You may have noticed over the last few months that we have been diving deep into the world of AI and how this is impacting the search landscape. As a Search Experience Agency, we’re fascinated with how the introduction of ChatGPT and AI Overviews is impacting the way consumers shop, and the impact this is having on the overall purchasing journey. 

But, there’s nothing like some real world insight and experience when it comes to these changes, so we sat down with the wonderful Michelle Gunn, Head of Digital Trading & UX at schuh, to find out how they’re not only adapting to this rapidly evolving search landscape, but how they’re investing in AI technologies to help further their product search and discovery experience. 

Q: We know that the introduction of AI in Search is rapidly changing the landscape – how does this affect how you do your job, as someone who isn’t solely focused on SEO? 

M: Well we know that this conversation does often centre around SEO and digital marketing however, at schuh, we believe that optimising for search starts with the product itself. We want to consider the full search experience journey, both offsite and onsite, starting with how we set up our products for success. 

Q: You’re a footwear retailer in a heavily branded fashion world, so I can see how product is key. Can you elaborate on what you mean by setting up your products for success?

Michelle: Absolutely. Traditionally, product attribution involves basic details like fabric, colour, and size. However, this limited information restricts our ability to leverage search effectively. We’ve been exploring how AI can enrich product attribution. By combining visual search with tagging, we can expand the attributes associated with each product significantly. This provides a wealth of searchable data, enabling us to answer customer queries more effectively and align with their search intent.

Q: Can you give us an example of how this AI-powered product attribution works in practice?

Michelle: Certainly. Let’s take a simple product like a shoe. Our initial product tags might be limited to basic descriptors. But by applying AI visual search and tagging, we uncover a much wider range of attributes, from style and occasion to specific design details. This richer data set then allows us to connect with more nuanced customer searches – as you can see from the image below. 

Q: I see. So you’re essentially using AI to build a more comprehensive and searchable product vocabulary. What about staying ahead of trends? How does AI help you there?

Michelle: That’s a crucial aspect, especially in the fast-paced world of fashion. We use social listening tools to identify micro-trends emerging on platforms like TikTok. By integrating this data with our product attribution, we can quickly update our tags to reflect these trends. For example, we might discover a new slang term for “cowboy boots” trending on TikTok. We can then incorporate this term into our product tags, ensuring our products appear in searches using that language.

Q: It sounds like this approach creates a feedback loop between your products, your customers, and the wider search landscape. How does this impact your overall search strategy?

Michelle: Exactly! This constant cycle of learning and adaptation is key to our success. By integrating social listening, AI-powered product attribution, and on-site optimisation, we create a seamless search experience. Whether a customer discovers us through a Google search, a TikTok video, or our website navigation, we aim to provide relevant and engaging content that leads to conversion.

Q: Thanks, Michelle. This has been a fascinating insight into how schuh is approaching the challenges and opportunities of the evolving search landscape. Your emphasis on the product as the foundation of search optimisation is truly innovative.