Has this digital fashion platform figured out personalized recommendations?

Source: theyes.com
May 29, 2020

A new app, The Yes, claims to be the first to successfully merge computer vision, natural language processing and artificial intelligence (AI) to deliver truly personalized fashion recommendations.

“Unlike every other ecommerce site today, The Yes is adaptive, in session, which means as a shopper taps a Yes or No, the algorithm re-ranks products in real-time,” according to a press release.

Has this digital fashion platform figured out personalized recommendations?
Source: theyes.com

The claim is gaining some merit because the app’s CEO is Julie Bornstein, was most recently COO at Stitch Fix. Previously, she was Sephora’s chief digital officer. Amit Aggarwal, the other co-founder, has experience at Google, Bing, Groupon and Bloomreach.

When first using the app, shoppers answer a few questions about their style, such as “What do you never want to see in your feed?” The app then produces a personal home feed with recommended brands and trends specifically for that user. Further “yes” or “no” clicks help the algorithm better understand the user’s taste.

At the same time, an extensive taxonomy covering each sales item fine-tunes recommendations. Ms. Bornstein told TechCrunch, “We leveraged both machine learning and computer vision to train models to understand how to absorb all pieces of data related to a product, as well as the image itself and how to read images. And it gave us a really strong understanding of 500 dimensions for every single item.”

The app launched with 145 brands, including Everlane, Gucci, Levi’s and Theory. Each brand’s full digital catalog is integrated into the algorithm.

The Yes, which takes a cut of each brand’s sales, uses each brand’s own imagery for its app listings. The platform does not hold any inventory. Brands ship the merchandise directly to the customer.

The app promises to fulfill the role department stores used to play in supporting discovery for consumers and customer acquisition for brands.

“You went to a department store because it offered something different from going to a brand’s own store,” Ms. Bornstein told Fast Company. “Our thesis is that the same is true in the digital world. There’s always going to be room for a multi-brand experience, as long as it’s a fun, seamless one.”

DISCUSSION QUESTIONS: What do you see as the technological keys to delivering truly personalized product recommendations in fashion or other categories? What do you expect the sales results of more personalized recommendations to look like for brands and retailers?

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7 Comments on "Has this digital fashion platform figured out personalized recommendations?"

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Michael La Kier

Many have claimed to hit personalization right, but it’s hard to do. Bravo if The Yes can leverage computer vision, natural language processing, and artificial intelligence (AI) to deliver truly personalized fashion recommendations. But the real question for personalization is, will this drive better conversion and sales? Furthermore, fashion is fickle; if The Yes delivers personalized recommendations based on my preferences I’m more likely to dress like it’s the 1990s than like it’s the 2020s, and that’s not a good thing (trust me).

Suresh Chaganti

Certainly an important step. It has a Tinder-esque feel as users affirm their choices. More seriously though, there is certainly lot of scope and hope for AI and augmented reality to provide virtual try-on rooms – to get the fit and look right, and reduce returns significantly.

Karen S. Herman

This is fabulous. Let’s start with the super smart rollout of The Yes. The app is available on iOS for the iPhone exclusively, it is only available in the U.S. and for women’s apparel. Brilliant positioning and timing, considering where we are with the coronavirus and its impact on retail. The Yes generates highly-curated, personalized recommendations of brands and trends that are user specific and refined use by use. This offers immediate discovery, investigation and selection for the user and connects them to a variety of brands, from startups to established names. Very promising. I just wish the app was available for Android, too.

Gabriela Baiter

I’m all for this solution. Shopping has been making a dramatic shift to mobile and as more and more Millennials grow accustomed to alternative interfaces (Tinder/Bumble/Eats/Postmates/Uber), they will be looking for this in shopping platforms. Within fast fashion, brands can learn from only showing what is relevant to a customer, while getting increasingly “smarter” the more that customers use it.

Stephen Rector

The key to delivering personalized product recommendations is — for example — for machine learning to understand whether a customer likes skirts or if they like a floral printed skirt and, therefore, likes floral prints in every category. Also, when that floral printed skirt is added to the cart, the “complete the outfit” suggestions need to make more sense. Does the customer need another printed floral skirt? Or do they need the shoe to complete the outfit? These are all questions that have to be thought through and often the technology isn’t there or the data science teams are not aligned with other business stakeholders. Fashion isn’t easy online – it’s not the same as buying batteries – hence Amazon’s struggle in this area.

David Leibowitz

Personalization is the new curation.

I do like the marketplace idea behind this. Though the Yes/No works for Spotify and iHeartRadio, I wonder if it is as effective as passive signals. Consider the duration of time spent browsing an item (what we call dwell in-store), copying a link with intent to share, checking for a size or price. Even when the item in my size is out of stock, my intent to purchase is a still a strong signal. So, merge all of that with the swipe right/left and this could make for a more compelling shopping experience.

April Sabral

The sport of shopping is to have others help me and recommend items I may not have selected. This is what always concerns me about making recommendations based only on preferences; working in bricks and mortar for years, this is one of the joys of interacting with a human. However, I think this is going to be successful as most of us like what we like and if the YES can match us with like items, then that’s making a consumer journey easier.

"Brilliant positioning and timing, considering where we are with the coronavirus and its impact on retail. "

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