Growing up, Madé Lapuerta always relied on data and coding to navigate the often confusing journey of establishing an online presence. More specifically, she wanted people to listen to One Direction right away when they logged on her Tumblr page, which was dedicated to the now-defunct British boy band. “I didn’t really know a whole lot about what the opportunities would be for me in computer science,” the Harvard graduate tells Refinery29. “I just knew it was something that I enjoyed doing, specifically how my ideas or things that I thought were interesting, could come to life with code.”
Now, as the alias @databutmakeitfashion, she spends her time digesting fashion trends on social media for her nearly 135,000 followers across Instagram and TikTok. “It wasn’t something that happened overnight,” she says. “It was this long journey of learning as much as I could about computer science and then throwing stuff to the wall to see what were the interesting ways that it could be intersected with my passion for clothing and runways.”
The result is a plethora of highly educational and data-driven videos that make the revolving door of micro trends, aesthetics, and runways a little easier to navigate. Recently, she analyzed the chaotic wardrobe of Emily in Paris’ titular character (for the record, 29% of the character’s outfits have a neon color) and compared designer Daniel Lee’s debut collections at both Bottega Veneta and Burberry (the graphic revealed that Lee’s Burberry debut had 73% more patterns than Bottega Veneta’s). On her website, she also dives into trending items, like ballet flats and UGG platform boots, where she compiles more user-friendly data that’s targeted to helping people make shopping decisions. “If you’re not buying pieces from shows, which I’m not, it’s an interesting way for me to understand how I can dress similar to a certain runway collection without having to specifically buy these high fashion, high price tag pieces,” says Lapuerta, who has also self-published a series of books, titled The Little Book of Big Fashion Data.
@databutmakeitfashion is the Burberry trench coat dead?? 👀🕵🏻♀️🕵🏻♀️ #fashiontrends #dataanalytics #burberry #londonfashionweek #daniellee #bottegaveneta ♬ cardigan – Taylor Swift
While fashion is often compared to art and is seen as a subjective medium, for Lapuerta – when it comes to design and trends – it’s a numbers game. Through her data work, she’s hoping to debunk today’s TikTok-accelerated cycle, which has seen the rise of trend reporting as its own trend, often without any data backing. “Trends are just changing too quickly in a way that’s frustrating for consumers because there’s always something to keep up on, but it’s also just very unsustainable to be buying new products every week because that’s how quickly trends are changing,” she says.
So, how does she do it? “I definitely go to Vogue Runway, it’s probably my most visited site,” she admits. Yet, that’s just the starting point. After reviewing coverage about a runway collection, she goes through each look within the lineup, which can often have anywhere between 50 to 70 outfits. Using a mix of manual tagging, as well as image recognition software, Lapuerta applies some code, leading to the exact percentage of trends and items seen in the collection. To understand trends in a macro sense, she samples an average of 20 collections, doing the same process across all of them to get a final result. And what does she look for? “Anything that’s more than half of the collection is pretty big,” she says, adding that the quarter percentage is also a telling mark. “For anything less than 10%, I consider it a micro trend.”
But Lapuerta is also deeply intrigued by Google Trends, the search engine that allows people to see what others have been asking on the internet. She finds that in the intimacy of their computer people actually let loose to what they want to buy and how they want to dress. “People tell their secrets to the Google search bar,” she says, an idea she first came about after reading the book Everybody Lies by data scientist Seth Stephens-Davidowitz. “People can say, ‘Oh, I hate ballet flats,’ but they’re secretly searching for them.” This specific example rings true to our current trend cycle: While people seem to detest the comeback of ballet flats all over social media, according to data gathered by Lapuerta, red ballet flats have risen 71% in popularity.
Like any data-driven, fashion-obsessed person, Lapuerta also applies similar formulas to her personal style and shopping choices. “When I started analyzing trends and runway collections, I started leaning more to quality over quantity,” she says. “It kind of lets me know what I should be investing in.” And while her process may look intimidating, she says that using data to build one’s personal style is not as difficult as it sounds. “I’m trying with my work to debunk the idea that conducting data analytics or using computer science is something that’s reserved for a select few and something that can be applied to your everyday life and not this super daunting topic,” she says.
@databutmakeitfashion what do you think? 💸💸 #fashiontrends #dataanalytics #chanel #chanelbag ♬ Dreamy Vibes – Ocean Bay Jazz
Even if you don’t have a computer science background, we all use data to get dressed, especially in an era when TikTok hashtags and viral videos influence our shopping decisions. But Lapuerta recommends other tools too. First, she suggests relying on Google Trends. “When deciding to make purchases, you definitely can use data to see if this is a trend that is pretty persistent across winter and summer, is it a trend that’s been persistent across the last three years or like is it a trend that you know had no Google search data available until even the last month.” If the response is the latter, Lapuerta considers that a micro trend, saying that those are probably not good investments in the long run. When it comes to deciding colors to include in your wardrobe – which Lapuerta analyzes with image recognition software – she says it’s a matter of analyzing the hue’s timelessness, as well as looking at how many pieces in your wardrobe it’s compatible to style with. During our interview, I threw in the idea of inputting everything I own in my closet into a spreadsheet by category and color, an exercise Lapuerta hasn’t applied to her own wardrobe, but recommends for people who are data nerds with no computer science training.
“[Data analytics] is something that can really be applied to anything,” she says. “Data and technology really intersect with any industry, from fashion to sports analytics to entertainment to airplanes. So, I think I definitely want to show that if you have any interests, like fashion, data can intersect with them regardless.”
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