, it’s a starting point for understanding what’s out there. Lapuerta herself doesn’t base her buying decisions around her findings, but she does incorporate the facts into her understanding of what’s happening in fashion. “It’s not the end-all be-all,” she says of her analysis. “Just because something is trending doesn’t mean everyone should like it or wear it. But it helps to know.”
Lapuerta has tapped into a rare, not yet oversaturated category of fashion content: the objective kind. “People are really interested in the way fashion and larger societal sentiment are intertwined,” the data analyst reports. “When I post about the hemline index, which states that hemlines get longer as the economy falls, people get really excited.” Earlier this year, Lapuerta posted a graph that illustrated the correlation between the S&P 500 and the percentage of miniskirts shown in spring runway collections, accompanied with a caption insinuating that shorter hemlines may be on the horizon. The caption read, “While the latest runway collections predicted a ~28 percent rise in mini skirts for spring 2023, could things be looking up??” Commenters responded, “*buys mini skirt*” and “This account is my bible.”
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In addition to backing up fashion theories, @databutmakeitfashion is also in the business of debunking. “There are always hypotheses and guesses about what’s in, and that’s interesting, but it’s not always right,” she says. One of Lapuerta’s top-performing posts of 2023 has been a graph that showed how, according to Google search data, the term quiet luxury rose in popularity by 1,230% between March and April of 2023. However, after running an analysis on more than a thousand looks from 2023 runway collections to track trends pertaining to quiet luxury, Lapuerta was surprised to find that logos, the antithesis of quiet luxury, were trending. “We’ve seen a consistent increase in logos on runways over the past four years,” she reports. “In spring 2023 shows, there was a 7% increase in logos on the runways.”
Evidently runway looks and consumer demand don’t always correlate. By dissecting the data, Lapuerta makes it clear that, similar to how our online echo chambers don’t always reflect what’s trending at large, runway trends aren’t always an accurate representation of what we’re actually wearing. Plus there are levels to this game. A trending item, such as a Chopova Lowena skirt, might become relevant due to its runway presence or commercial demand. But often it’s not until a smaller demographic of aspirational dressers, such as editors or industry icons, adopts the trend that consumers really want to buy it. In other words, a garment may enter our zeitgeists by way of ubiquitousness, but when it comes to what we want to wear, there’s nothing as powerful as who we see wearing it. It’s the Alexa Chung, Regina George, and Olsen twin effect, to name a few original converter culprits.
Beyond the topic of what to wear, Lapuerta’s audience is also looking to her for the facts on fashion ethics. “For instance, brands have talked a lot about reducing leather and fur, and a lot of customers get excited about that,” she says. “But leather was still in an average of 16% of the looks of spring 2023 collections.” Another data point Lapuerta continues to watch is diversity in body size on the runways. “The data shows that there is resistance from many legacy houses to embrace diversity, while newer brands continue to challenge them,” Lapuerta says. According to the creator, running tests to see which brands are following through on sustainability and diversity promises helps her and her audience understand where they want to shop. “Knowledge is power,” Lapuerta says. “And I’m putting knowledge out there so that we can make informed decisions.”
Along with highlighting trends, debunking theories, and shedding light on fashion ethics, Lapuerta has one more purpose behind Data But Make It Fashion—and this one is personal. “I used to think that in order to be a good engineer, I couldn’t be interested in fashion,” she says. “Whether someone is interested in fashion or data analytics, I want to make both feel more approachable.” After just four years of running the numbers, Lapuerta is helping thousands decide what to wear, pulling back the curtain on what’s truly trending, and making two typically intimidating fields feel more friendly—one fashion chart at a time.