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Home » How Stitch Fix Is Using Generative AI To Help Us Dress Better
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How Stitch Fix Is Using Generative AI To Help Us Dress Better

Press RoomBy Press Room8 March 20244 Mins Read
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How Stitch Fix Is Using Generative AI To Help Us Dress Better

Business leaders looking to harness generative AI – the technology made famous by ChatGPT – are facing some major strategic questions. What are the best ways to use generative AI within the organization? Where can the technology add the most value? And how can you find a delicate balance between human expertise and machine intelligence?

Online personal styling service Stitch Fix is a business that all organizations can learn from. The company was built on data and AI from the ground up, allowing it to provide a personalized styling service and ship clothes directly to customers’ doors – clothes that they know clients will love based on their style preferences and previous choices. But what makes Stitch Fix really special is its ability to strike that perfect balance between human knowledge and machine capabilities. Here’s how Stitch Fix is harnessing generative AI to streamline processes and provide a better service to customers.

A Data Goldmine

Stitch Fix is sitting on a goldmine of nearly 4.5 billion text data points that clients have shared with the company. This data may include a client’s style preferences or feedback on how an item fits them, for instance. It’s valuable data for understanding each customer’s style, but it’s often in the form of freeform text – making it tricky data to work with. Generative AI helps Stitch Fix leverage this complex, messy data because generative AI excels at quickly making sense of and summarizing vast amounts of text data.

Stitch Fix uses large language models from OpenAI, combined with their own deep learning recommendation algorithms, to interpret the feedback that clients share and then use that information to inform future recommendations. In other words, generative AI translates customer feedback into a format that Stitch Fix recommendation algorithms can understand more easily.

Let’s explore some specific use cases in a little more detail.

Creating Clothing Recommendations

One of the ways Stitch Fix uses generative AI is to surface a selection of clothing items based on feedback the client has shared about their style preferences and fit. These recommendations are shared with a human stylist, who will then curate the final pieces for the individual client.

Considering Stitch Fix has thousands of pieces in its inventory, this initial recommendation saves stylists valuable time and allows them to spend more time focusing on the client’s personal style needs.

Supporting Text Generation

Generative AI isn’t just about interpreting text. It can also create text (and images, and video, and more). Stitch Fix uses this ability to produce engaging ad copy that communicates the benefits of signing up for Stitch Fix’s service. All copy generated by AI is quality checked by human copywriters (with a 77 percent pass rate at the time of writing).

Generative AI also helps Stitch Fix create informative product descriptions that give clients details about an item’s features, specifications, and benefits. Writing descriptions for thousands of items is, as you can imagine, a time-consuming task. But having trained OpenAI’s GPT-3 on previous product descriptions (written by copywriters), plus feedback from clients, the model can now quickly create descriptions for copywriters and merchandisers to review. Stitch Fix says the model can generate 10,000 product descriptions every 30 minutes, with each description only needing a quick one-minute review by an expert before approval.

Automatically Styling Outfits

Another interesting use is Stitch Fix’s Outfit Creation Model (OCM), which uses generative AI to generate millions of new outfit combinations per day. OCM, which was trained on millions of outfits created by stylists, picks items from Stitch Fix’s current inventory, as well as from customers’ previous purchases, to compile personalized outfit suggestions for clients. This shows clients how to style items they might be interested in purchasing (or already own) with other items available from Stitch Fix. This is done through personalized emails and ads and through the customer’s personalized shopping feed.

Key Takeaways

In short, Stitch Fix uses generative AI to better understand what customers want – and, importantly, to strike a balance between automation and human skills. By letting AI systems automate the time-consuming, repetitive tasks, Stitch Fix frees up human experts to focus on their uniquely human capabilities like creativity, judgment, and building awesome relationships with clients. This is why I think all organizations can learn from Stitch Fix’s approach.

AI Artificial Intelligence Generative AI GenerativeAI OCM retail Stitch Fix
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