Latest / Retail Media Breakfast Club / Loyalty Programs To Give Retailers An Edge In AI Shopping Future?
Transcript
- [Weds Sep 3] Loyalty Programs in the AI Shopping Era === [00:00:00] Did you know that the average US consumer belongs to 17 loyalty programs? 17. Personally, I'm probably above average between airline miles, hotel points, grocery store cards, and [00:00:15] every retailer that's ever convinced me to hand over my email. At checkout, most of them honestly gather digital dust while I fumble for my phone number at checkout, hoping I'll remember enough digits to unlock whatever poultry discount awaits me.[00:00:30] [00:00:30] But what if AI agents could actually make these programs useful? In my recent deep dive into how AI agents will disrupt retail media, I argued that loyalty programs could become retailers last moat when [00:00:45] traditional advertising gets bypassed. My thesis was that when chat GBT builds your shopping basket instead of you browsing Amazon loyalty status becomes one of the few ways retailers can influence those purchasing decisions. [00:00:59] But theory [00:01:00] is one thing, reality is another. So I reached out to someone who's actually built loyalty programs at scale. Stephanie Melt Apol, who is a veteran loyalty expert with over two decades as an executive at Inspire [00:01:15] Brands Duncan BJ's Wholesale Club, and most recently as EVP of Global Loyalty at MasterCard. [00:01:21] Stephanie has launched a awesome new newsletter called So Many Points For Loyalty and CRM marketers definitely recommend [00:01:30] checking out if you're interested in that space. ~But I spoke with Stephanie about what,~ [00:01:32] ~but today I'm going to share some of Stephanie's. But today I'm gonna share some of Stephanie's ideas and POVs about how this may all shake out in the future.~ [00:01:32] But today I'm gonna share a few of Stephanie's POVs about how loyalty programs could play out in an agentic shopping future. [00:01:39] [00:01:40] So the first point Stephanie made is that AI could turn program overload [00:01:45] into strategic advantage. So this comes back to that average of 17 loyalty programs per US consumer. You know that you have all of these loyalty programs that you're a part of, maybe with your bank, with Chase, with amex, with [00:02:00] hotels and airlines and retailers. [00:02:02] But [00:02:03] a lot of consumers don't feel that they're making the most of those programs. [00:02:08] Stephanie says that AI can help consumers ensure that they're getting the best value out of the programs and not redeeming points or cashback for the [00:02:15] wrong things. [00:02:16] For consumers drowning in program complexity, that's going to be genuinely helpful. But for retailers, it creates a new dynamic. They need to create programs that play well with agents so that they get used more [00:02:30] because those that don't will get forgotten in the digital pile. The advantage here is that with a better user experience, loyalty programs in general might become more attractive. [00:02:41] Personally, when I'm asked to sign up for a retailer's loyalty program at [00:02:45] checkout, I often decline because of the hassle of first signing up. Then getting the resulting barrage of emails and texts. I'm not even sure I'm going to use that program again, but if I know that my agent is able to tap into all of these programs and help me in the [00:03:00] future, maybe I would sign up for more loyalty programs. [00:03:03] Let's put the future on pause for a moment, because Stephanie points out that even today, loyalty benefits aren't shown in product searches. She points out, if you search for a branded term [00:03:15] like Veronica Beard Pants on Google Shopping, you'll see results from the Veronica Beard website, plus retailers like Nordstrom and Bloomingdale's. [00:03:24] But while you see the price that you get from those different retailers, you don't see the loyalty [00:03:30] points that you'd earn the tier multipliers or whether you're close to unlocking free shipping. It's price and price only. And so Stephanie says this is a huge opportunity and one that might come more to life with agentic shopping. [00:03:44] To [00:03:45] close this gap. [00:03:46] Now there is at least one company out there that's looking to address this gap. It's called Wildfire Systems, and they just announced the first solution enabling consumers to earn cash back from AI assisted shopping. And how it works [00:04:00] is as a browser extension ~that detects when~ [00:04:01] ~it's currently a browser extension that surfaces an. ~That surfaces available, cash back and rewards in real time. It's early days, but it shows at least one company that's building the plumbing for loyalty aware agents. [00:04:11] Stephanie also explained an important distinction that shifted my [00:04:15] thinking. There's a big difference between earning loyalty points and redeeming them through AI agents. Here's what she said. I think the earn side of loyalty is easier via an agent than the burn side, and that's because agents can [00:04:30] easily route purchases to maximize points or automatically enroll you in programs. [00:04:35] But redemption might actually be trickier. She says, if you're sitting on a thousand alter points. You need to go to alta.com to redeem them through their [00:04:45] process. There's pretty complex redemption logic involved here. Tier based valuations, promotional multipliers, and these are the things that make loyalty programs profitable for retailers, but may not easily translate to [00:05:00] agent interfaces. [00:05:01] Stephanie says that at least in its current format, chat, GBT still gets many details wrong about existing loyalty programs, and this creates an interesting dynamic. Agents might excel at [00:05:15] helping consumers accumulate points across programs, but retailers. For now might retain control over the very valuable redemption experience, and that could be a great thing because it helps to keep the direct relationship alive, even in [00:05:30] an agent mediated world. Acosta group's, retailer intimacy is legendary. Merchants answer their calls. You just can't [00:05:45] find that access at the same scale with any other partner out there. [00:05:50] That expertise with both retailers and Shoppers fuels its Connected Commerce team, which offers digital shelf retail, media, and data analytics [00:06:00] all under one roof. Tap into a hundred years of retailer relationships and award-winning digital commerce capabilities. Learn more at ACOA Group and tell them Retail Media Breakfast Club sent you.[00:06:15] [00:06:15] That's A-C-O-S-T group. [00:06:20] Something I was pondering also is how retailers can compete when there's what we would call in economics, perfect competition. That's [00:06:30] where buyers and sellers are so numerous and well-informed that all elements of monopoly are absent and the market price of a good or service is beyond the control of individual buyers and sellers. [00:06:43] In other words, what does [00:06:45] it look like when our AI agents can essentially do infinite price comparisons and program comparisons to find the best deal? Is it just gonna be a race to the bottom? Well, it turns out loyalty is not that simple or [00:07:00] rational. Here's what Stephanie told me. [00:07:02] Loyalty isn't just points. As points have been devalued over the years, consumers have leaned into other types of benefits, such as access, like the early shopping hours at Costco, lounge [00:07:15] passes at airports, and in-store events, status upgrades, even physical products. Those samples that you get at Sephora on your birthday, for example. [00:07:25] This shift becomes crucial in an agent driven world [00:07:30] when AI can instantly compare prices across every retailer and find the cheapest option. Pure price competition becomes a race to the bottom, but experiential benefits can't be easily commoditized or compared on a spreadsheet. [00:07:43] Think about this. An AI [00:07:45] agent can tell you that Target has the lowest price on laundry detergent, but it can't factor in on a purely numerical basis. The value of Sephora's early access to new launches, Costco's Generous Return Policy, or American Express's [00:08:00] Airport Lounge Access. [00:08:01] These benefits create genuine preference that persists even when agents are able to infinitely optimize for price. [00:08:08] But it's not all sunshine and rainbows for loyalty in the age of ai. Stephanie pointed to a growing problem [00:08:15] in loyalty, which is disloyalty benefits where brands give their best offers to their worst customers in order to win them back. She says, too many programs have been turned into discount or coupon machines. [00:08:28] The worst consumers are sometimes [00:08:30] getting the best offers so the brand can win them back or reengage them. Now, imagine agents. Systematically exploiting this loophole, an agent could theoretically game multiple retailer programs such as [00:08:45] letting accounts go dormant to trigger a win back offer, and then activate them strategically on behalf of their humans. [00:08:52] So what happens when AI optimization meets the perverse incentives that have been built into modern loyalty programs? [00:08:59] [00:09:00] Well, we've seen this actually play out in real life. Stephanie highlighted a couple of recent examples from Delta and Wendy's who both face criticism for suggesting dynamic pricing based on customer loyalty status with elite [00:09:15] members, worried they'd pay more precisely because of their loyalty. Both companies had to walk back these comments, but it shows just how careful retailers need to be with AI driven personalization. [00:09:27] In one of my earlier articles, I said that loyalty is [00:09:30] one of the last moats for retailers, and Stephanie pushed back on this. She said, I'm not sure they are. The last moat loyalty programs started out in the 1930s where consumers got stamps for buying that they could then cash in for free product. [00:09:44] Then those [00:09:45] programs moved to ID cards. Then everything went digital, then via the app, and eventually it'll be infused with agents. Loyalty just keeps evolving. [00:09:55] The point is that loyalty programs have survived every major commerce shift by adapting, [00:10:00] not by standing still, [00:10:02] so when we think about the agentic shopping pathways. Of the future, the retailers and brands that win won't be those that hold onto these purposefully opaque points and discount models hoping [00:10:15] to just hold out against the AI disruption. The ones who are successful will be rebuilding their programs as preference engines that agents can actually read and act on. [00:10:27] But that evolution requires strategy, [00:10:30] not just hope. So coming up on the podcast, I'm gonna dig into the specific moves that retailers and brands can make [00:10:38] to tap into the world of loyalty programs to appeal to both humans and their AI [00:10:45] shopping co-pilots. [00:10:46] And be sure to check out Stephanie's new newsletter. So many points. I'll link up to it in the show notes. Catch you next time. [00:10:53] [00:10:55]