The Yes fashion shopping app spans the smartphone space to the wider web.
At the Fairchild Tech Forum on Wednesday, CEO and co-founder Julie Bornstein revealed that the company is launching a website based on the same data science that powers its popular mobile app.
The start-up launched in May 2020 with an iPhone app that presented users with different looks and asked yes / no questions to understand their preferences. The responses fueled data models that focused on their tastes and style, and with 100,000 downloads since then, the news stream has sprung up. According to the company, The Yes has seen more than eight million yes / no clicks in the app so far, and it’s growing 40 percent month-over-month.
Still, the company still realizes that sticking to just one iPhone app is a somewhat limited proposition.
“I think the first year was really about getting a product to market. And we started in mobile, because not only is it the fastest growing part, but it’s also a more restrictive format, ”she said during the“ The View From Next ”panel. Gen Fashion and Retail ”on Wednesday. “And so it forced us to make some tough choices. But at the end of the day, if you want to reach everyone, you have to be on the web. “
Today anyone can launch a webpage or eCommerce site with static listings. But that was never going to do for The Yes. Instead, it touts this launch as the first e-commerce site powered by a neural network – a data-driven approach that trains machines to perform tasks based on data models. In other words, The Yes has created a shopping site that remembers customers and all of their individual preferences every time they return, so that it can actively adapt to each user’s tastes.
Like the app, shoppers can answer simple yes-no questions about individual products – which, in fact, users find entertaining and even addicting, according to App Store reviews. There’s also a quiz on style, price, and size preferences, for a broader look at their general tastes, both of which inform the new site’s smart search feature.
Bornstein expanded on data science in exclusive commentary to WWD: “We have rebuilt the architecture of e-commerce to incorporate a layer of AI into the core technology. This allows us to create a personalized neural network with each buyer, ”she explained.
The more a mobile user or website visitor interacts and provides information, whether through the yes / no interactions or the style quiz, the better the business knows about their preferences. “It’s the first e-commerce system to adapt based on the explicit signals of each buyer,” Bornstein continued. “The result is that each customer’s ‘store’ adapts to her. Whether it’s on the home page, browsing, or searching, she’ll see products categorized by her style, brand, price, and color preferences, pre-selected in size.
“The effect of this eliminates all irrelevant products and helps her find what she likes in hundreds of brands in a whole new way,” she added.
In other words, two buyers don’t see the same product feed.
The Yes calls it “adaptive purchasing e-commerce”. But digital natives will find the formula familiar, as it’s similar to how streaming services like Pandora or Netflix queue up songs or movies they think the user might like next.
The concept isn’t entirely new – eBay launched its “Store of You” in 2018 with a similar premise – making the effort especially worthwhile for massive markets that can overwhelm buyers with so many choices. The e-commerce titan is competing for a high volume of ads quickly approaching two billion, for example.
The Yes offers almost 100,000 styles, which may not seem like much in comparison. But it’s only been a year and the selection is focused specifically on fashion, with a wide range of over 250 brands, from Mango and Everlane to Miu Miu and Balenciaga, in sizes from 00 to 40.
Its fundamental premise is to help fashion buyers navigate all of the choices, and perhaps determine what their individual style is, even if they don’t quite know themselves.
In either case, data science relies on the work of creating taxonomies from scratch. For eBay, a platform that crosses so many categories, it had to develop a so-called “taxonomy of interests” that can distinguish why buyers flock to certain types of products, based on their passions. For The Yes, his “Fashion Taxonomy” covers the nuances of style in clothing, footwear and related products.
“We create a lot of our underlying artificial intelligence models through intelligent labeling of data,” co-founder and CTO Amit Aggarwal told WWD. Today, every product in the catalog is automatically tagged through a machine learning model with over 500 detailed product attributes.
The result is a system that can distinguish between two skirts, dresses or other garments with very similar details, but different styles.
As you might expect, engineers make up more than half of the 40-person crew at The Yes. They have been busy creating a proprietary fit map that normalizes the size for all brands, which offers tremendous efficiency in making size recommendations or product recommendations based on size profiles. To promote brand discovery, they also built a personalized matrix that draws on a customer’s purchasing preferences and behaviors, as well as the expertise of a particular expert: the Fashion Director. and the creation Taylor Tomasi Hill, who previously hailed from Moda Operandi.
The combination of fashion and tech expertise has attracted $ 31 million in funding to date, along with a few other impressive numbers: According to its data, the platform is seeing conversion rates of over 6%. , with loyal customer rates exceeding 50%. Sixty percent of its shoppers are under 30, and its top customers use the app more than seven times per month and have purchased more than 20 items.
So far, the customer base looks like an even split of young shoppers who like to share the app and luxury shoppers who appreciate the ability to buy high and low in a single basket, 50% each. Additionally, The Yes claims that 90% of them consider the app to be one of their top shopping destinations.
There’s no question that mobile has been good for the business, so naturally he still sees himself as mobile first and recommends using the iPhone app, if that’s an option. The difference now is that it’s not a limiting factor. The data-driven startup can now accommodate any online shopper, regardless of what technology they use or what style they want.