Expert Perspectives
Expert Perspectives
Episode 141


In this episode we talked about:
- How to compare the current technology wave to the arrival of the internet
- Why generative referrals are leading to higher conversion rates in specific sectors
- The framework for transitioning from traditional search optimization to generative discovery
- How to optimize product data to be machine-readable for automated systems
- Why beauty and health categories serve as early indicators for adoption patterns
- The strategy for building first-party data to protect against algorithmic changes
- How to balance human and bot audiences in a modern storefront
- Why consumer trust in established retailers remains a barrier for new platforms
🎧 Listen now on Apple Podcasts, Spotify, or YouTube
Episode highlights:
01:29 – The reality of Gen AI as a retail technology wave
05:34 – Analyzing conversion rates from AI referral data
10:28 – Elements of the next generation online storefront
12:13 – Serving both humans and bots in the new discovery model
13:37 – The reality of AI checkouts and platform changes
15:59 – Challenges with attribution in a muddier data environment
Michelle's Bottom Line: GenAI isn't another channel to bolt on — it's a rewiring of commerce's plumbing, closer to the arrival of the internet than to the mobile or social shifts that preceded it. The near-term opportunity is discovery, not autonomous checkout: retailers still own the transaction and the trust, so the work is making your catalog machine-readable, your reviews credible, and your content authoritative enough to surface wherever the query starts.
Michelle Evans & Kailin Noivo — Transcript
The Ecommerce Toolbox: AI in Retail • Human-Reviewed Transcript
[00:00:00] Michelle Evans: And retailers and brands today are serving, you know, both humans and bots. I think GenAI is likely to impact across different categories, but the level and degree of that impact will be different, I'm sure, because of that need for comparison and reassurance.
[00:00:20] Kailin Noivo: For today's episode, we chatted with Michelle. We talked about a lot of different trends in retail and ecom, some very, really interesting insights. Like always, we talked a bit about AI. Excited for this episode.
[00:00:30] Kailin Noivo: Welcome to another episode of The Ecommerce Toolbox Expert's Perspective. Joining us today, we have Michelle Evans. Welcome, Michelle.
[00:00:38] Michelle Evans: Hi. Thanks for having me.
[00:00:39] Kailin Noivo: Awesome. Michelle, we always like to start off by learning a bit more about your career journey. So, why don't you take us through your career journey and how you ended up in your current role?
[00:00:49] Michelle Evans: Yeah. So, I've been at Euromonitor for 15 years, been covering sort of that intersection of, you know, retail and technology. As it stands today, my role, my title, is called Global Lead. So, I lead our retail insights and engagements on retail specifically at Euromonitor. And, obviously, you know, do things like this out at conferences, writing reports, speaking at clients, all of the above.
[00:01:17] Kailin Noivo: Very cool. I've seen some of your posts online. You're very passionate about AI discoverability, things like that. Obviously, being at Euromonitor for 15 years, you've been through a couple of different platform shifts. Just how big is kind of AI for ecom as a platform shift? And maybe talk us through some of the trends that you're seeing out of the gate. Like, what's hype? What's real?
[00:01:39] Michelle Evans: Yeah. Yeah. I think, you know, when it comes specifically to technology and how it influences different parts of retail, I think there's often hype associated with it. So, like I said, I've been covering this for a good 15 years now. And, you know, we've had AI, as in machine learning, in 2016, and IoT was everything in 2017, and you know, blockchain and the like. So, I think my analysis is more known for taking a more grounded and cautious view. So, certainly, I think, you know, AI or Gen AI as we know it is rapidly changing. Ecommerce, you know, I think where we're seeing a lot of that change is in terms of the discovery experience and rewriting that. You know, consumers are turning more and more to these platforms to ask questions, and then it's changing, you know, where those products come up, you know, in terms of where they see them first. It is also creating a lot of backend changes as well. So, that sort of shift from SEO to GEO that brands have to implement. I'm a little less bullish on the autonomous checkout, at least as it stands today. At the very least, I think we're way off. But when it comes to Gen AI and its influence, you know, I think this is gonna be a pretty big change, you know, I think it's certainly bigger than mobile was the rage in 2010, 2011, 2012, sort of time frame. I think it's certainly bigger than that. I think it's bigger than social. You know, I think it's a lot more like, you know, when the Internet came into retail and started to change how consumers shop, just because of the kind of fundamental changes going on underneath.
[00:03:34] Kailin Noivo: Very interesting. So, talk to me a bit about why you think it's going to be bigger than mobile or social, which are two huge drivers for ecom, right? If you look at socials effectively, most of the ads spend that people are doing are on TikTok, Meta, Instagram, and then mobile is now, honestly, dominating. I think last time I looked at it, it's, like, 70% of mobile, of website sessions. So, yeah, that's a really interesting take. Talk to me a bit about more detail, like why you think Gen AI in the context of online retail is going to be a bigger shift than those two things.
[00:04:11] Michelle Evans: Yeah. You know, I think from a social perspective, where my mindset is going is more like, we have a lot of referral data. And, you know, AI referrals are growing fast, so they grew 300% last year. And they're, you know, obviously, their gains team's still a small part of the overall pie. And when we look at it, so is social, really. A lot of it is driven, you know, so by search or direct links as well. So, that's why I wanted to put it, you know, into perspective from that standpoint. I think mobile, you know, what it did off the back of the Internet was sort of rewrite the consumer path, you know, and how they experienced websites. Obviously, you know, retailers and such had to make changes to make, you know, their web experience more mobile-friendly and the like. But I think what GenAI is doing is more like when the Internet came in from the standpoint of sort of, you know, it's gonna force players to sort of rewire that piping underneath commerce. So, you know, I think the frontend experience is changing for consumers. I think there's gonna have to be a big shift in the backend as well, and I think you'll see it at the end of the day in a few years in terms of the numbers, in terms of the referrals, and such. So, that's why I think it's a little bit bigger deal than those two I noted.
[00:05:44] Kailin Noivo: Yeah. That's interesting. And you're right. Referral data is still pretty small, but it is run really quick. How are you seeing from your data and just from chatting with merchants, like, how are you seeing the conversion side of it? Like, is it super high in tech traffic?
[00:05:59] Michelle Evans: Yeah. So, obviously, the conversion piece is still very small. You know, it'd be because overall, you know, I think if we look at just global share, AI referrals have about 2% of of the total sort of discovery-driven referrals. So, it's small potatoes at this point, rapidly growing, and then the conversion piece is gonna be even smaller than that. But in terms of, you know, what we're seeing come down the pipeline, you know, we are starting to see information from retailers to show, or to indicate that the AI-driven referrals are leading to higher conversion rates. So, I know some retailers are speaking openly about this. I spoke at Shoptalk Europe in June, and, obviously, that had a lot of European retailers. And one of them is Douglas Group out of Germany, which is, you know, more, you know, pharmacy and beauty and those kinds of products. And the executive there spoke about referrals, like, conversion was up from 3% to 4% to more like 5% to 6%. So, you know, kind of borderline doubling that rate. And I think it, you know, makes sense because, essentially, GenAI and those tools that are out there are helping consumers sort of move further down the path to purchase, gather more information on products, you know, build that confidence and whatnot before execution. So, already, you know, when they come to the retailer site, they're maybe more primed to make that purchase than if they were coming from, you know, a traditional website.
[00:07:44] Kailin Noivo: That's something that we've been hearing in the market as well, like, from our customer base, especially on the conversion side. Do you think that's gonna apply unilaterally across retail, or are you seeing from your early conversations that certain categories are actually seeing more of it than others? For example, like luxury, not seeing it compared to, like, home goods and things like that.
[00:08:07] Michelle Evans: Yeah. So, I don't think that what we're seeing happen in terms of this pivot towards AI shopping is not gonna happen uniformly across categories. So, you know, we look at it from a few different angles, but I think it's about, you know, how many products are on the shelf and can GenAI help you, you know, have a more convenient experience and get to that, you know, that product recommendation quicker? And then also, what's the confidence level you need to be able to make that decision? So, you know, if it's a higher ticket item, you may want more information before making that purchase. Obviously, we're buying a car, right? We'd probably do more research than if we were buying eggs. So, you know, in terms of some of the areas where we're seeing sort of faster pickup, you know, one of the areas is definitely just kind of the beauty space. You know? Beauty and also health, for that matter. And those tend to be areas that have, you know, high online penetration, high online sales. Consumers are shopping there already. But there are also products that, you know, lead to high-intent queries. So, you know, what is the best moisturizer for eczema? Something like that. And, you know, if you think about skin care, there's a lot of products out there. So, Gen AI can really help a consumer, you know, navigate through that and find that product selection. And then health does well, think about some more specific subcategories, like supplements, just because there's thousands of supplements out there. They all have different claims for how they, you know, will help your health. So, you know, in that sense, AI has a different role to play. So, you can start to think about those different dimensions that drive that and take it to other categories. So, I think beauty has a lot of similar characteristics as fashion, for example, to use to, you know, pull back to to your example that you used in the question to start.
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[00:10:34] Kailin Noivo: You named, recently, in next-gen online storefront as one of your kind of defining trends for the year ahead. What does that mean? Like, in plain terms, like what is the next-gen storefront look like in your opinion, and then how is it different from what people are working on today?
[00:10:48] Michelle Evans: Yeah. So, this was something that we've been looking at for a number of months. And, essentially, this idea is that the savviest retailers and brands are embracing new places of discovery, and tools for engagement and ways to serve shoppers. A piece of that is all this AI, the GenAI that I'm talking about, but it's obviously not the only piece. So, the way shoppers discover products is changing. So, retailers and brands are trying to embed more closer to the moment of inspiration when a consumer first gets excited, so that speaks to that social piece that we talked about, why TikTok does so well. You even see it in terms of, you know, if you think broadly about TikTok, it's about commerce needing content. So, you see players like Netflix moving into this, and that's where a lot of GenAI comes in as well, interactive discovery. And then there's also, you know, how do we engage shoppers when they're online? So, retailers and brands are using different engagement tools like shoppable videos and gamification and VR, conversational commerce, all to, you know, make that online shopping experience feel more like, you know, what we experience in-store. So, those are just, you know, two of the ways that we've approached that or talked about in that content.
[00:12:15] Kailin Noivo: Like, when you're chatting with these VPs of ecom that are balancing kind of, like, getting pushed on core metrics and growing revenue, in some cases, their overall traffic is kind of flat. How are you kind of advising them to think about the whole, like, well, it's small, but it's growing at 300% when it comes to the call it, like, the new front door to your site?
[00:12:38] Michelle Evans: Yeah. So I think, you know, where they need to be clear is that a shift is underway. And retailers and brands today are serving, you know, both humans and bots. So, we'll see, you know, some categories, like I mentioned earlier, with beauty and health more impacted. Some others, like snacks and pet care, and soft drinks, may have a limited impact today. So that potential, you know, really depends upon where that player, where retailers and brands sit in the ecosystem, sort of, you know, how fast they need to make changes. I think GenAI is likely to impact across different categories, but the level and degree of that impact will be different, I'm sure, because of that need for comparison and reassurance, like I spoke about a couple of minutes ago.
[00:13:35] Kailin Noivo: Yeah. No. It makes sense. Now, to transition to something that's a bit more up in the air, the AI checkout. Obviously, it was pretty highly publicized earlier this year. Shopify OpenAI. They were doing commerce in-app checkout. I think that's been abandoned, but when I use ChatGPT for product discovery, it kind of looks like it's broken, and it's been broken for, like, three months. So yeah, like, what are your thoughts on that? Is it inevitable? Is it something that's still up in the air?
[00:14:07] Michelle Evans: Yeah. So, for context, in March, ChatGPT pulled away from trying to create that in-chat checkout experience on the platform itself. So, that was a shift away. At this point, they're sort of conceding, you know, retailers own this experience. You do have someone like Shopify, on the heels of that, made an announcement that they're gonna enable this for their merchants. But in that case, also, merchants still own the experience. It's just leveraging Shopify to make that checkout happen. So, in terms of, you know, where we're at in the overall development, we're a long way off from this idea that people are going to ChatGPT and ignoring retailers altogether in their checkout experience. Retailers have the trust. We see that in our consumer surveys, by and large, across the world. Consumers say, you know, I trust the retailer more than I do the platform, the AI platform, to make a purchase. So, I think you have that playing into it. Obviously, sort of like those privacy and security concerns come into this as well. You know, we've seen the business models from these AI platforms evolving as well. So, ChatGPT, soon after they backed off on that, sort of shifted and pushed monetization more through advertising. So, they may be backing away entirely from that. Still early days, so we'll see, you know, what the twists and turns bring. But I don't think this idea of autonomous checkout is gonna be mainstream in the coming years, in the more near term.
[00:15:57] Kailin Noivo: Yeah. I agree. I think to your point, the discoverability aspect of it is likely where most retailers should be leaning in. It's where the growth is coming from and, yeah, fully aligned. Diving deeper into GenAI and then kind of bringing that back into social media influencers, as more and more kinds of sources of traffic come through, have you seen retailers struggle with, like, true attribution? For example, you find me through ChatGPT, go on the website, don't purchase, you're retargeted through social. Maybe at some point, I send you an email, like, how are people gonna be able to actually, truly understand attribution, especially because a lot of these platforms are just, they're not owned. Like, they're not owned by data sources that you have.
[00:16:48] Michelle Evans: Yeah. I think the reality is that the picture is getting muddier, really, as we go along for sure. Because I think even I've had the experience from the standpoint of, you know, like, experimenting with ChatGPT and trying to then go to the retailer website, where that experience becomes clunky. So, I may just myself go directly to the retailer. So, that right there breaks it, of course. So, you know, I think things are gonna probably become messier before they become any clearer in these coming years.
[00:17:25] Kailin Noivo: Especially because everyone's taking credit for everything with larger attribution windows. So, it's being double-counted. I know you spend a good amount of time talking to Europeans. How are Europeans thinking about this, like, the AI approach versus the U.S and North America?
[00:17:43] Michelle Evans: Yeah. So, I think a lot of people in the industry would say, you know, the U.S is 6 to 12 months ahead. It's interesting in our data and our AI referral data. If you take, like, the 6 largest European markets, which will put them on more equal footing in terms of population to the States, we do see that AI referral traffic is a bit higher in Europe. We're also seeing it replace search engine traffic faster. So, in some ways, that movement is happening there. Where you see the big difference is in terms of sort of the commercialization of AI. So, in the U.S, obviously, a lot of these tech giants are here. A lot of these models are based here. You're seeing a lot more partnerships here between AI platforms and retailers. Obviously, I mean, Amazon's chosen more of a walled garden, but Walmart is partnering, and players like Target are partnering. That's what you don't see in Europe as much. So, Carrefour, out of France, has one of the most advanced partnerships where they brought their, you know, grocery catalog into ChatGPT. But other than that, you know, most players are trying to figure this out on their own, build on their own. So, maybe taking more of a wait-and-see approach, but I think they're, you know, a lot more cautious about what this is and what it might be.
[00:19:10] Kailin Noivo: No. It makes sense. And it's cool that you mentioned Carrefour. They're a customer of ours, and they're actually, to your point, very innovative on this. Not to say that it surprises me. But to your point, European top 10 retailers, like you, don't think cutting edge of technology in my experience, right? So, it's really cool to see that. And looking ahead, you said one of the open questions is kind of like who claims the doorway? Do brands still control demand, and on what platform? Yeah. Like, what do you think retail leaders should be building today so that they're not entirely dependent on someone else's algorithm? Because, ultimately, like, it could end up being AI know these models are probabilistic and not deterministic, but at the end of the day, like, if you're a, I don't know, startup for growing plants in your house, Right? And then there's, like, an entrenched monopoly that returns 99% of the queries, 99% of the time, like, how are you really gonna break into that front door? So, how do you think retailers should be thinking about this?
[00:20:14] Michelle Evans: Yeah. You know? So, I think, you know, obviously, this is, you know, creating somewhat of a different ecosystem. Right? And I think we've seen it in retail before. Like, in Asia, super apps are very common, kind of have that closed ecosystem. They didn't really take off in the States, probably because we're a lot more competitive here, have a lot more players, so no one can get that kind of consolidation. But, yeah, I don't think any of these players want to be overly dependent on someone else's ecosystem. So, I think it is about building those assets that compound, you know, regardless of who controls the doorway. So, you know, having those strong brands, having first-party customer relationships, clean proprietary data, good content, genuine consumer trust, all of those things help. And those are what, you know, help to retain and drive value for shoppers. At the same time, I think retailers need to ensure they're visible inside these systems, especially if, you know, they start influencing where your shoppers are making decisions. And that means, you know, some data cleaning, right, that you have to make your data machine-readable. You have to have trusted reviews. Really, this idea of reviews and ratings has gotten more of a promotion in the last year, more authoritative content, and then just expertise to understand how these AI models work. So, I don't know that the goal is necessarily to predict who's going to win this doorway, but it's about becoming so relevant and so trusted and so discoverable that whatever doorway consumers use to get to you, and I don't think there's probably, there's not just one doorway, there never is. But regardless of who maybe takes control of certain doorways, that consumers still want to go to your retailer, that they still, you know, want to buy your products, have your customer experience, and if they're able to find you in this new world.
[00:22:26] Kailin Noivo: Very cool. Well, Michelle, this was an awesome conversation. Thank you so much. I always love seeing your takes online on LinkedIn and really appreciate you taking the time today.
[00:22:35] Michelle Evans: Of course. Thanks for the invite. I enjoyed the conversation today.
[00:22:39] Kailin Noivo: Awesome.
[00:22:40] Outro: The Ecommerce Toolbox: AI and Retail is brought to you by Noibu. To find out more about Noibu and how we unify error monitoring, site performance, and experience analytics to uncover growth opportunities and skyrocket your revenue, visit www.noibu.com. That's n-o-i-b-u.com. And then make sure to search for The Ecommerce Toolbox: AI and Retail on Apple Podcasts, Spotify, or anywhere else podcasts are found, and click subscribe so you don't miss out on any future episodes. On behalf of the team here at Noibu, thanks for listening.
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