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10 minutes of expert insights every weekday. Your morning ritual for staying ahead in retail media.
Editorial - Benedict Evans on AI
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[00:00:00] Kiri Masters: Benedict Evans, who is one of the clearest strategic thinkers in tech, doesn't compare AI to the invention of electricity or the Industrial Revolution, or some other comparisons that have been [00:00:15] made know he has a more grounded comparison. The invention of the iPhone.
[00:00:22] Now the invention of the iPhone on the surface doesn't sound like that big a deal, but when you think [00:00:30] about the second order effects of that technology, the assumptions that people made at the time and what actually happened, it actually is a massive deal. And the lesson from that time is that you can be totally right, [00:00:45] that a technology is going to be transformative.
[00:00:49] And still be completely wrong about who wins and where the value goes. This same thinking matters enormously for [00:01:00] retail media as we're looking at the precipice of a huge platform shift with AI and AI enabled shopping.
[00:01:08] In this episode, I'm gonna share a few highlights from an interview with Benedict Evans on another podcast called The [00:01:15] Knowledge Project, and I'm going to play some snippets from Benedict
[00:01:19] and share some of my initial thinking on how this relates back to retail media and what we're seeing in the retail category. So let's jump in.
[00:01:29]
[00:01:31] Kiri Masters: Let's first talk about value capture and the real impact of the iPhone.
[00:01:37] Benedict: you know, I was a, a telecoms analyst in 2000 and it was very clear mobile internet was going to be a thing. It was not clear that there would be basically [00:01:45] small pc. Like, that was the, the fundamental shift of the I iPhone is, it's a small Mac, it's not a phone with better ui, it's a small Mac.
[00:01:52] And it wasn't clear that the telcos would get no value. It wasn't clear. Microsoft and Nokia would get no value. [00:02:00] It wasn't clear, it would take 10 years before it took off. Um, and it wasn't clear it would replace the PC as the center of the tech industry. I mean, everyone was talking about, well, what's a mobile use case?
[00:02:09] What would you do? You'll do some things on your mobile phone, but what, but obviously your PC will be how you [00:02:15] use the internet. And of course that's not how it worked. And so I, we kind of forget because now we don't see it because now it just kind of became part of the air we breathe how weird and strange and different all these things are.
[00:02:26] And yes, this is new and weird and different in a bunch of kind of [00:02:30] strange, confusing, confounding ways we can probably talk about, but we sort of forget that other things were weird and strange and different too.
[00:02:36]
[00:02:37] Kiri Masters: This example makes me think about all the assumptions that we have. Right now about the [00:02:45] incentives that the different players in the retail space have and the levers that they currently control. All of those things are at risk with such a major technology [00:03:00] shift, and as usual, it's the incumbents who have the most to lose.
[00:03:06] Let's talk about retailers first. They are adding AI features to their websites. So we've got Rufuss at Amazon, Sparky at [00:03:15] Walmart, and a whole host of other AI features being rolled out on other retailer dot coms.
[00:03:21] And with the exception of Rufuss and Sparky, these are essentially alternate [00:03:30] interfaces for the same shopping journey. It's really a replacement and often a more clunky replacement for the current search bar. Meanwhile, the AI platforms like Chat, GBT, and Perplexity. [00:03:45] And Google, they're working towards something different, which is a new starting point for commerce that could possibly replace retailer websites in general, or at the very least, as the [00:04:00] very start of the shopping journey.
[00:04:02] The place that we go to research items to compare different options to get ideas.
[00:04:11] And this leads us to a behavior reset. [00:04:15] This is the mechanism that makes platform transitions so dangerous that consumers change where they start. Let's listen to Benedict in the interview about such behavior resets
[00:04:29] Benedict: The very [00:04:30] high level threat to Google is that you have this moment of discontinuity in which everybody resets their priors and reconsiders their defaults. And so it's no longer just the default that you go and use Google and for this search or that search, like maybe Bing is 10% better on that search.
[00:04:44] In fact, [00:04:45] as we saw from the micro, the, the, the Google. TAC trial last year actually go being is Google is still the best search engine by quite a long margin relative to the other traditional search engines. But what we have now is like a reset of the playing field. Um, and [00:05:00] Google has a whole bunch of advantages as to why they might win in that playing field.
[00:05:04] But there's a reset both of what the product is and and and how you sell it and your org structure around selling it. And do you have the right politics and the right org structure to build that and the right incentives and internal [00:05:15] conflicts. And then the consumer behavior kind of gets through reset as well.
[00:05:17]
[00:05:19] Kiri Masters: Benedict talks elsewhere in the episode about how when the iPhone arrived, people didn't just get a better phone, they stopped turning on their desktop [00:05:30] computers as often. The PC was still perfectly functional.
[00:05:35] Software companies like Microsoft weren't suddenly making worse software, but. The default behavior shifted [00:05:45] because something was better about using a phone. It was portable, it was with you, wherever you were, and the capabilities that you could unlock from that phone in your pocket quickly came to be.
[00:05:59] [00:06:00] Almost as good as what you could get on a desktop. So instead of sitting down at a desk to check email, browse the web, or look something up, people just started pulling out their phones.
[00:06:11] That same dynamic threatens retail media right now. [00:06:15] Retail media network revenue, which is. Largely made up of onsite sponsored product ad revenue. That is the bulk of current retail media spend. That revenue depends entirely on traffic. [00:06:30] Going to a retailer.com if these L LMS intercept shopping queries before consumers reach a retailer.com, that onsite ad inventory and the advertiser demand for it shrinks. [00:06:45] Miracle Ads is the Ad Tech solution trusted by Rakuten and over 50 global enterprise retailers. That's because Miracle Ads was built [00:07:00] with both three P Marketplace sellers and one P suppliers in mind. Both advertiser audiences demand a seamless advertising journey from onboarding to reporting.
[00:07:11] You can offer everything from sponsored products to video [00:07:15] ads all in one solution. Learn more@miracle.com. That's M-I-R-A-K l.com.
[00:07:23]
[00:07:24] Kiri Masters: Now the retailers themselves, of course, are going to survive. AI platform companies have [00:07:30] no intention of becoming retailers themselves, even as they pursue potential marketplace, um, strategies or affiliates strategies as a mechanism for [00:07:45] monetization. They're not gonna become retailers storing inventory,
[00:07:49] but it calls into question if retail media, as we currently know, it will survive.
[00:07:56] And a final highlight from this episode before I jump into [00:08:00] conclusions that incumbents generally first look to make the new technology a feature of what they already have. Let's listen to Benedict.
[00:08:09] Benedict: The thing is when any, with any of these sort of fundamental technology changes, the incumbents always try and make it a feature [00:08:15] and they try and absorb it. And the same thing outside of technology. Um, existing companies try and absorb it and they use it to automate the stuff they're already doing.
[00:08:24] And then over time you get new stuff, you unbundle based the income, but it's intake and you [00:08:30] unbundle existing companies because of something that's possible, because of this new technology. So you can always kind of jump into the new thing. And sometimes the new thing kind of really is just a feature and sometimes it's, now it's a fundamental change in how everything works.
[00:08:42]
[00:08:44] Kiri Masters: Today, [00:08:45] retailers are treating AI, at least from a consumer standpoint as a feature. They're adding chat bots to their existing websites. They're improving search interfaces, they're making recommendations smarter
[00:08:59] [00:09:00] but all of this assumes that the current behavior will persist, that consumers will still come to your website and that we'll just help them to find things better. But AI platforms and the way that consumers are [00:09:15] using them aren't constrained by that assumption. We're starting to see entirely new shopping experiences where discovery comparison and.
[00:09:25] nascently purchasing happen [00:09:30] without ever having visited a retailer's website. AI shopping agents and LLM powered product search represent genuine unbundling of the traditional retail journey.
[00:09:42] I've talked a little bit about onsite retail media [00:09:45] being at risk, but offsite retail media faces po possibly an even greater risk, and that deserves its own analysis, which I'm working on
[00:09:54] The core point is this, when your core value proposition is exclusive [00:10:00] access to closed loop purchase data. And now the LLM start observing both intent and possibly conversion across multiple retailers. That data exclusivity dissolves quickly. [00:10:15] More to come on that topic soon. And finally, the window is closing.
[00:10:20] This is what makes platform transitions so dangerous for incumbents.
[00:10:26] So this is the mechanism of change. Consumers [00:10:30] reconsider their default behaviors and potentially multiple default behaviors at a time. This consumer confusion creates a brief window of opportunity. Retailers have limited time to better engage consumers [00:10:45] onsite, such as with truly smart and differentiated onsite AI assistance and personalized, genuinely helpful experiences. Before external agents [00:11:00] capture that habit, share example, if Amazon's Rufus becomes the default way that consumers shop on Amazon, Amazon's onsite and offsite revenue streams stay relatively safe, but if chat [00:11:15] GBT becomes the default way consumers start shopping journeys, both of those revenue streams face existential pressure.
[00:11:23] Lots of retailers are slapping on features to their existing businesses, but AI platforms are [00:11:30] building an entirely new commerce pathway. So the big question that retail media network should be asking is what percentage of your current p and l depends on behaviors that could move [00:11:45] to LLM environments?
[00:11:47] Retailers have a short window to build insur AI habits that preserve attention and the data advantage that they currently have. Which is essential for the longevity of their retail [00:12:00] media businesses.
[00:12:01]