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What it now takes for a shopper to switch brands, using AI
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[00:00:00] Kiri Masters: Most shoppers are now using AI tools to shop, and they're increasingly discovering new brands and products inside a chat window, which raises a practical question for anyone buying or selling commerce [00:00:15] media. What does it actually take to get a shopper to switch to a brand they've never heard of on an AI's recommendation?
[00:00:25] That is the very question that I partnered with [00:00:30] Bazaarvoice on to answer in their latest consumer study
[00:00:33] called What Is a Brand Worth When AI Does the Shopping? And this is the concern that I kept hearing from brands that have spent decades building trust [00:00:45] that AI assistants would kick off some kind of race to the bottom
[00:00:49] recommending dupes and swaps that shoppers would accept without thinking about. Perfect information that leads to [00:01:00] unflattering comparisons. Perfect competition flattening decades of brand architecture into just specs and prices. But what we found in this consumer study is that [00:01:15] switching is expensive, and price is the least effective way to pay for it
[00:01:21] In this episode, I'm gonna cover some of the highlights from this research that I collaborated on with Bazaarvoice, but I really do recommend checking out the [00:01:30] full research study, which is live today at 7:00 AM Eastern Time. I'll link up to that research in the show notes.
[00:01:39] Let's jump in.
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[00:01:41] Kiri Masters: So I'm gonna start with the reassuring part. Only [00:01:45] 4% of shoppers in our study would switch to a highly rated dupe of their usual product if they got a 10% discount. we looked at sort of the price sensitivity or discount sensitivity [00:02:00] of consumers
[00:02:01] To see at what point they would cave in and accept a discount for switching over to a dupe and across different product categories as well. But just a couple of highlights here. It takes a [00:02:15] 50% off discount to move the largest group of consumers away from their usual product towards a dupe, and 57% of respondents said
[00:02:25] A dupe has to be at least half the price before they would consider it
[00:02:29] [00:02:30] 15% of respondents said they wouldn't switch at any discount. And this same pattern turns up everywhere where we asked about price in this study. When AI puts several options in front of a shopper, only [00:02:45] 11% click the cheapest.
[00:02:47] And when it comes to deciding where to buy, only 12% go wherever AI says the price is lowest
[00:02:55] Now it's worth being precise about why this race to the bottom fear was shaky to [00:03:00] begin with. Perfect information collapses prices only for genuinely identical goods. For everything else, where there is some difference, it does something different. It makes it harder [00:03:15] to charge for a premium that isn't earned
[00:03:18] And easier to get paid for a difference that you actually have. So AI shopping is a threat to unearned brand premiums rather than just [00:03:30] to national brands
[00:03:32] Now, beauty is the category most exposed to dupes, and even there, a cheaper lookalike fails to win by default. We get into some of this cross-category analysis in the [00:03:45] report. And just sharing a quote from Ajay Patel, who is the SVP of Global Growth at U Beauty, which is certainly a premium beauty brand. He says, "Beauty is about the most dupe-saturated category there [00:04:00] is, so it's reassuring that its cheaper lookalike doesn't win by default.
[00:04:04] It's also a challenge to us. The premium we charge at U Beauty has to be backed by a real, provable performance difference. When it is, shoppers will pay [00:04:15] to stay."
[00:04:15] So another finding that I wanna highlight here is that familiarity holds the door. So if price isn't doing the work, what is? When an AI tool puts several products in front of a shopper, sixty-five [00:04:30] percent click the brand they already know and trust. Twenty-four percent click whatever the AI has labeled its best match, and just eleven percent click through on price [00:04:45] alone.
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[00:05:49] Now, how much it costs depends on your category. Familiarity wins the first click in every category that we looked at, but by different margins. [00:06:00] 69% in beauty and personal care, that's where it matters the most, down to 56% of consumers choosing f- a familiar brand in the DIY and home improvement category.
[00:06:14] And my [00:06:15] reading here that I included in the report is that there is a, a kind of a risk-reward gradient here. The question that a shopper is really asking ranges from something innocuous like, "Will these headphones last me [00:06:30] more than a month?"
[00:06:31] to, "Are these children's pajamas fire-resistant?"
[00:06:35] And as we can see, 38% of consumers say they're comfortable buying an unknown brand only in a low-risk category. [00:06:45] 17% are never comfortable with it.
[00:06:47] And we reached out to get the perspective from a few brands across different categories for this report. We also heard from Kim McDermott, who is the senior brand manager at Egg Life Foods, and she says that brand [00:07:00] loyalty is heavily dictated by category risk reward. In low-ticket categories like food and beverage, price elasticity can more easily trump equity because the risk is minimal.
[00:07:11] If a consumer tries an unfamiliar brand and doesn't like it, [00:07:15] they can switch back on the next shopping trip. This doesn't hold as true for high-ticket purchases like appliances or electronics, where consumers demand far more proof before purchase
[00:07:26] So if a challenger brand can't discount its way in, [00:07:30] what does work? Well, one is multi-format validation. 76% of shoppers want reviews with photo or video before buying an unfamiliar brand that an AI has [00:07:45] recommended. 75% want written reviews. Now, brand-supplied claims about features and benefits are the raw input, still super important, but reviews and other content from real customers [00:08:00] are what makes those claims credible enough for a shopper to actually act on and legible to the models reading on the shopper's behalf
[00:08:10] Now, one final point I wanna make here. This wasn't a major focus of the report, [00:08:15] but interesting to note that the categories where it's cheapest to dislodge an incumbent, as in food and beverage, DIY, baby and kids, these are precisely the categories where retailers push their own brands, their private label [00:08:30] brands, the hardest.
[00:08:31] It's worth noting that private label is really the largest organized dupe operation in retail, and this research puts a rough price on entry about half off, which means that [00:08:45] retailers are running this playbook that the challenger brands also need to operate
[00:08:50] against the same national brands that they sell to. Now, this isn't a new tension. It's been there for decades. But AI-assisted shopping [00:09:00] makes it easier to see because it puts incumbent and challenger brands side by side in one list, stripped of shelf position and packaging
[00:09:11] For brands, the practical work is making sure the proof [00:09:15] that shoppers go looking for is actually findable by them and the models. And for retailers too, I mentioned the data point that when it comes to deciding where to buy, only 12% go wherever AI says the price is [00:09:30] lowest. This is something that I try to convey to retailers all the time is we shop at different retailers for different missions for different reasons.
[00:09:40] It can be the most convenient option because it's on my [00:09:45] way home from soccer practice. It could be the lowest price option. It could be the place where all my favorite brands are sold. It could be the place where I get the best service. There are so many dimensions that retailers can compete on, [00:10:00] and this was a really reassuring piece of the research that even when a consumer understands where the price is cheapest for an item that they're looking to buy, they don't necessarily always gravitate to that immediately Brand [00:10:15] trust still extends to retailer channels as well.
[00:10:18] So that's it from my highlights. I have a couple of pieces out today, another one at my column at The Drum talking about this research and what we learned about trust [00:10:30] in advertising in these AI chat assistants
[00:10:34] And what that means for retail media. Definitely check out the full report. Again, I'll link up to it in the show notes. You'll be seeing some highlights from me in the coming weeks on this. Thanks for [00:10:45] listening, and I'll catch you tomorrow
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