Michael Kors’s AI styling assistant helps shoppers find the perfect date outfit

Mastercard-led Dynamic Yield has joined forces with Michael Kors on Shopping Muse.
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Anna Kim

4 min read

Imagine browsing your favorite retailer’s website looking through a massive selection of products to find the perfect outfit for your friend’s wedding and the right shoes to go with it. It can be confusing and sometimes intimidating, to say the least.

Well, Shopping Muse—a next-generation retail assistant from Dynamic Yield, a Mastercard company—may make things a tad easier…at least if you’ll be shopping at Michael Kors, which has become the first retailer to adopt the tech.

“Retailers need new ways to reach shoppers that have a lot of options and often little patience, and consumers need to get what they’re looking for quickly and effectively,” Ori Bauer, CEO of Dynamic Yield, told Retail Brew via email. “Using generative AI and our deep personalization capabilities, we created a solution that meets both of those challenges.”

With Shopping Muse, consumers can log on to the retailer’s website and punch in questions or commands like “What do I wear to the beach?” or “I want to look great on a date,” in the styling assistant pop-up, which will then generate a series of apparel options with accessories to match.

“Retailers can deliver a level of tailored engagement you could previously only really get from an in-store sales associate,” Bauer said, adding that they only started working on the platform last year before bringing it to market in November.

AI for an AI: Generative AI is estimated to bring anywhere between $150 billion to $275 billion to the apparel, fashion, and luxury industries, over the next three to five years, per McKinsey & Co.

So while the tech may make things easier for customers in some ways, it is hardly new, with retailers like Ssense and companies like Klarna and Google launching their own versions over the past year.

Bauer, however, insists that personalization is what sets Shopping Muse apart from the other players. “In addition to the direct questions it’s being asked, the tool considers contextual insights like the shopper’s location (when enabled) and their real-time behavior on the website (i.e., what they’re clicking on, what else is in their cart, etc.),” he explained. “If a shopper is logged in, it’ll also account for past purchases and demonstrated preferences to ensure that the recommendations it’s serving are as relevant as possible. None of this is done without the shoppers’ explicit consent.”

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Per Dynamic Yield’s initial tests, Shopping Muse has generated around a 15%–20% higher conversion rate than traditional search queries. And although the company is eyeing several fashion retailers for a partnership, it is also looking to expand its tech to categories like furniture and even grocery stores.

“In my house, we do Taco Tuesday every week, and my daughter, who is gluten-free, has specific dietary restrictions that limit what we can buy,” Bauer said. “I like to grocery shop online and if my store had Shopping Muse, I could ask it to help. Typing in ‘Show me gluten-free products I can use for a taco night’ would save me time sifting through nutritional labels and expose me to new products I maybe didn’t know existed. The discovery aspect is the unsung hero; with Shopping Muse, I’m introduced to new items that are in line with what I’m looking for or similar to what I already like, providing real value.”

Citing research by his own company that found that 77% of grocery customers expect a tailored digital experience, but only 11% of brands are actually delivering it, he added that he hoped Shopping Muse could help bridge that gap, “making online grocery shopping even more efficient, and improve discovery in a traditionally crowded environment,” he said.

Retail news that keeps industry pros in the know

Retail Brew delivers the latest retail industry news and insights surrounding marketing, DTC, and e-commerce to keep leaders and decision-makers up to date.