How Wayfair stays on the leading edge of AI Search

Imagine buying a brand-new, midcentury sectional online. You’ve measured your living room, coordinated the color scheme, and clicked “buy.” But when the delivery truck arrives at your urban walk-up, reality hits: The couch won’t fit through the front door.

Preventing these delivery day disappointments requires more than just good logistics. It demands rich product data, intuitive Search experiences, and, increasingly, the power of AI. Global home retailer Wayfair is at the forefront of this shift, continually experimenting with the latest technology to transform how people shop for their homes.

To find out how Wayfair keeps innovating in the AI era of Search, we sat down with CMO Paul Toms.

How are you thinking about today’s superempowered consumers, and where is Wayfair focusing its efforts to stay top of mind?

Paul Toms: Our biggest opportunity is to connect with consumers well before they have active shopping intent. So when a need does arise, Wayfair is already top of mind as the place to start their journey. Search remains incredibly important to us, and we’re obviously a significant participant there.

But we’re also spending a lot of time thinking about what happens before Search, how we build relevance and consideration before a customer is actively shopping. That means showing up in places where consumers are already spending their time, such as YouTube, with creators and live sports.

This fall, we’re also launching a new brand platform designed to deepen that connection and keep Wayfair in customers’ minds even when they’re not actively shopping. The goal is to be there throughout the journey, not just when intent already exists.

With a marketplace catalog of over 40 million items, how do you ensure product data integrity and accuracy at scale, especially when rich data is so critical for showing up in Search?

Toms: Feed richness is an always-on marathon. Every year, the feed is going to grow because these models are going to need more information, and more information leads to even more data needs.

AI allows us to manage it at a scale that wasn’t possible before. It enables us to provide rich data on a set of items in the shoulder or tail of our catalog. It gives those products a chance to show up and be matched to customers as Search looks for more specificity in recommendations.

At the same time, as a retailer with marketplace dynamics, data integrity starts with our suppliers. We hold our supplier partners to a high standard, and we have many checks in place to ensure they are trustworthy and committed to the customer experience. For example, we’re using Google’s Gemini AI models to test dimension validation, looking for conflicts between a product’s text and imagery, and the measurements provided directly by the supplier. We also have a suite of AI QA tools to crossvalidate data. This is critical to our business, because the No. 1 cause for returns on a lot of our large items is that they don’t fit through the door.

Ultimately, we hold a very high bar on what we call “accurate.” We know Google does too, because, by the time you’re buying a sofa and need it to be a certain size, you can’t be wrong when it reaches the doorstep.

What is your approach to identifying and capturing new market opportunities to drive growth?

Toms: Our muscle, and where we’ve seen significant results, is our experimentation platform. It allows us to test novel approaches and ideas in days or weeks, quickly identifying pockets of opportunity where we can offer something different and drive incremental growth. Just as importantly, it helps us identify areas without incremental growth, so we can avoid wasting time and money. Our strong, collaborative partnership with Google is a great example of this in action. Across Search and YouTube, we’re constantly testing, learning, and refining new approaches to uncover opportunities and scale what works.

As a Universal Commerce Protocol partner and pioneer in agentic commerce, what’s your advice to brands preparing for a future where AI agents play a role in how people shop?

Toms: First, focus on the quality of your feed. Second, look at your web surfaces and ask, “If an agent is searching on behalf of a user, is our experience readable enough for it?” Getting those foundations right is important, but so is being part of shaping what comes next.

For us, that means prioritizing close partnerships, innovating early with AI, and putting ourselves in a position to gain that first-mover advantage. That means being willing to invest the time, engineering effort, and cycles even before there are commercial returns.

How have you been able to turn AI ambition into an organizational mindset at Wayfair?

Toms: We’ve been around for 24 years, and we see ourselves as a tech company committed to being on the leading edge. AI is the leading edge for the foreseeable future, so we are committed to using the technology in every possible way. That framing makes it easy.

What allows this to work and scale in lockstep is that the entire organization sees that we have prioritized it. We have built space for it, set OKRs around it, and we are able to innovate at scale across creative, merchandising, search, and supply chain. Marketing is just one part of that.

In my conversations with other companies, I think it is easy to trip up there. Some say, “Oh, we’ll use AI when it benefits us.” Our perspective is: “No, we are going to use AI and commit to it before it benefits us.” We know that up-front investment is what gives us the edge over a longer period of time. You are already seeing companies diverge, and you don’t want to be on the wrong side of that shift.