Digital First, Physical Second: Wayfair’s Fiona Tan

**Sam Ransbotham** (0:02)
Even digital first companies approach technology implementations with caution, ensuring they limit their exposure to risk. In today's episode, find out how one e-commerce retailer thinks about implementing and scaling AI.

**Fiona Tan** (0:17)
I'm Fiona Tan from Wayfair, and you're listening to Me, Myself, and AI.

**Sam Ransbotham** (0:22)
Welcome to Me, Myself, and AI, a podcast on artificial intelligence and business.
Each episode, we introduce you to someone innovating with AI. I'm Sam Ransbotham, Professor of Analytics at Boston College. I'm also the AI and Business Strategy guest editor at MIT Sloan Management Review.

**Shervin Khodabandeh** (0:41)
And I'm Shervin Khodabandeh, senior partner with BCG, and I co-lead BCG's AI practice in North America. Together, MIT SMR and BCG have been researching and publishing on AI for six years, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.

**Sam Ransbotham** (1:06)
Today, Shervin and I are excited to be joined by Fiona Tan.
Fiona is the CTO at Wayfair. Fiona, thanks for joining us. Welcome.

**Fiona Tan** (1:13)
Thank you for having me.

**Sam Ransbotham** (1:15)
Let's get started.
We've got listeners throughout the world that may not be as familiar with Wayfair as Shervin and I are. We could probably look around our rooms and find Wayfair items. But can you start by describing Wayfair? What does Wayfair do?

**Fiona Tan** (1:29)
Sure. First of all, thank you for being customers. Always happy to have customers to talk to.
But yeah, basically, we are a digital-first retailer in the home goods category. We've also augmented that now with some stores, opening our second store in the Boston, Massachusetts area. And so really excited about that as well as we move to what's being an omni-channel retailer.

**Sam Ransbotham** (1:49)
That's the opposite direction that most people go.

**Fiona Tan** (1:51)
You know, it is, but it's actually kind of neat. It does afford us some interesting ways of approaching it because we are digital-first. I think hopefully you'll find that there are some really nice, the way that we are able to tie in the digital aspects. You go in the store, you see what's there, but you can also see the rest of our catalog in a way that's hopefully really useful and a little bit different than the typical brick and mortar shopping experience.
Part of it, too, that's really interesting about Wayfair and our approach to AI ML, right? A lot of the, it's under the covers and you don't realize, but what is actually powering the entire experience that you have as a customer and then also for our suppliers, there's a lot of machine learning and AI behind it that's not invisible, but it is actually powering everything that we do. For example, there's a lot around trying to understand the customer's intent, and we do that in as much as what they can tell us in the search strings, et cetera, but also based on where they've looked and how much time they spent looking at something versus another thing. So we try to build up our customer graph and then we also look at the products, the items that we're listing on our site. Because of the category that we're in, we don't really have as much branded items. So it's how do we use AI and ML to upload as many items as possible? And we have tens of millions of items on our site.
And be able to get as much product information as possible. Some of that we get from our suppliers, but a lot of the product information, we are using AI and ML to actually glean from the photos they give us, from the text that they give us, to be able to form our product understanding.
So we build out customer graph, we build out a product graph, all using AI and ML. And then we do that matchmaking. When you're on our site and you're looking for something, or we can personalize based on what we already know about you, that's the magic. How do we find you that perfect couch when you can't really describe it to me in a very succinct way?

**Shervin Khodabandeh** (3:45)
Fiona, tell us a bit about your own journey. How did you get into technology and how did that evolve?

**Fiona Tan** (3:52)
I went to MIT as an undergrad and I took my first computer science class, 6.001, and fell in love with it. And it's one of those things, I look back and I'm like, I'm so fortunate to find something that I enjoy doing, and I realized they're going to pay me money for it. And this was one of those really fortuitous moments, I think, when I realized, hey, I've always loved solving problems. I always loved optimizing whatever I was doing. And here's a field where I get to do that in practice.