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I’m a lot more interested in what I think is a much bigger disruptive change, which are entirely new consumer behaviors because of AI.

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Um, and so when I’m talking about the disruption, I’m not talking about, uh, being able to make your, your email marketing more efficient.

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I’m talking about people that discover products and buy them in new ways that they didn’t a year ago.

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Welcome to the Retailgenic Podcast, where we explore the intersection of retail, e-commerce, and AI agents, which we call Retailgenic.

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Our mission is simple, we are shining a bright light on the new agentic AI shopping mega-trend which will disrupt the trillion dollar digital retail market.

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The stakes are high.

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Google, OpenAI, Microsoft, Perplexity, Amazon, Apple, Meta, and Anthropic are all fighting to be the consumer AI shopping agent winner.

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There are gonna be some tough decisions for online brands and retailers to make.

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What happens to checkout?

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How should payments work?

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Should you continue to invest in retail media networks?

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What does the world look like when over half of your traffic is not from humans, but from AI agents?

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These existential questions are the tip of the iceberg.

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On this podcast, we’re talking to industry experts, analysts, and influencers to get answers to these questions, identify trends and best practices.

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Uh, this is Retailgenic, your podcast partner in navigating our AI shopping agent future.

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And now here’s your host, Scott Wingoooo!

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Welcome to the Retailgenic podcast.

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Today, we have something different, but hopefully fun for you.

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As you know, the NRF Big Show 2026 just wrapped up earlier this week on Tuesday.

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The last keynote of the entire conference was my good friend and podcast partner, Jason Goldberg, AKA Retail Geek.

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Also, he is the chief commerce strategy officer of Publicis.

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Uh, last year, Jason and I celebrated 10 years of podcasting together, and it’s been a wonderful partnership.

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Each episode, I learn a ton from Jason about some nuance about, um, consumers, retail, digital tags, payments.

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He knows a million things about a bazillion things.

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That being said, as I was watching this keynote and reflecting back on those last 10 years, I came to the conclusion that what I’ve really learned the most from Jason is how to be a better storyteller.

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That’s Jason’s superpower.

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He is a great storyteller of retail stories specifically, which obviously is great for what he does, and this keynote is a really good example of that.

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He’s so good at this superpower that he is always jetting around the world delivering keynotes at digital retail events, uh, and with Publicis top clients.

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He always mentions Walmart, but they have many others.

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The title of this keynote is Commerce Disrupted: Rise of the AI-Native Consumer, which is also near and dear to my heart.

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So for this episode, we did an experiment, and what we’re trying to do is put you in the audience.

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Maybe you couldn’t make it to the keynote, maybe you’ve never been to an NRF before.

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So what we wanted you to do is feel like you were there.

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If you watch the video, you’ll get the full immersive experience.

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Uh, you can see the size of the room, the A/V setup, uh, how Jason moves around the stage, how he gesticulates, all those good things if you’re really into this speaking, storytelling thing like, like I am.

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Um, if you’re on the audio, that’s great as well.

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Um, the, the presentation is definitely worth looking at while you go through this or afterwards.

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We are including that on the Retailgenic Substack.

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I’ll also post that on LinkedIn for you.

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Um, I hope you enjoy this as much as I did.

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It’s a really good story, uh, and it raises some interesting questions about what’s gonna happen with agentic commerce and the future.

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And now, without further delay, Jason Goldberg, Retail Disrupted: The Rise of the AI-Native Consumer.

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Ladies and gentlemen, please welcome to the stage chief commerce Strategy Officer of Publicis Groupe, Jason “Retail Geek” Goldberg.

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Oh,

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Bet you think that she is so cool.

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couch

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Oh my god.

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Retail is the greatest industry in the world, and I am in front of the best-looking, smartest, most diligent people in all of retail.

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It’s the very end of the show, and you guys are still here, hungry for more content.

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This is amazing.

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Or, my podcast co-host, Scott, hired a bunch of seat fillers.

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Uh, so give yourself a hand for still being here and still learning at the end of the show.

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Come on, guys, you totally deserve it.

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Yeah, and if you could indulge me for one extra second, did everyone have an amazing show?

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Yeah?

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Yeah?

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Like, we had lots of good conversations and learned a lot?

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Uh, that is because the NRF staff has been working crazy for months to get ready for this show, and they’ve been working nonstop since they’ve been here.

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So if you could do me one favor and give a hand for Matt, and Jill, and Paul, and Eric, and all the folks that have been working hard to make this a good show for us.

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Thank you, guys, very much.

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Yeah.

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Uh, so I’m gonna jump right into it.

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We’re gonna be talking about the disruption of AI, so no, no spoilers there.

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Uh, and in the highly unlikely event that anyone in this room doesn’t get enough of me in the next

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4 hours, I think I have.

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4 hours, uh, I have great news.

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Uh, I have a much smarter friend, Scott Wingo.

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He and I accidentally started a podcast at this show l- like, over 10 years ago before podcasting was cool, and there are now, like, 400 hours of us on the interweb talking about this stuff.

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So, so y- uh, Scott’s parents very helpfully spelled his name wrong with only one T, uh, so it’s super easy to find, uh, in the search engines.

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And you’re, you’re welcome to tune in and join us for this discussion.

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Um, but as I said, we’re gonna be talking about this giant thing we’re living through right now, agentic commerce disruption.

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And this is gonna be a participatory session.

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You guys are gonna have to help me.

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We’re gonna answer a couple of big questions that have been on everyone’s mind, uh, while we’re here.

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So, we’re gonna- we’re gonna get an amazing outcome, but I have to kind of set the table.

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So, one of the big questions is, how big a deal is agentic commerce, right?

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And so I wanted to kind of very quickly share 2 perspectives.

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Uh, if you were here on Sunday, uh, you saw Sundar on stage, and he, he famously is very bullish on AI, not surprisingly.

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You know, he’s like, “I don’t know, maybe as big as electricity or fire.”

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Um, and the, the former, uh, uh

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or one of

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uh, at Amazon, they also, of course, are very bullish on this.

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You know, th- this is probably the biggest innovation since the invention of the internet, which was quite relevant to most of us in this room.

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Um, and somewhat humorously, another great, uh, technologist, Bill Gates, said, “Yeah, it’s gonna be so big that you’re probably not gonna go back to Amazon again when it happens,” which I’m not sure Andy appreciated that quote.

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Um, but so there’s a lot of luminaries in our industry that think that this is a huge, transformative deal that we all have to immediately get ready for.

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But not everyone agrees with them.

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Uh, if you hang out in the weird corners of LinkedIn that I hang out in, uh, there’s a bunch of smart people that are dubious, right?

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So, I have a good friend, Andrew Lipson.

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He’s, he’s a great analyst.

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He’s one of the, the pioneers in writing about retail media, uh, and he’s a great voice in our industry.

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Uh, a couple months ago, he wrote an article called, “Agentic commerce is one giant hallucination.”

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No one’s ever buying anything from the robot.

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No one’s ever gonna trust the robot, right?

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Um, and another dear friend of mine, Sucharita, uh, Kudai, from, from Forrester, uh, she had a slightly more balanced take, but she’s like, “Hey, it might be a thing, but it’s a small thing.”

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Like, less than 2% of, of, uh, all the questions on, on, uh, ChatGPT, for example, are related to commerce.

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Um, so she thinks it’s overblown, right?

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Uh, so one of the first things I wanna do is gauge the audience before we get going too far in how big a deal you think it is.

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So, we’re gonna do a survey.

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Now, I wanna quickly warm everyone up for the survey.

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Uh, get out your phone.

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If you’re playing Angry Birds, I’m sorry, you got to abandon your map.

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Um, and scan this QR code.

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This is the practice session before, before we jump into the actual survey.

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Scan this QR code right here.

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And it’s gonna take you to a survey, and the correct answer to this survey is, “Five stars, he was amazing.”

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So, if everyone could just fill out, “Five stars, he was amazing.”

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You can paraphrase if you choose.

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Um, that, that would be awesome.

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Uh, and so now that you’re all warmed up, now that y’all have your phones out, now that you all know how to scan a QR code, we’re gonna go to the Slido survey, which is, “How big a deal is agentic commerce?”

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Is it Andrew Lipson, total hallucination?

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Is it Sucharita, real but overhyped?

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Is it, uh, sort of somewhere in between?

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Uh, it’s the latest in a long line of disruptions, like social and mobile?

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Um, or is it the, the most important thing that’s, that’s ever happened to us, right?

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Um, yeah.

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And so you can see there’s some, some controversy in the room.

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Like, there’s, there’s very few Andrew Lipsons, but the other 3 are pretty close.

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It’s pretty, pretty neck and neck, which is interesting.

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Um, I’m gonna share some facts with you, and then we’re gonna see if you still feel the same at the end.

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Uh, but I do have one more question.

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If it is a big deal, if it does become a meaningful part of commerce, the next magic question is, who’s gonna win?

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Is it the giant incumbents with the huge booths that you’ve seen downstairs that have already been winning that are gonna have an intrinsic advantage?

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Or, is it all the cool new innovative companies in the startup pavilion?

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Uh, Scott has said on our podcast a few times that if your company was born before agentic commerce was invented, you’re probably not gonna win at, uh, agentic commerce.

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So, so he would certainly be betting on the new challengers.

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Uh, but there’s some reason to believe that there’s some, some resource advantages, uh, for the incumbents.

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So, it seems like we’re split about 60/40 in that room.

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Okay.

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So, one more thing I have to do before we get into it.

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I intentionally asked you those questions without defining agentic commerce.

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Um, but I really think definitions are important.

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I think it’s kind of boring and geeky to talk about definitions, but I find when a lot of us are debating these things, we’re using the same words, but we have wildly different meanings.

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So, I just wanna kind of ground everyone for the purposes of this presentation.

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The first thing is, there’s this really annoying, uh, I wanna call it a word, but I think it’s an acronym, uh, AI, artificial intelligence.

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Um, and if you haven’t noticed, every single exhibitor at NRF is an AI company.

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It’s in every single company’s name.

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And, like, in the 4 words they had to dedicate to the sign on their booth, 3 of them were AI, I’m pretty sure.

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Uh, I, I bought a hot dog from the AI hot dog vendor on the booth today.

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Um, and that’s potentially true, because AI is incredibly broad.

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It’s a tool that can impact almost anything, right?

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And so, there’s a ton of things retailers have been doing since the beginning of time that AI can absolutely make more efficient, that AI can make better, right?

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And so, I, I call that whole genre of AI the efficiencies genre.

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And if you wanna make money today with AI, that’s probably where you should play.

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Like, there’s lots of improvements to supply chain, and staffing, um, and order management, and, uh, uh, product merchandising, uh, that efficiencies can dramatically help.

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So, I’m not trying to pooh-pooh efficiencies.

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I’m just trying to say that’s not what I’m talking about.

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I’m a lot more interested in what I think is a much bigger disruptive change, which are entirely new consumer behaviors because of AI.

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Um, and so when I’m talking about the disruption, I’m not talking about, uh, being able to make your, your email marketing more efficient.

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I’m talking about people that discover products and buy them in new ways that they didn’t a year ago.

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Uh, so that’s, that’s my definition of agentic commerce.

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And then, I have to address one other part of this.

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And this is a huge debate, uh, on, on LinkedIn right now.

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Um, as soon as you start arguing with someone about how big agentic commerce is, one of the first questions that comes up is, “Well, are you talking about how many times the robot takes the credit card?

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Or are you talking about how many times the robot influences a purchase decision,” right?

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And we’ve been arguing about this since the beginning of e-commerce.

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Like, is, is e-commerce only the orders I take on my website?

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Or is it all of those sales that get generated after you use Google Maps, and read ratings and reviews, and do all this digital product research, and then you walk into a Target and buy the product?

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Is that digital commerce, right?

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And then as social commerce came up, we had those arguments again.

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Is social commerce just TikTok Shop?

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Or is it all the products that did, get discovered on TikTok?

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And we’re having that same argument again.

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Is agentic commerce all the orders that the robot takes and collects the money for?

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Or, is it all of the new purchases that wouldn’t have happened had it not been for the robot, right?

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And I strongly believe that you’re far more prudent to think about the whole iceberg, not just that part of the iceberg that’s above the surface.

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So, those are my 2 definitions.

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Agentic commerce is new customer behaviors, not the efficiencies, and it’s the whole pool of new purchase behaviors that get influenced as a result, right?

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So, you remember that first question I asked is, “Who wins?

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Incumbents or challengers?”

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And I have some bad news for you.

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Historically, this level of disruption is not awesome for incumbents, right?

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Did anyone see a dinosaur on their way to work today?

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Yeah, probably not.

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I wanna tell you, uh, what I think is a more illustrative story.

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I wanna tell you about, uh, one of my marketing heroes, uh, this gentleman, Frederic Tudor.

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And I, I wouldn’t expect too many of you to be familiar with him.

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Uh, he lived in the early 1800s.

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He actually got out of debtor’s prison at the age of 18, uh, in about 1804.

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And he had a new business venture in mind.

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He’s much like Scott.

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He’s just serial entrepreneur.

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Um, so, so Frederic Tudor grew up on a farm in, uh, New England, I wanna say, the Tudor Pond.

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It was a pond in the backyard of his, his family’s farm.

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And he had this idea that there are all these new rich expats living in the Caribbean, and he imagined that they would really enjoy a cold beverage if only there was cold in the Caribbean, which in 1800, there was not.

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So, he had a revolutionary idea.

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“I’m gonna carve out the ice from my family farm.

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I’m gonna put it on a boat and ship it to the Bahamas.”And just you know, about half the ice melts on the way from New England, uh, to the Bahamas.

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But some of that ice did arrive in the Bahamas, and Frederic Tudor invented free samples.

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00:16:21,915.9999999998836 –> 00:16:34,276.0000000001164
He gave free ice to every bar in the Bahamas and said, “Serve a cold drink to your customers, and I’ll bet you they come back for more, and you can buy that ice from the Tudor Ice Company.”

190
00:16:34,276.0000000001164 –> 00:16:36,456
And that turned out to be a good idea.

191
00:16:36,456 –> 00:16:45,175.99999999988358
By about 1840, Frederic Tudor was w- worth $200 1000000, which is billions of dollars in today’s currency.

192
00:16:45,175.99999999988358 –> 00:16:59,146
Uh, and he was literally delivering 90,000 tons of ice a year to India for the, the OG retail conglomerate, the Bombay Trading Company, to drink cold beverages in India.

193
00:16:59,146 –> 00:17:02,236
And it spawned a whole industry, ice harvesters.

194
00:17:02,236 –> 00:17:08,096
A ton of it got harvested right here in New York, uh, and it was the largest industry in the world.

195
00:17:08,096 –> 00:17:10,996.0000000001164
The Norwegians are apparently are very good at ice.

196
00:17:10,996.0000000001164 –> 00:17:14,336
Um, is anyone familiar with Tudor Ice today?

197
00:17:14,336 –> 00:17:15,956.0000000001164
Anyone buy any Tudor Ice?

198
00:17:15,956.0000000001164 –> 00:17:17,226.00000000011642
No Tudor Ice customers.

199
00:17:17,226.00000000011642 –> 00:17:18,656
Do you know why?

200
00:17:18,656 –> 00:17:27,195.99999999988358
Because what Tudor and none of his competitors foresaw is the invention of artificial ice.

201
00:17:27,195.99999999988358 –> 00:17:29,916
Do you know what, do you know what artificial ice is?

202
00:17:29,916 –> 00:17:34,036
Artificial ice is ice made in a factory, all right?

203
00:17:34,036 –> 00:17:44,096
And the American Ice Company started making ice in bulk, and it could make ice in the Bahamas so you didn’t have to put it in the boat, you didn’t have to mail it, uh, uh, uh, sail it to, to India.

204
00:17:44,096 –> 00:17:45,656
It was much more efficient.

205
00:17:45,656 –> 00:17:49,336
And the American Ice Company completely put Tudor Ice out of business.

206
00:17:49,336 –> 00:17:56,796
Uh, by, by, uh, 1914, 85% of the homes in America got regular ice deliveries.

207
00:17:56,796 –> 00:18:02,476
You had a cooler, an ice man came to your house, put ice in it, and that’s how you kept things cold.

208
00:18:02,476 –> 00:18:05,596
Y’all familiar with the American Ice Company?

209
00:18:05,596 –> 00:18:06,956.0000000002328
Yeah, you know why?

210
00:18:06,956.0000000002328 –> 00:18:15,276
Because none of the huge ice factories foresaw that we could make ice in our kitchens, right?

211
00:18:15,276 –> 00:18:16,976
And so here’s the lesson.

212
00:18:16,976 –> 00:18:29,176
None of the ice harvesters, the largest company in the worl- uh, industry in the world became ice factories, and none of the ice factories became ice, home ice makers.

213
00:18:29,176 –> 00:18:31,016
And I’m gonna predict the future for you.

214
00:18:31,016 –> 00:18:33,275.99999999976717
I’m gonna tell you what the next big innovation in ice is.

215
00:18:33,275.99999999976717 –> 00:18:34,576
You know what it is?

216
00:18:34,576 –> 00:18:36,456.00000000023283
It’s, it’s the nugget ice.

217
00:18:36,456.00000000023283 –> 00:18:38,076
Y’all familiar with nugget ice?

218
00:18:38,076 –> 00:18:48,235.99999999976717
Uh, if you, uh, ever went to Sonic, they had this delicious, chewy, aerated ice, and people literally drive through Sonic, don’t get a hamburger, but just buy bags of ice.

219
00:18:48,235.99999999976717 –> 00:18:55,976
And you know it’s a big deal because my, my most beloved brand, Starbucks, now serves nugget ice in, in all the Starbucks.

220
00:18:55,976 –> 00:19:03,436.00000000023283
And so magic question for you, are all those home ice makers gonna be the ones to invent the nugget ice machines, right?

221
00:19:03,436.00000000023283 –> 00:19:11,235.99999999976717
So that is sort of a cautionary tale for the incumbents in this room about what could happen because of digital commerce.

222
00:19:11,235.99999999976717 –> 00:19:14,716
Um, but there’s also evidence on the other side of this.

223
00:19:14,716 –> 00:19:18,336
If you don’t know, you deserve an incredible amount of credit.

224
00:19:18,336 –> 00:19:23,376
Last year in the United States of America, we sold $5.3 trillion worth of stuff.

225
00:19:23,376 –> 00:19:25,476
That’s a lot of stuff, right?

226
00:19:25,476 –> 00:19:29,436.00000000023283
Um, that’s about 3 1/2%, 3.6% growth.

227
00:19:29,436.00000000023283 –> 00:19:32,476
3.6% growth is about our 10-year average.

228
00:19:32,476 –> 00:19:40,476
We grow between 3.5 and 4% a year for the last 10 years, so 3.6 is right in the, the sweet spot of that.

229
00:19:40,476 –> 00:19:43,916.0000000002328
Um, so we’re, it was kind of an average year.

230
00:19:43,916.0000000002328 –> 00:19:45,196
Here’s the thing.

231
00:19:45,196 –> 00:19:46,656
I don’t like talking about averages.

232
00:19:46,656 –> 00:19:47,728
Do you know why?

233
00:19:48,516 –> 00:19:51,824
On average, the country of Nepal is flat.

234
00:19:52,656 –> 00:19:57,516
There are exactly 25,000 feet up and 25,000 feet down.

235
00:19:57,516 –> 00:20:05,596
So if you talk about averages, you would miss the giant mountain in the middle of, of, uh, uh, Nepal called Everest, which is pretty important, right?

236
00:20:05,596 –> 00:20:16,466
So in the same way that 3.6% growth, that’s $183 billion of stuff you guys sold that we didn’t sell the year before.

237
00:20:16,466 –> 00:20:17,216
And that’s amazing.

238
00:20:17,216 –> 00:20:18,896
Like, you don’t get enough credit.

239
00:20:18,896 –> 00:20:21,596
But when you say, “Who got all those sales?

240
00:20:21,596 –> 00:20:23,896
Was it incumbents or challengers?”

241
00:20:23,896 –> 00:20:26,336
the story gets very different, right?

242
00:20:26,336 –> 00:20:28,420
Uh, this is not e-commerce.

243
00:20:28,420 –> 00:20:30,380
This is retail.

244
00:20:30,380 –> 00:20:34,014
Amazon got 31% of all that growth.

245
00:20:34,780 –> 00:20:39,520
Walmart got the next 14% of all that growth.

246
00:20:39,520 –> 00:20:42,400
The next company is my nemesis, Costco.

247
00:20:42,400 –> 00:20:45,260
Do you know, uh, hopefully, Costco’s not in the room.

248
00:20:45,260 –> 00:20:46,360
Uh, I should have asked.

249
00:20:46,360 –> 00:20:48,940
Uh, do you know why Costco is my nemesis?

250
00:20:48,940 –> 00:20:55,920
They are famously the retailer that most often does not take any of my advice and is wildly successful for doing so.

251
00:20:56,600 –> 00:20:58,220
So I’m, I’m a little bitter.

252
00:20:58,220 –> 00:21:01,780
Uh, but they, they alone represented 7% of all that growth.

253
00:21:01,780 –> 00:21:06,800
So 3 incumbents represented half of all the growth.

254
00:21:06,800 –> 00:21:15,360
The next biggest chunk is 3 challengers, 3 companies over the last 3 years that invented direct to consumer models from China.

255
00:21:15,360 –> 00:21:21,220
So if you don’t know, 3 years ago, Shein became the fastest growing retailer in the history of mankind.

256
00:21:21,220 –> 00:21:30,120
They didn’t get to keep that title very long because the next year, Temu launched a Super Bowl ad, and in one year, surpassed Shein in sales.

257
00:21:30,120 –> 00:21:36,960
Uh, and if that wasn’t impressive enough, last year, TikTok Shop sold $9 billion in their first year of business.

258
00:21:36,960 –> 00:21:45,760
Um, so these 3 companies that we don’t talk about enough here, uh, have, have revolutionized their industries and become some of the fastest growing companies.

259
00:21:45,760 –> 00:21:48,520
So we’ve got incumbents winning half the growth.

260
00:21:48,520 –> 00:21:50,990
We’ve got challengers winning a big chunk of the growth.

261
00:21:50,990 –> 00:21:59,800
And what that means is every other NRF member had to fight for 38% of that growth, right?

262
00:21:59,800 –> 00:22:03,260
So when you disaggregate this, it becomes an interesting story.

263
00:22:03,260 –> 00:22:06,520
There’s some incumbents that win, there’s some challengers that win.

264
00:22:06,520 –> 00:22:10,919
It’s the, uh, excuse me, the uncomfortable middle where you don’t wanna be.

265
00:22:10,919 –> 00:22:12,560
So, so how is th-

266
00:22:12,560 –> 00:22:13,600
What is this disruption?

267
00:22:13,600 –> 00:22:14,639.9999999997672
How is this disruption?

268
00:22:14,639.9999999997672 –> 00:22:16,500
I wanna try to make it real for you.

269
00:22:16,500 –> 00:22:20,400
Uh, I like to call it the disruption of discovery.

270
00:22:20,400 –> 00:22:21,360.00000000023283
Uh, I’ve been doing this a while.

271
00:22:21,360.00000000023283 –> 00:22:22,740
I’m a 4thgeneration retailer.

272
00:22:22,740 –> 00:22:25,420
I’ve been in the business for over 30 years.

273
00:22:25,420 –> 00:22:36,500
And for my entire life, the greatest source of leads in the history of retail is our beloved SIS, saw in store.

274
00:22:36,500 –> 00:22:48,200
I went to the store, uh, to get Oreos for my, my 10-year-old’s lunch, and he discovered the Coca-Cola-flavored Oreos and made us get them, which sidenote, is not my cup of tea.

275
00:22:48,200 –> 00:22:50,680
I don’t know if you’ve tried the Coke-flavored Oreos.

276
00:22:50,680 –> 00:22:58,180
Um, but the, uh, that discovered it in the store and decide to buy it is how retail has always worked.

277
00:22:58,180 –> 00:23:01,329
And our friends at Procter & Gamble literally invented a name for it.

278
00:23:01,329 –> 00:23:05,460
They call it the first moment of truth, and we invented a marketing discipline around it.

279
00:23:05,460 –> 00:23:13,060
We call it shopper marketing, and many of us in this room are the absolute black belt world champions in, in shopper marketing.

280
00:23:13,060 –> 00:23:15,600
Saw in store is how we launch new products.

281
00:23:15,600 –> 00:23:18,320
It’s how we invent new flavor profiles.

282
00:23:18,320 –> 00:23:21,720
Uh, it’s the most important marketing vehicle we have.

283
00:23:21,720 –> 00:23:23,620
Only one problem.

284
00:23:23,620 –> 00:23:25,660
It’s being disrupted, right?

285
00:23:25,660 –> 00:23:30,620
Some of you that know me know that I have an unhealthy relationship with caffeine.

286
00:23:30,620 –> 00:23:36,540
I don’t know if there were any, any clues about that when I came out on stage today.

287
00:23:36,540 –> 00:23:46,660
Um, but if you’re in my hometown, you, you would probably have some other evidence at any of the Starbucks in Chicago where I’m the customer of the month at all of them.

288
00:23:46,660 –> 00:23:53,780
Um, and if you had a chance to visit my refrigerator right before NRF, you might, you might see a familiar logo.

289
00:23:53,780 –> 00:24:00,720
So imagine the saw in store experience for Jason “Retail Geek” Goldberg buying coffee, right?

290
00:24:00,720 –> 00:24:02,100
I go into the Target.

291
00:24:02,100 –> 00:24:12,760
I have to walk by 38 other brands of coffee, all that have a chance to conquest me, to tell me about their new flavor fro- flavor profiles, to get me to try that Dunkin’.

292
00:24:12,760 –> 00:24:19,120
And if none of them succeed, I get to my beloved Starbucks section, and Starbucks gets to tell me all about their new flavor profiles.

293
00:24:19,120 –> 00:24:20,860.0000000002328
They get to expand my wallet.

294
00:24:20,860.0000000002328 –> 00:24:23,980
They get to, uh, extend their relationship with me.

295
00:24:23,980 –> 00:24:25,639.9999999997672
That is shopper marketing.

296
00:24:25,639.9999999997672 –> 00:24:27,280
That is saw in store.

297
00:24:27,280 –> 00:24:32,139.99999999976717
Does anyone in this room believe that that’s how I got coffee?

298
00:24:32,139.99999999976717 –> 00:24:33,280
No, right?

299
00:24:33,280 –> 00:24:34,680
How am I gonna get coffee?

300
00:24:34,680 –> 00:24:35,860.0000000002328
I’m gonna go to Target.

301
00:24:35,860.0000000002328 –> 00:24:43,910
I’m gonna type Starbucks into the search engine, and I’m gonna parachute right down to the giant kegs of coffee that I stock in my refrigerator.

302
00:24:43,910 –> 00:24:46,560
And nobody got a chance for serendipitous discovery.

303
00:24:46,560 –> 00:24:52,600
Nobody got a chance to introduce new flavor profiles unless you bought some retail media from Andrew Lipson, right?

304
00:24:52,600 –> 00:24:56,969
Few retail media spots, but I missed all that chance for serendipitous discovery.

305
00:24:56,969 –> 00:24:58,800
And I have a secret for you.

306
00:24:58,800 –> 00:25:01,520
This isn’t how people discover coffee anymore either.

307
00:25:01,520 –> 00:25:04,300
Do you know how people discover coffee today?

308
00:25:04,300 –> 00:25:06,360.00000000023283
The TikTok, right?

309
00:25:06,360.00000000023283 –> 00:25:09,800
This is a video that went viral on TikTok about two and a half years ago.

310
00:25:09,800 –> 00:25:13,180
A dude took this thing that we’ve all forgotten existed called instant coffee.

311
00:25:13,180 –> 00:25:15,380
Does anyone remember instant coffee?

312
00:25:15,380 –> 00:25:20,760
He puts it in a cup, sugar, hot water, emulsify it, pour it over ice.

313
00:25:20,760 –> 00:25:26,360.00000000023283
It’s a delicious caramelly, creamy sh- uh, caffeine delivery vehicle that he called whipped coffee.

314
00:25:26,360.00000000023283 –> 00:25:28,550
This video got seen 10 million times.

315
00:25:28,550 –> 00:25:33,380
A bunch of other talented creators made better versions that were s- seen tens of millions of times.

316
00:25:33,380 –> 00:25:39,010
And that week, I got a panicked call from one of my clients, Walmart.

317
00:25:39,010 –> 00:25:45,296
“Hey, Jason, we are sold out of instant coffee nationwide, and we have no idea why.”

318
00:25:46,240 –> 00:25:47,320
Right?

319
00:25:47,320 –> 00:25:49,660
And think about it.

320
00:25:49,660 –> 00:25:52,060
Walmart has the greatest supply chain in the history of mankind.

321
00:25:52,060 –> 00:25:54,100
They’re amazing at inventory.

322
00:25:54,100 –> 00:25:59,280
Can Walmart restock 4,700 stores with instant coffee in a week?

323
00:25:59,280 –> 00:26:03,527
No way, right?And did this trend last longer than a week?

324
00:26:03,527 –> 00:26:06,027
Did any of you have whipped coffee this morning?

325
00:26:06,027 –> 00:26:06,788
No.

326
00:26:06,788 –> 00:26:11,518
So by the time, uh, they were able to restock, this trend had come and gone.

327
00:26:11,518 –> 00:26:13,748
And that would be a tragedy.

328
00:26:13,748 –> 00:26:19,848
But the bigger tragedy is I’ve gotten a call like that from a retailer every week for the last two and a half years.

329
00:26:19,848 –> 00:26:22,328
Last month, it was my friends at Sam’s Club.

330
00:26:22,328 –> 00:26:33,288
Uh, an influencer went viral with their amazing, uh, flavored artificial crab legs, and I literally got a call, “Hey, we can’t get any more artificial crab legs.

331
00:26:33,288 –> 00:26:37,768
Do you think we could sell real crab legs and call them imitation crab legs?”

332
00:26:37,768 –> 00:26:40,828
Which I, I don’t think they were being serious, but they didn’t do that.

333
00:26:40,828 –> 00:26:48,206.99999999976717
Um, so these disruptions of, of social media being where people discover product on is a huge deal.

334
00:26:48,206.99999999976717 –> 00:26:52,542
I have another example that’s been on my mind a lot for reasons that’ll become apparent.

335
00:26:53,206.99999999976717 –> 00:26:55,668.0000000002328
This is the saw-in-store experience for sunscreen.

336
00:26:55,668.0000000002328 –> 00:26:58,448
Can anyone recognize the best sunscreen on this shelf?

337
00:26:59,087 –> 00:27:02,768
Yeah, unless you’re in the sunscreen industry, there’s no way, right?

338
00:27:02,768 –> 00:27:07,632
And if I opened all those sunscreens and squirted it into your hand, could you tell a good one from a bad one?

339
00:27:08,206.99999999976717 –> 00:27:09,408
Probably not.

340
00:27:09,408 –> 00:27:11,568
So how do we all pick sunscreen?

341
00:27:11,568 –> 00:27:12,868
I already told you the answer.

342
00:27:12,868 –> 00:27:14,648.0000000002328
The TikTok, right?

343
00:27:14,648.0000000002328 –> 00:27:31,168.00000000023283
Doctor, Dr. Shah, uh, on TikTok, uh, AKA Dr. Derm, uh, making videos and telling us that the most effective, best, uh, coverage sunscreen in the world are illegal, not FDA-approved sunscreens from South Korea.

344
00:27:31,168.00000000023283 –> 00:27:34,788
Um, and so, uh, what do people all try to get?

345
00:27:34,788 –> 00:27:36,508
South Korean sunscreens.

346
00:27:36,508 –> 00:27:39,928
Um, when I first met him, he had 20,000 followers on TikTok.

347
00:27:39,928 –> 00:27:43,768
Today, he’s got four million followers, and he did a Super Bowl ad.

348
00:27:43,768 –> 00:27:46,868
Um, so this is how people are discovering products.

349
00:27:46,868 –> 00:27:49,967
But increasingly, they’re using a new tool.

350
00:27:49,967 –> 00:27:51,498
They’re going to the robot.

351
00:27:51,498 –> 00:28:00,048
“Hey, ChatGPT, what’s the best sunscreen to buy for my 9yearold son to go on vacation to Hawaii?”

352
00:28:00,748 –> 00:28:01,608
Slight humble brag there.

353
00:28:01,608 –> 00:28:04,108
Does anyone get why I’m thinking about sunscreen now?

354
00:28:04,108 –> 00:28:04,947.9999999997672
Yeah.

355
00:28:04,947.9999999997672 –> 00:28:07,248
Um, and think about what the robot did.

356
00:28:07,248 –> 00:28:09,787
The robot didn’t get the 3 words I typed into Google.

357
00:28:09,787 –> 00:28:11,938
It gets 26 words on average.

358
00:28:11,938 –> 00:28:15,368
And the robot doesn’t answer just based on those 26 words.

359
00:28:15,368 –> 00:28:18,648.0000000002328
It answers based on every question I’ve ever asked the robot.

360
00:28:18,648.0000000002328 –> 00:28:28,428
So it does all this math, and it comes back and it says, “Oh, for your son, these are the criteria that matter most, and here’s 3 sunscreens that best meets that criteria.”

361
00:28:28,428 –> 00:28:29,706.9999999997672
Only I’m tricking you.

362
00:28:29,706.9999999997672 –> 00:28:32,328
That’s the results the robot would have given us 6 months ago.

363
00:28:32,328 –> 00:28:33,548
That’s ChatGPT.

364
00:28:33,548 –> 00:28:36,288
Do you know what the results were 2 months ago?

365
00:28:36,288 –> 00:28:37,847
They looked a lot more like an e-commerce site.

366
00:28:37,847 –> 00:28:41,148.00000000023283
They had product tiles, and I could click through and buy the product.

367
00:28:41,148.00000000023283 –> 00:28:42,548
But I’m still tricking you.

368
00:28:42,548 –> 00:28:47,387
If you did this search over Christmas, this is what it would look like.

369
00:28:47,387 –> 00:28:48,928
“Don’t go to a retailer.

370
00:28:48,928 –> 00:28:51,028
Just buy the sunscreen straight from us.

371
00:28:51,028 –> 00:28:53,308
We’re selling Glossier direct,” right?

372
00:28:53,308 –> 00:28:55,627
And see what you want, click on it.

373
00:28:55,627 –> 00:28:59,428
Uh, 3 clicks, that’ll be relevant later.

374
00:28:59,428 –> 00:29:04,688
Uh, check out, and bam, you’ve got sunscreen at home.

375
00:29:04,688 –> 00:29:08,488
And think about how much of this has happened in the last quarter.

376
00:29:08,488 –> 00:29:11,248
Think about how much of this has happened this week, right?

377
00:29:11,248 –> 00:29:17,568
Uh, ChatGPT launched a dedicated shopping research engine, uh, right before Thanksgiving.

378
00:29:17,568 –> 00:29:27,048
Um, and then on Thanksgiving, Target launched an app that you could use to do research for sunscreen and buy sunscreen direct from Target on ChatGPT.

379
00:29:27,048 –> 00:29:37,028
Uh, Perplexity, which had been doing this for a year, launched a new version of their checkout that allowed you to be the merchant of record on Perplexity the day after Target launched its app.

380
00:29:37,028 –> 00:29:46,588
Uh, by the end of Cyber Week, Walmart had announced that they were gonna make available their entire product catalog on ChatGBT, GPT.

381
00:29:46,588 –> 00:29:54,268
Um, last week, on Monday, Microsoft announced that if you find products you want in Copilot, you can buy them direct from Copilot.

382
00:29:54,268 –> 00:30:00,668.0000000002328
And on this very stage on Sunday, Google announced that you could do it from Google, right?

383
00:30:00,668.0000000002328 –> 00:30:10,208
Uh, the AV guys wouldn’t let me update the deck again, but yesterday, Apple announced that we’re gonna use that Google engine on all the Apple devices.

384
00:30:10,208 –> 00:30:11,947.9999999997672
So think about what that means.

385
00:30:11,947.9999999997672 –> 00:30:19,367
Agentic commerce is not, “Hey, Google, order a new ingredient for my kid’s lunch.”

386
00:30:19,367 –> 00:30:24,848
Agentic commerce is, “Hey, Siri, never let me run out of ingredients for my kid’s lunch again.”

387
00:30:24,848 –> 00:30:26,540
And think about what Siri’s gonna do.

388
00:30:26,540 –> 00:30:31,580
She’s gonna go, “Oh, Jason’s kid goes to Chicago Public Schools, and here’s the lunch schedule.

389
00:30:31,580 –> 00:30:37,800
And Jason flies too much on United Airlines, and I see he’s got a vacation booked for Hawaii, he’s not gonna need lunch that week.

390
00:30:37,800 –> 00:30:40,140
And Jason buys all his groceries at Walmart.

391
00:30:40,140 –> 00:30:45,310
Even though he doesn’t live near a Walmart, he’s pandering to his customer, so he buys all his groceries at Walmart.

392
00:30:45,310 –> 00:30:49,200
Um, and I see from his Walmart purchases that Jason’s kid doesn’t eat peanut butter.

393
00:30:49,200 –> 00:30:54,720
Jason’s kid only eats Pirate’s Booty, and so I’m gonna make sure that Jason never runs out of Pirate’s Booty.”

394
00:30:54,720 –> 00:30:55,800
Right?

395
00:30:55,800 –> 00:30:57,530
That is agentic commerce.

396
00:30:57,530 –> 00:30:59,280
And do you know what’s scary about it?

397
00:30:59,280 –> 00:31:11,420
When I first started, I launched my first e-commerce site at Blockbuster Entertainment in 1993, and it took 22 clicks to buy one of the 8 Disney movies you could buy in the world in, in 1993.

398
00:31:11,420 –> 00:31:14,620
Um, I’m still waiting for my residuals from that, that gig.

399
00:31:14,620 –> 00:31:27,000
Um, I spent my entire career getting 22 clicks down to the 4 clicks I mentioned earlier, and honestly, I thought that’s what was gonna be on my tombstone, “Here lies Jason ‘Retail Geek’ Goldberg.

400
00:31:27,000 –> 00:31:28,840
He got us down to 4 clicks.

401
00:31:28,840 –> 00:31:29,500
High 5.”

402
00:31:29,500 –> 00:31:30,640
Right?

403
00:31:30,640 –> 00:31:35,840
And I would’ve been totally satisfied, until the bastards invented one click.

404
00:31:35,840 –> 00:31:38,060
Do you know why I’m bitter about one click?

405
00:31:38,060 –> 00:31:41,380
Do you know how many clicks it takes to make a one-click purchase?

406
00:31:41,380 –> 00:31:43,300
It takes 4 clicks.

407
00:31:43,300 –> 00:31:44,400
They just marketed it better.

408
00:31:44,400 –> 00:31:46,390
I’m so mad that I didn’t think of that.

409
00:31:46,390 –> 00:31:52,680
But the robot that we just met could buy our products with 0 clicks, right?

410
00:31:52,680 –> 00:32:05,550
And so all of that friction, all of that marketing, all of that persona work that we’re doing to sell to the Goldbergs goes away when the NVIDIA microchip makes sure I never run out of Pirate’s Booty.

411
00:32:05,550 –> 00:32:15,080
And the guy that invented the word for this, agentic commerce, is a super credible AI scientist, he’s Professor Andrew Ng, professor at Stanford.

412
00:32:15,080 –> 00:32:22,780
Ran Google’s Deep Think AI Lab, People Magazine’s Most Fascinating Man in the world in 2013 for his AI research.

413
00:32:22,780 –> 00:32:23,880
Totally legit.

414
00:32:23,880 –> 00:32:26,080
Invented the phrase “agentic.”

415
00:32:26,080 –> 00:32:32,340
Uh, if you’re curious what Dr. Ng is doing today, meet the newest mor- board member at Amazon.

416
00:32:32,340 –> 00:32:39,300
So if you’re wondering what Amazon thinks the future of commerce is, you can bet that they’re thinking about agentic commerce, right?

417
00:32:39,300 –> 00:32:40,860.0000000002328
And it’s already happening.

418
00:32:40,860.0000000002328 –> 00:32:52,360.00000000023283
Uh, over, uh, this, this h- holiday week, the, the Cyber 5 week, um, lots of customers were introduced for the first time to Rufus and Sparky, right?

419
00:32:52,360.00000000023283 –> 00:33:03,060
Uh, Amazon announced that, uh, customers that used Rufus converted 60% more often than customers that did not use Rufus.

420
00:33:03,060 –> 00:33:08,940
And on Black Friday, 38% of all Amazon sessions used Rufus.

421
00:33:08,940 –> 00:33:18,680
So for the first time this holiday season, a bunch of our shoppers met an agentic agent, but that agent lived on a retail website.

422
00:33:18,680 –> 00:33:23,440
You had to already know you needed something from Amazon or Walmart before you met that agent.

423
00:33:23,440 –> 00:33:26,500
And potentially, that’s not gonna be the future.

424
00:33:26,500 –> 00:33:31,840
Potentially, you’re gonna use a robot that’s gonna pick the retailer for you, right?

425
00:33:31,840 –> 00:33:49,340
So if you go to chatgpt.com or copilot.com or, uh, gemini.google.com or perplexity.com, you can get all this amazing research, you can get products recommend- recommended, you can even buy products and you never had to pick a retailer.

426
00:33:49,340 –> 00:33:50,660
You never had to go to Amazon.

427
00:33:50,660 –> 00:33:52,340
You never had to go to Walmart.

428
00:33:52,340 –> 00:33:59,620
So the, the onsite agents may well lose, uh, some or all of the traffic to the offsite agents.

429
00:33:59,620 –> 00:34:03,760
And by the way, this isn’t just happening on the web, this is happening in the store.

430
00:34:03,760 –> 00:34:16,339
I took the ChatGPT app to my local Kroger store, and I pointed it at the sunscreen aisle and I did this, “Hey, ChatGPT, what do you see?”

431
00:34:16,339 –> 00:34:18,659.9999999997672
I see a variety of lotions and sunscreens.

432
00:34:18,659.9999999997672 –> 00:34:22,179.99999999976717
Are you looking for a specific SPF or brand?

433
00:34:22,179.99999999976717 –> 00:34:22,540
Uh, yes.

434
00:34:22,540 –> 00:34:26,320.00000000023283
I’m going on vacation to Hawaii with my 9yearold son.

435
00:34:26,320.00000000023283 –> 00:34:29,720.0000000002328
What’s the best sunscreen for use on Maui?

436
00:34:29,720.0000000002328 –> 00:34:33,480
For Hawaii, you’ll want a reef-safe sunscreen to protect the coral reefs.

437
00:34:33,480 –> 00:34:38,080
Look for mineral-based options with zinc oxide or titanium dioxide.

438
00:34:38,080 –> 00:34:40,960
Brands like Blue Lizard or Badger are good.

439
00:34:40,960 –> 00:34:44,520
Make sure it’s at least SPF 30 for both you and your son.

440
00:34:44,520 –> 00:34:47,279.99999999976717
Do you see a suitable choice on the shelf?

441
00:34:47,279.99999999976717 –> 00:34:49,800.0000000002328
Yes, I see a few options that look suitable.

442
00:34:49,800.0000000002328 –> 00:34:53,380
The Sun Bum sunscreens on the middle shelf are reef-friendly.

443
00:34:53,380 –> 00:34:57,680
Also, the Alba Botanica ones to the right are another good choice.

444
00:34:57,680 –> 00:35:01,580
Both brands offer mineral-based broad-spectrum protection.

445
00:35:01,580 –> 00:35:01,900
Great.

446
00:35:01,900 –> 00:35:04,080
Which one would you recommend I try?

447
00:35:04,080 –> 00:35:08,060
Sun Bum is a popular choice and easy to apply, especially for kids.

448
00:35:08,060 –> 00:35:11,540
It’s reef-safe and provides broad-spectrum SPF 50.

449
00:35:11,540 –> 00:35:12,880
I’d give that one a try.

450
00:35:12,880 –> 00:35:13,240
Perfect.

451
00:35:13,240 –> 00:35:14,500
Thanks very much.

452
00:35:14,500 –> 00:35:15,140
You’re welcome.

453
00:35:15,140 –> 00:35:17,320
Have a fantastic trip to Hawaii.

454
00:35:17,320 –> 00:35:18,840
Thanks, ChatGPT, I will.

455
00:35:18,840 –> 00:35:21,440
She is super friendly, by the way.

456
00:35:21,440 –> 00:35:32,200
Um, so it’s happening in-store, but all of these websites and stores that are hoping to win agentic commerce, they may lose to something even more upstream.

457
00:35:32,200 –> 00:35:45,140
They may lose to the browsers, because the, the AI companies now make their own browsers, like Comet and Atlas, and all the legacy browsers are building robots into the legacy browsers like Edge and Google Chrome.

458
00:35:45,140 –> 00:35:49,000
Um, and so-It may be that we don’t even go to a website to go shopping.

459
00:35:49,000 –> 00:35:53,220.00000000046566
We’re, we’re always shopping the robot whenever we’re in our website.

460
00:35:53,220.00000000046566 –> 00:35:58,800
And the browsers may be in for a bad disruption, because maybe you don’t even use the browser, right?

461
00:35:58,800 –> 00:36:05,980
Maybe the robot’s just built into your phone and your operating system does the answer before you ever do any of this, right?

462
00:36:05,980 –> 00:36:15,760
And that’s what the, the Apple Google announcement was yesterday, is that the robot’s built into Apple devices, it’s built into Go- Google devices, it’s built into Microsoft devices.

463
00:36:15,760 –> 00:36:19,020
And so, uh, we may ubiquitously have the robot.

464
00:36:19,020 –> 00:36:25,680
OpenAI bought Johnny AI’s company for $4 billion to build the robot into all of our brains very likely, right?

465
00:36:25,680 –> 00:36:27,489
And this isn’t the future.

466
00:36:27,489 –> 00:36:29,340
This is already happening.

467
00:36:29,340 –> 00:36:37,160
Uh, ChatGPT released all of their data from last July and they gave it to a bunch of Harvard researchers that published a study.

468
00:36:37,160 –> 00:36:39,700
It’s the study Sucharita referenced in her thing.

469
00:36:39,700 –> 00:36:46,060
And in that study, they said only 1.9% of all our prompts are trying to buy something.

470
00:36:46,060 –> 00:36:50,360
But just so you know, that’s 1.9% of 12 billion prompts a day.

471
00:36:50,360 –> 00:36:52,600
So I did some public math for you.

472
00:36:52,600 –> 00:36:59,490
That’s 52 million prompts a day people are trying to buy something off of ChatGBT last July.

473
00:36:59,490 –> 00:37:02,760
And just so you know, you couldn’t buy anything on ChatGBT last July.

474
00:37:02,760 –> 00:37:09,660
It was a research engine only, but it was already getting 52 million visits a year and they’re doubling every 6 months.

475
00:37:09,660 –> 00:37:13,920
So this is probably over 100 1000000, uh, questions that they’re getting today.

476
00:37:13,920 –> 00:37:22,279.99999999953434
But even if it’s still 52 1000000, just so you know, that makes ChatGBT the 9th largest e-commerce site in the world.

477
00:37:22,279.99999999953434 –> 00:37:27,860
Without even having a checkout engine, they’re getting more traffic than Apple, they’re getting more traffic than Shopee.

478
00:37:27,860 –> 00:37:37,560
They’re, they’re a top 10 e-commerce site in the world without commerce, just based on 1.9% of their prompts being commerce related.

479
00:37:37,560 –> 00:37:41,100
And I know most of us do business in the US so I extrapolated that to the US.

480
00:37:41,100 –> 00:37:49,120
It’s about seven billion prompts, uh, seven million prompts a day in the US, which makes them the 11th largest e-commerce site in the US.

481
00:37:49,120 –> 00:37:53,660
Bigger than Home Depot or Best Buy already, and it’s getting much bigger.

482
00:37:53,660 –> 00:37:56,440
Um, so I’m always interested in proof points.

483
00:37:56,440 –> 00:38:00,320
Uh, I found this, this, uh, great company, uh, called Measured Protocol.

484
00:38:00,320 –> 00:38:04,840
They have a panel of users that actually give them their ChatGBT logs.

485
00:38:04,840 –> 00:38:06,220.00000000046566
So this isn’t a survey.

486
00:38:06,220.00000000046566 –> 00:38:20,340
This is looking at the data of real users, and if you look at how many searches were trying to buy salty snacks on the robot, it ex- extrapolates to 6.8 billion prompts a day worldwide, um, uh, or a month rather, worldwide.

487
00:38:20,340 –> 00:38:22,080
So a huge amount.

488
00:38:22,080 –> 00:38:34,930
And we know from all of the, the, the robot analytics company, this is from my, my, uh, friends at Evertune, um, that each robot has different criteria and is giving us different answers.

489
00:38:34,930 –> 00:38:37,120
And we’re not doing the same on all the robots.

490
00:38:37,120 –> 00:38:41,288.99999999953434
And the robots aren’t giving the same answers that the search engines gave.

491
00:38:41,288.99999999953434 –> 00:38:45,080
And the robots don’t even have the same criteria that people have, right?

492
00:38:45,080 –> 00:38:57,790
So the robots for salty snacks care a lot about, uh, ingredients and healthfulness, um, and, uh, some of the most popular salty snacks don’t do well, uh, for those criteria.

493
00:38:57,790 –> 00:39:01,210
And when you go, “Wait, how did the robot decide what was important?”

494
00:39:01,210 –> 00:39:06,580
The robot is reading tons of micro-influencers’ blogs to learn what, what’s important.

495
00:39:06,580 –> 00:39:08,560
They’re reading Reddit to learn what’s important.

496
00:39:08,560 –> 00:39:11,520
They’re not reading our manufacturers’ websites.

497
00:39:11,520 –> 00:39:14,560
They’re not reading our retailers’ websites near as much.

498
00:39:14,560 –> 00:39:20,800
So if we’re gonna win the robots, we have to understand what’s important to the robots, which is going to change every day.

499
00:39:20,800 –> 00:39:27,279.99999999953434
So we need tools and we need business processes to understand what the robots care about, right?

500
00:39:27,279.99999999953434 –> 00:39:28,360
And the industry has

501
00:39:28,360 –> 00:39:36,600
They’re still arguing, but they call it GEO, generative engine opti- optimization, or AEO, answer engine optimization.

502
00:39:36,600 –> 00:39:43,240
Uh, and my, my friend Scott has, has proposed that, hey, those are important, but what you actually need is something more strategic.

503
00:39:43,240 –> 00:39:47,779.9999999995343
You actually need, um, uh, agentic commerce optimization.

504
00:39:47,779.9999999995343 –> 00:39:50,510
You’re not just optimizing for the robots.

505
00:39:50,510 –> 00:39:52,620
You have to optimize for your product catalog.

506
00:39:52,620 –> 00:39:55,140
You have to optimize for the business outcomes.

507
00:39:55,140 –> 00:39:57,620
You have to optimize for the customer expectations.

508
00:39:57,620 –> 00:40:06,279.99999999953434
And so you actually have this bigger job of which GEO is a small part, and he, he started a company here at the show, Refibuy, to try to help brands with that, right?

509
00:40:06,279.99999999953434 –> 00:40:11,680
And so this kind of thinking is what we need if we’re going to win the robots.

510
00:40:11,680 –> 00:40:16,060
And so I want to leave you with one last piece of advice I got from a much smarter person.

511
00:40:16,060 –> 00:40:19,900
Uh, as you may have heard, the CEO of Walmart is retiring this month.

512
00:40:19,900 –> 00:40:26,900
Uh, I’m super bitter because he’s not shy to point out that he’s 2 years younger than me and he’s retiring, so just saying.

513
00:40:26,900 –> 00:40:32,464
Uh, so for the last 2 years, every meeting that Doug McMillon’s gone to at Walmart, do you know how he starts the meeting?

514
00:40:33,870 –> 00:40:34,260
“Hey, y’all.

515
00:40:34,260 –> 00:40:35,700
Thanks very much for coming to this meeting.

516
00:40:35,700 –> 00:40:37,900
I appreciate all your, your time and attention.

517
00:40:37,900 –> 00:40:41,776
Before we get started, how did you use AI to prepare for this meeting?”

518
00:40:44,760 –> 00:40:47,660
And I asked him once, I said, “Why, why are you always asking that question?”

519
00:40:47,660 –> 00:40:49,240
And he said, “Well, it’s simple.

520
00:40:49,240 –> 00:40:51,470
Like, I’m not the fishing merchant anymore.

521
00:40:51,470 –> 00:40:53,420
They won’t let me pick any products.

522
00:40:53,420 –> 00:40:56,220
And John Furner won’t let me muck with the USPNL anymore.

523
00:40:56,220 –> 00:40:57,720
He owns that, right?

524
00:40:57,720 –> 00:41:01,000
Uh, and so my job is to be the change agent.

525
00:41:01,000 –> 00:41:05,000
The hardest thing in these disruptions, Jason, is not the technology.

526
00:41:05,000 –> 00:41:06,680
It’s not the strategy.

527
00:41:06,680 –> 00:41:10,480
It’s getting the 1.6 million Walmart associates to think different.

528
00:41:10,480 –> 00:41:15,220
It’s the organizational change management, and I’m the head cheerleader for thinking different.

529
00:41:15,220 –> 00:41:20,280
So I’m gonna keep asking and making people think different about these new things.”

530
00:41:20,280 –> 00:41:25,900
And do you know what the answer was in that first meeting, the first time he asked the question, “How, how’d you use AI to prepare for the meeting?”

531
00:41:25,900 –> 00:41:32,020
It was a bunch of crickets looking at him, and then some brave soul looked at him and said, “Doug, it’s illegal to use AI at Walmart.

532
00:41:32,020 –> 00:41:33,680
Like, it’s been banned.”

533
00:41:34,520 –> 00:41:36,560
Uh, and so think about what’s happened over the last 2 years.

534
00:41:36,560 –> 00:41:46,140
They’ve gone from IT locking down all the AI tools to buying AI tools for all 1.6 million associates, to creating 6 of their own super agents.

535
00:41:46,140 –> 00:41:51,620
Uh, Sparky and Marty and @Walmart, and the, the Walmart developer, uh, agent.

536
00:41:51,620 –> 00:42:12,810
And so what I, I wanna leave you with this final thought is, while the tech is important, the strategy is important, we have to think about how we’re gonna take all those human beings, all those coworkers in our organization, and get them comfortable with this disruption so that we don’t end up being the Frederic Tudor ice harvesters or the American Ice ice factories.

537
00:42:12,810 –> 00:42:16,340
And I know you’re all on pins and needles, so I’ll leave you with one final fact.

538
00:42:16,340 –> 00:42:18,448
My family did in fact make it to Hawaii.

539
00:42:19,520 –> 00:42:21,320
So thank you guys very much for your attention.

540
00:42:21,320 –> 00:42:23,960
Congratulations on an amazing show.

541
00:42:23,960 –> 00:42:33,118
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