Your Next Competitor Might Be an AI Agent

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AI is reshaping the entire research stack, from how analytics gets done to how consumers shop and what data actually matters. In episode 136 of The Exchange Karen Lynch and Lenny Murphy cover the product launches, funding rounds, and infrastructure shifts that are quietly redrawing the industry, and what research teams need to do right now to keep up.

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Karen Lynch: I'm showtime, showtime.

Lenny Murphy: There we go. All right. We were optimizing our agenda.

Karen Lynch: Optimizing. Yes. I think Lenny was just about to say we should let people know we had like dozens of new product launches this week. And I mean, from companies that, you know, are really good partners of ours. You know, companies that we have strong relationships with, we just can't cover them all.

Lenny Murphy: And just kind of discussing strategy there, like what to do, what to do. Right. I think what we can say, we'll cut, Karen came up with a great idea. You came up with a great idea of what's new, new, right? It's kind of a prioritization. Yeah. And I think that makes an awful lot of sense. Totally good if that for everybody else listening. I mean, truly, just a flood of new product releases this week. All just validating the themes, right? All data synthesis, AI, AI integrations. I mean, all variations on a theme, not because that is not important, simply because that is. Just the momentum, the direction of travel for the industry as a whole. Um, and for whatever reason, everybody decided to release all their new products this week. Early, let's do that. I guess so.

Karen Lynch: I mean, literally, there's so many that when Lenny's knee deep in grit and Karen's about to go to Europe, like, a lot of stuff out there, right?

Lenny Murphy: Right. We did have a conversation on Wednesday. Um, the team just thought: is there another path for Greenbook to show this stuff? It's in discussion. We never need to. Do we split into two shows?

Karen Lynch: Do we like the new product show? Like, do we have our own little like, Is this show, is The Exchange all about us kind of exchanging intel about the future? And yet then we have another one about just like, let's just talk about new products. Maybe we have two of those. Maybe. So, so just the audience FYI. We really are, because we're trying to keep it as condensed.

Lenny Murphy: We're trying to keep it structured with just a few things that are really most important. I mean, really the signal. Not the rest of it is noise, but the things that really represent the signal. And we're figuring out ways to make sure that everybody's getting some attention because everybody's doing cool shit, right? There's no doubt that, and we want people to recognize that. We just don't have time to cover it all here, especially this week. We would be here for like two hours. So two, two, three hours. Anyway, let's do our plugs real quick.

Karen Lynch: Yeah, yeah. Oh, yeah, plugs. Oh, my goodness.

Lenny Murphy: Europe, right, right. Last plug for Europe, right?

Karen Lynch: Last plug for Europe. And the reason we say last plug for Europe is we are not here next Friday because Greenbook closes in celebration of June 19th, Juneteenth day. So we will not be here next Friday. So, this is officially our last plug for Europe. The following week, we will be overseas, many of us on the team at IIEXEurope. Celebrating a fantastic event with some of these great speakers. Thank you so much, Karley. Not too late to sign up and register. Uh, the code Exchange will give you 15% off the general admission tickets.

Lenny Murphy: Um, in Amsterdam in June, not a bad place to be. And in the Bursa Verlage, right? I mean, we've been there now, what, like 10 years, just because it's such a freaking awesome venue.

Karen Lynch: Um, it's just yeah, you know, we love it there. It's so close to Central Station. Um, you know, the train station is right in Amsterdam. It's easy for people to get to. You know, it's just, it's just a great city in, you know, again, central, easy for people to get to. So we keep staying there. And there's, you know, we like to move around here in the US. In Europe, it just seems to suit everybody's purposes really well. So there we sit.

Lenny Murphy: 100%. And then right after, then we're like, Europe, and then there's July 4th, and right after July 4th. The GRIP form. I'm really excited about that again. Keep hyping. The GRIP report will be out, I think, next week. I think it's an important one. It's a big one. Always big, but it's important too. There's so much data informing the trajectory of the industry and that and the shifts that are just happening faster and faster. And we're talking about all that with our commentary providers on the GRIP forum for July 8th.

Karen Lynch: So, and that's free to attend for everybody listening. Go to greenbook.org slash events. You can find the registration link. It's free to attend virtual events.

Lenny Murphy: 100%. You will get your full, your absolute. Fill me, like be sickened by it. Um, uh, because I will be moderating. I actually look forward to it. It's quite a marathon. Like, I do presentations, they have to moderate three panels back to back, and it's kind of fun. Um, so the uh anyway, but fun times for that. And then all attention towards your or towards IX West.

Karen Lynch: Well, no, because we have IIEXAI, we will have over West, but we will also have IIEXAI in there, so yeah. Come July, we'll start talking about everything else. But West is our next biggest in-person event. Getting very excited about that. That will be in San Francisco. First time we're bringing our show to the West Coast for the folks out there who made it very clear that, you know, sometimes traveling to the East Coast is just not conducive for their work weeks. We respect that and we're going to, you know, bring what we do out to them.

Lenny Murphy: Yeah. We're not retreading IX, you know, North America.

Karen Lynch: It's not exactly the same. There will be similarities. Some of the formats will be the same. Still have those 20-minute speaking spots. We will have three stages. We will have our competition there as well, but we'll also be having roundtables like we used to do when we were in Atlanta. And so we will be having those roundtable conversations. We'll have slightly longer breaks, you know, because we'll have a slightly laid-back pace there. We'll have some kind of kiosks for. I am some startups and really leaning into everything that Silicon Valley has to offer. And of course, we'll be right on the pier in San Francisco. So it will be kind of a location that can't be beat. I think this will be an event not to miss. We're also pulling in a lot more UX professionals, which is pretty sweet. And some of the speakers that I'm talking to are excited because the discipline of UX research and insights work is going to be. Kind of coming together like maybe like it was at one point in time, but then kind of the two disciplines found their own space, but now they're coming back together again. And the people that I'm talking to are very excited about that. And so we are as well.

Lenny Murphy: And that's probably segue because the synthesis, right, we've had these things that were all under one umbrella years ago. They split, they're kind of adjacent, you know, but now we're back in the world of synthesizing information, unlocking new value from that. And that leads us right into our first story. Yeah. So you, I think you found this one, The Anthropic.

Karen Lynch: Yeah. So it's interesting. And I thought, so Anthropic, this is kind of like, it would seem like further reading, right? It's kind of like a post that they wrote about. How Claude is enabling self-service data analytics. And at first glance, you might be like, why is this a tech development, Karen? Why are you putting it here? And not just for us to read about, right? But here's the thing: it's talking about how they are using, how their data analytics people are kind of using Claude, of course. But they're talking about 95% of their business analytics queries being automated. And that gives me pause, right? That's not just for further reading. That's not just something for you to think about. That's something for you to really say: hold up. If this tech company is automating 95% of its data analytics, y'all should be paying attention to that because that means your data analytics. Should also be moving towards automation or will be moving towards automation. And what does that mean for you? If you are a data analytics professional, if you're a data scientist and you are not moving your skills towards learning and understanding that data automation process, this is a good place to start. So I think that to me, that was the big takeaway from this particular piece: there are the tools. Anyway, it's all coming together and this is a great place to start from. I don't know what your two cents were, but that was my big takeaway from this.

Lenny Murphy: Well, let's do the other one that's kind of related. And then, because this has been the theme of the week, let's dig into it a little bit. Let me think about our Wednesday meeting of the process. So we have some context to share. But related to the anthropic, which particularly points out organizing information.

Karen Lynch: Right? 

Lenny Murphy: That was a big piece of that. And Stack Overflow launched a new way for AI tools to find, check, and improve technical answers with human oversight, which fundamentally was about knowledge libraries and knowledge management, not just from a, oh, here it is organized, but how does that fit from context? How is that context now then connected into agentic workflows? And so, Karen, I was thinking a lot, guys. We had this internal meeting of how do we, you know, leverage content in new ways, et cetera, et cetera. And we were showing our own individual processes. I had been resisting skills, not resisting, I just hadn't done it. And then Karen, so kindly actually wrote, something that I was like, well, damn, there's a skill. Okay. And here, here's the context. Where I've gotten to my personal workflow, and I think this is exactly what we're talking about through all of this, right? I organize information that I curate that I think is relevant and important in spaces. And those spaces are aligned to topics or business issues or clients or whatever, right? But so there's a curated context layer. Now that I am building, you are building, we are all kind of building appropriately. And now you can add skills. I think almost every frontier model has a skills component where you can write this: this is expressly what I want done, how I want it done. This is the additional context and structure on how to do these things. So then when you're diving in, to synthesize information and unlock new value from this context layer, this library of information, which often is research reports. So, right, the uh there's a whole other layer of now making that much more actionable. So, using this layer of skills, and that's what we're talking about, these examples. And this is, I would argue, this is. Worldwide. I mean, every company needs to be thinking about how you structure the context that provides context to unlock these tools and their capabilities to be able to streamline that process with the human loop, human in the loop orchestration and judgment layer. Yeah. Um, but more of just eliminating the process.

Karen Lynch: So, well, this. Stack overflow for agents.

Lenny Murphy: Yes, right, particularly for agents to identify.

Karen Lynch: Well, what's interesting about this is I instantly went to, do you remember that MALT book, which was all the agents that got into that little playground where they were having their own little social network and they were having these philosophical discussions?

Lenny Murphy: And I think it was the New York Times. That was like, what, six months ago? I mean, God, it's history.

Karen Lynch: So I was like, well, this is interesting because what this is, is actually. It's no longer just like a little playground. This is like infrastructure where the agents are given this space by design, go in there and crowdsource or share intel for API fixes or fill in intelligence gaps. Like basically helping each other out with the work that needs to be done. So stop having philosophical debates that you might have had over on Maltbook, but now what I want you to do is really get to work. Like enough play. Now I want you to get to work. And I thought that was really interesting because that's what we are now equipping our agents to be able to do. Learn from one another. You know, we have this great, we have, we have agents that work at Greenbook. And, you know, Dana has agents that work for the sales team, and Jazz has agents that work for the marketing team. And I have agents that work for the content team. And I'm pretty sure Kara has agents who work now for the events team, because every now and then it makes a mistake and it says like Dana thought you might be interested in this. And I'm like, Dana? And I haven't even talked to Dana about it yet. But I'm like, I have to talk to Dana about it because I got a little intel from maybe Dana's agent, like came over and, you know, Dana thought the content team might need to know about it. I'm like, was that Dana or was that Dana's agent? Like, there's this interesting dynamic happening in our agentic world. And yet it's getting it. Our little agentic space is getting smarter and smarter by the minute and really introducing great efficiencies, things that we couldn't even dream of being able to do.

Lenny Murphy: You're ahead of me from that standpoint. I mean, with my workflow, the skills. Like I do now the next step is take the skills and create agents off of those skills.

Karen Lynch: They're all very different. That's the, and that's, I think, the big overarching message for all of this is they're all, they're all very different and they're all at very different levels. The enterprise level is something that you and I are nowhere near, right? Because we don't work for enterprises. And I think that that's what, when you look at this, when you look at like this, this piece on. Stack overflow, these agents that work at the enterprise level that have large communities of agents being able to talk to one another. That is very different. You know, that's very different from two or three kinds of teams of agents talking to each other. Now we're talking about hundreds of autonomous agents getting to work with one another. The collective intelligence of hundreds of agents. Hundreds of agents, as if, you know, that is very different. That is a different level of knowledge and a different level of utility being unleashed at the enterprise level. And I think, again, going back to like, what does this mean for research teams? It means make sure you have developers on your team, we have a dev team. We have somebody who is equipping Greenbook to be able to bring us into this world. We are upskilling our. Junior staff members so that they are getting proficiencies in this, so that hopefully they don't ever leave Greenbook. But if they do, we are upskilling them. Like, we are doing the responsible thing by our team. Our dev team is the responsible team for Greenbook. All of the research suppliers out there, make sure you have developers on your team who are doing the same thing for you. Because if we can do it, you can do it more than any mini media team.

Lenny Murphy: And or you know, even as you're yeah, if you're an individual consultant, right? The, uh, you know, if those are like, well, Lenny, you're part of Greenbook. Yes, but I kind of have a specialized function. So it's kind of like, I kind of sit out here. All the stuff Karen's talking about, I'm aware of, but I don't necessarily engage in because I'm just kind of a little different.

Karen Lynch: Yeah.

Lenny Murphy: But the point is, even if you're an individual consultant, like I am experiencing, it's not hard to build and deploy these things.

Karen Lynch: It takes some time.

Lenny Murphy: It's allocating time. Right. And still having access to expertise would be technical expertise is important. But this isn't the direction of travel. We're already there, right? We're already in the town now. So now we're just learning our way around the town, but we already got there. This isn't coming.

Karen Lynch: It's here. It's here. It's here. And I think that is, that is really the bottom line. Like it is here. And, and you and I can talk, by the way, because I can put the way I can, we can get an agent to work for you and I specifically, and it can email us things. So, you know, keep us. Yeah. Yeah. You and I will talk. That's a sidebar conversation that the whole world doesn't need to know about.

Lenny Murphy: No, no, it doesn't. But here we are, guys. But the efficiency to the last point on that, what we're all talking about is this is not. The efficiency unlocks here and I would argue that the uh I experience my judgment increasing. Maybe I'm fooling myself but deploying these technologies takes care of the process to allow us to think and and and to think about more than we could before, right? Because we only have so much attention.

Karen Lynch: Yeah.

Lenny Murphy: Pulling things together allows that attention to be focused on a synthesized information flow rather than a compartmentalized information flow. So all this is good and useful, not just from a process efficiency standpoint, but from an impact standpoint.

Karen Lynch: Yeah. Yeah. So, and that's why, I hope. Again, I hope the people listening are able to kind of hear these big stories as we kind of funnel down into some other stories. But we're starting off big and we're going to, we're going to, we're funnel down. So let's talk about some M  ⁇ A and partnership activity because I don't know much about Minerva. Have you heard of them before?

Lenny Murphy: I had not. I love the name, though. The AI platform, consumer marketers, 20 million funny brands with OpenAI contributing. So my take was this was a marketing workflow platform with insights embedded in everything we just talked about, right? But specialized just for marketing.

Karen Lynch: So it says within 24 hours of onboarding, marketers could unlock first-party customer data.

Lenny Murphy: So quick, you know, quick.

Karen Lynch: Quick access to first-party data. It says the MBA is already a customer. So I was sitting there thinking, like, you know, all right, let's go next. I have to throw that in there, right? Because all next all the time right now, they're going to, they're going to take it in five is what we're all saying.

Lenny Murphy: So, you know, all right.

Karen Lynch: That's that's the plan. So if the MBA is using them, then you know, it's going to be kind of, it's kind of interesting to see. So good luck, Minerva. And, you know, let's go.

Lenny Murphy: Good segue into the next one, Pogo, rose 32, roasted, raised, 32 roast. It's Friday. It's Friday. It's an AI-powered research platform, connecting brands directly with verified buyers. But that, so I happen to know one of the companies that they're working with is a company I know called Microblink that does receipt scanning. They power receipt scanning, right? So. This, it's about data. Look at the Minerva feed, right? The Minerva, it's about first-party data. And we're moving away. Actually, I dive deep in the last week or two into the shift happening in AI training. That's still happening, although it's more robot training now. But agentic feeds, feeds of real-time data. That's what is happening. That's absolutely appropriate for the research world, especially panel companies and the desire for. Verified human first party data is only increasing. And so here's an example of that. They raised 32 million.

Karen Lynch: Basically. A little sour about their claim in their press release saying that they're the world's first AI research platform powered by verified buyers because I think that's a big claim and I don't think it's accurate. I don't think that they're first. I mean, I think several of our partners are. Enumerator.

Lenny Murphy: Does Enumerator have one?

Karen Lynch: Yeah.

Lenny Murphy: You know, I think they're splitting hairs, they're splitting hairs, they're saying we're AI first and we're leveraging it.

Karen Lynch: That's I think their angle. And here's, I think it's a big deal. I just don't like that kind of thing.

Lenny Murphy: I've said this before when somebody says they're the first, I don't think you can. Well, so I was in a conversation earlier, this is relevant and it goes into our new product launches. Shit, just table stakes now, right? Already. So many of these things are being commoditized simply by their ubiquity. So I get why the company is, they're looking for differentiation because six months ago, you could make a different claim and it would be differentiated. A year ago, it would be really differentiated. Today, it is increasingly hard.

Karen Lynch: Oh, we have AI and data.

Lenny Murphy: Yeah. And it's true.

Karen Lynch: We just already got there. But I think if they, if they just focus on the real transaction data, which and transaction data is really important. Real transaction data. That is from verified buyers.

Lenny Murphy: Yes like I think we can all agree yes that is very important right now real transaction data from verified buyers one up and it's not easy to get and most of the companies already do that numerator ibota fetch I mean all those yeah they don't play in this world per se so you can't just go and get that that data easily from a research uh company standpoint so so big deal for that um uh I thought this was great quest mind share uh and detect combining data quality, real verified humans. So I made my camera jump because I was being emphatic. So very cool. We cannot, we've been talking about this for forever, right? The data quality issue is fundamental. It always has been, but really, it is in this world. So there's enough AI slop, bullshit, recursive.

Karen Lynch: You know stuff out there yeah yeah real human data is only increasing importance and that means quality so very cool yeah and this next one I mean these necessarily I think these are UK based um you know blue marble research and is it pi tate consulting and coachi research um uh combined under the new navigator insight brand end-to-end solutions, right? Like coming together, a couple of different companies. We talked about this last week with a bunch of different companies coming together. End-to-end solutions. Just what's going to keep happening, right? We're going to see more and more of this and it makes sense. Time permitting, we'll keep talking about it because we get it.

Lenny Murphy: 100%. There's more agencies and an audience listening, right? If you're having a hard time gaining traction independently, yeah. There's strength in numbers. So I think we will see more of these roll-ups, self-funded roll-ups.

Karen Lynch: It's so funny because all I keep thinking of right now is, gosh, and we don't often shout out, you know, our marketing, our marketing friends. You know, about Susan Griffin, who's very close to Greenbook. You know, we have a very close relationship with you know, with a lot of the marketers in the industry, they're often chairing our stage, like Norbert Lucy Davison, who is always bringing us content at our events. But Priscilla McKinney, wrote that book, Collaboration is the New. And I forget what the final thing is. So, like, she'll kill me for that one. But anyway, it's a book about collaboration. And I'm like, anybody who would like to, first of all, read Priscilla's book about collaboration and then think, okay, what can I do with collaboration to find people that perhaps I can join forces with in the new era? Because she was onto something with that book, I think.

Lenny Murphy: Agreed. But here to our orchestration, it's the same principle, right? It's the same idea. So, you know, there's business mechanics and all those things and deals, blah, blah, blah. But yeah, we'll see a lot more of that. All right. Let's get into new product launches. And again, we had like 500 this week.

Karen Lynch: I feel really bad that we're starting with this one, but it's a really no, we have to. We have to. I don't even want to, but it's really, it's big. It's big.

Lenny Murphy: So you want to drop the bomb or something? No. No, you, you go.

Karen Lynch: You go. All right. All right. Okay. So, friends. Our friends at NIQ, I swear, we're like, we get no kickback from them. Like this, this is nothing, nothing, right? But they're just rocking it. They're just rocking it. So they've launched something called product intelligence, which is helping retailers and brands, power AI-driven commerce experiences. And, you know, again, I looked at this and I'm like, gosh, do we really want to include them? Because we're whittling down this list. Do I really want to include them? Because they launched so many things. But, here's the deal. They're, they're. We know they're pivoting. We know they're launching or shipping a lot of things. But this one is about what happens when AI gets involved in commerce. And the whole idea here is that if autonomous AI agents are going to start doing some of our grocery shopping and aiding product discovery, your brand is not going to be invisible if. We get to work on that, right? And that's what this particular tool is helping with. It's this product intelligence designed to help your brand be involved when AI-driven commerce becomes more of a reality. This will start to feel really important a few articles from now about what Instacart is doing, which is here now, which is. Collaborating with the market. Again, spoiler alert, we'll talk about it in a few when we share that article, but it's here basically, you know, AI-driven collaboration in store, not just online. We talked about what's happening with AI collaboration in your Amazon cart. Like AI is in the mix. So, this particular product intelligence feature, yeah, it just makes so much sense. And I want to need, we need to talk about it because, um, not that this is the end-all tool, but you know, this is where we're headed. Um, brands need to be paying attention to how to make sure that their brands are visible to the you know AI agents that are doing the shopping. 100%, and that's the period. That's like all there is to it. That's like it's a very simple thing. I do want to say product discovery has changed.

Lenny Murphy: Yes. And again, I do want to step back a little bit just on NIQ because we've used them as an example so often. They had an event this week where they launched like a bajillion products. Yes. I mean, right. So this was one that stayed out and I, this is the right way to focus on it. But if you think, just step back. They have a data asset. They have a trust asset as well, right? They have market penetration, they have trust, and value. And they're just finding new ways to unlock value from that core data asset over and over and over and over again, right? And they're shipping all these products, and some of that's in partnership, some of it like this. You know, they're combining things, they're doing new things. But if you are a business, a CEO or business owner in this industry, how do you productize your fundamental asset? And IQ is just showing. They make it look so freaking easy. And yeah, they're a public company and they got you know tons of money. So let's acknowledge that.

Karen Lynch: Yeah, yeah, yeah.

Lenny Murphy: But the strategy they're deploying, yeah, is no different than the strategy that every single company in this space can deploy based upon their specific asset inventory. Yeah. And they just keep doing it.

Karen Lynch: So yeah. And if you're like, if you're, if you're entry level in, in the PR space, or if you have friends that are entry-level in the PR space, like look at those press releases, they're getting picked up everywhere. Like, you know, like there's, there's a reason why we keep getting them all. They're in our faces, week after week. We are seeing them everywhere. So.

Lenny Murphy: Yep. And they're probably using agents to do that.

Karen Lynch: Not necessarily. Right. Right. Yes. All right. Question Pro.

Lenny Murphy: Let's give a shout out to our friend Pebec. I have to say, utterly unsurprised by this. Question Pro, they're headless now. Meaning, exactly we've been talking about they're embedded in workflows via MCP. You don't have to go to questionpro.com. You have to log into Question Pro. You can access Question Pro in any LLM, in any workflow, in Slack, in whatever. They're a nimble company. So, and that's, you know. One thing that I just, I love about Vivek is he'll just come up with an idea oh, we're going to do it.

Karen Lynch: And he does it. Yeah.

Lenny Murphy: Yeah. The point is, here's another example. Smaller company. So, you know, they're not a big giant behemoth. Yeah. Skating to where the puck is going. Yeah. So already, VMCP, reduce friction, be where the work is, be embedded in people's workflow, unlock more capability and more users that way. Yeah. Yeah. If you're a tech platform, yeah.

Karen Lynch: Sorry. Go ahead. No, I know it's all really good. This one. You know, full disclosure: you know, there are limits to my computer knowledge, as you can all imagine. I might be really, you know, getting quite good at AI and some of the stuff I'm doing there, but I was like, headless architecture flew right. I know that's a new term. It's a new term. I was like, whoa, I need to, I need to do some research here. So, here I am, so what do I do? I asked Gemini. I'm like, all right, Gemini, tell me a little bit more about this. And, um, as I'm trying to learn, I'm like, oh, okay, I understand that. You know, I get it. Get it. But then I was like, so what does this mean for research buyers? And it starts talking about that. How, you know, you don't have to log into your web browser to use the tools. You can see just what Lenny was saying. And I'm like, all right, well, what does this mean for the competitors? Because now I'm curious, right? I'm doing a deep dive. This is what I do when I do research for these stories. And it's like, here's what Gemini told me. This shatters the value of having a pretty website or user interface. And I was like, well, that's interesting.

Lenny Murphy: Now, again, the whole SaaS apocalypse idea.

Karen Lynch: I mean, that's. I was like, what's this, what, what it's saying is, don't spend time on the user interface. That's not what they're saying. They're saying don't overinvest in that at the expense of agility moving into these. Spaces, right? What Question Pro is doing is making accessibility the priority and getting it elsewhere and being really ahead of the curve. Using your analogy, which I like, is you know, skate where the puck is going and stop worrying so much about the pretty face if we stay with hockey. And I think that's really interesting because so many companies might not be doing that and they might be really focused on. On that user interface on the web and staying stuck there. And I just thought that was very interesting, like things that make you say, hmm, that's interesting. So, and the implications from a, yes, sorry, I didn't mean to talk over.

Lenny Murphy: This is, I really want because this is so, although I do it all the time, anyway, I know it's one of my character flaws, but think about the implications from a business model standpoint, right? So, you won't. Question Pro is a SaaS business, right? And Build is a SaaS, they have salespeople who are out selling licenses to use your software, um, like everybody else. Yeah, that's turned on its head in this model. So, the um, I don't, I don't know the specifics, I haven't spoken to Vivek Co about this, but my suspicion is that. Not buying seats anymore, you're buying access or credits, yeah, probably. It's probably like burning tokens, yeah. And you pay as you go, and you're not worried, there's no salesperson involved, you're just there, and you're a buyer-user. What's the right solution for me to run a survey? Yeah, oh, question pros are already embedded.

Karen Lynch: And goes, yeah, yeah.

Lenny Murphy: Uh, and that's the world, yeah. So many implications.

Karen Lynch: Um, it's just interesting also because he's thinking about you know, thinking about how to make it an automated workflow, how out that friction, um, which is a step beyond, of people are talking about, which is this is the product we have, not how can I be, you know, and here this is the product that we have. I want to make it easier for the user versus what would make it. What would what does the user how could how could we fit into the user's workflow right be where the user is right it's a whole different paradigm shift and uh it is don't make them come to you yeah be where they are at the point that they need you so in the interfaces they need you and everything yeah pretty cool so anyway yeah pretty cool that's all Hats off for the innovation and, you know, pushing up, pushing us to do a little thinking research of our own and pushing everybody else listening, thinking, you know, okay, you know, back to that developer you need on your team.

Lenny Murphy: Anyway, if you go ahead,

Karen Lynch: No, no, just if your brain, if your brain had to look that up, you probably should have somebody on your team who knows what that is. Right.

Lenny Murphy: Yeah. Yeah. So you didn't ask Tim?

Karen Lynch: So Tim is not here this week. Okay Tim has left Tim. He has been out of town this week and so yeah, so he is not here to be my, you know, Tim.

Lenny Murphy: Yeah, no. 

Karen Lynch: Tim, what the hell does headless mean? I don't even know. I don't even. You get it, he hasn't chimed in yet. I don't know if he's able to listen. That's how busy Tim is this week. Oh, man. Oh, gosh. I knew something was missing. Okay.

Lenny Murphy: Start socializing. I don't know about you, but I was waiting for something like this. Yeah. The non-research company, right? Stat Social is basically social media analytics.

Karen Lynch: Yeah. Launched Digital Friends. Yeah.

Lenny Murphy: Allowing brands to survey, yeah, to talk to their digital twins built off of the data that they collect. Um, there's not a single piece of it that is um uh research process-oriented, right? That's uh, excuse me, they're leveraging lots of different data sources by creating digital twins now, yeah. Um Um, so we're coming now; we're getting it coming from other angles.

Karen Lynch: Yeah. Let's do some jumping. Are you okay if I do some jumping? Because there's a lot of reading to do if you want to stay with digital twins. And I think to do justice to some of these, some of this as a topic, I want to point down, I want to go to this Colgate study because this is a big brand published or this is a big brand in a big brand backed. A big brand backed it's a tongue twister.

Lenny Murphy: Say that three times, real fast.

Karen Lynch: If you get it, a study came out that Colgate's has backed that found LLM-generated synthetic consumers achieved purchase intent predictions approaching human survey reliability.

Lenny Murphy: And converting it into a Liker scale.

Karen Lynch: Yeah. So. Here we are talking about, you know, digital twins in general. And now we're talking about synthetic consumers. And we have not been shy talking about fit for purpose or, you they serve their purpose and they have their use cases. But, you know, there's, there's, there's a fast down, this is down at the bottom. Karley, I'm sorry, I'm jumping because I happen to know because I just did this, but there's a fast company article. About, you know, was that last week? About, was that this week? My thing is all, you know, it's this week. Yeah, last week, the rise of synthetic respondents was there. And there was one more, right? The research world. Oh, no, that was something different.

Lenny Murphy: No, the fast company was the only other one.

Karen Lynch: So, reading up on synthetic respondents this week, I think, is the bottom line. Just synthetic respondents is kind of the

Lenny Murphy: Uh just the thing to read up on yes and and that topic has dominated my my week with every single conversation yeah so the uh but the the cold made the point one one I remember vividly if literally a few months ago um yeah uh debating with simon chadwick on you know that no it's only 70 or 80 percent and love you god bless simon love you um Well, Colgate's saying that it's over 90% alignment, predictive. Yeah. Yeah. And it's only going to get better. So, but the particular semantic similarity rating that dive into this paper. It is, it really is interesting from a wonky kind of standpoint because it is still effectively text analytics.

Karen Lynch: Yeah.

Lenny Murphy: But they put some magic in there and it makes it look like a Liker scale. And that's, you know, I mean, it's basically purchase intent. But, and then there's debates on whether the purchase intent is good or not. But compared to a survey, a traditional survey, it was pretty damn close. And there we are. And Colgate, that was an important piece on it too. This is Colgate doing this and releasing it. So you think my clients are asking me for synthetic, you're right. They're not. No. But if you think that they're not doing it, you're wrong.

Karen Lynch: That's key. That's key right there. Because they are all checking it out and experimenting. Experimenting, but they're probably doing it in a very safe and controlled and trusted way because they want to make sure that they are building synthetic samples on verified data.

Lenny Murphy: Verified human data, absolutely.

Karen Lynch: They may not trust your sample, and I'll just leave it at that, right? They want to make sure that if they are putting synthetic samples together or creating synthetic consumers, that they are verified. To be accurate because otherwise it is a waste of their money. So the whole game's not going to mess around.

Lenny Murphy: The big ones mess around with this. 100%. And so, and look at the NIQ data. It's panel data, they still have what you're bonus son, right? Yeah. The M4 published a white paper. And it's, it's M4, it's a white paper. They're, you know, they're. Obviously have some agenda, but they're still right that deterministic shopper data is becoming a durable competitive advantage. And yes, and that's what M4 does. They have an app and they're capturing lots of data.

Karen Lynch: Yeah. Yeah. Well, and that's why this shopper data, that's why going back to this, this, um, this Instacart piece that I saw, remember, remember we used to talk about it. I feel like we talked about Instacart. Years ago because I was all like an Instacart buyer during COVID, and I then just stayed an Instacart buyer. But I was reading this about Weiss. I don't have Weiss Markets up here. I don't know if you, I don't know where Weiss is. Weiss is California. I feel like I've shopped at Weiss before. Maybe it's a West Coast thing. You know, anyway, Weiss Markets. But like they're deploying AI-powered, what they're calling caper carts that when you go down the aisle, you're getting kind of like AI, like, oh, you've bought this before, or oh, here's a coupon for this. Like, the AI is helping you shop, basically, making recommendations so that you don't walk past something or you don't forget something. Like, I don't know, like, if I'm going down the aisle and it's like, don't forget your. It's never going to tell me not to forget coffee because I would never forget coffee. Like, you know, like, like, you just skipped the, you know, the toiletries aisle and you're out of toothpaste. I'd be like, oh, cool. Thanks. Like, little things like that. Like, if I get an AI assist when I'm in the store, that's pretty sweet. Like, you know, or, um, you know, if I'm, if I'm rushing through the produce aisle and it says to me, like, you usually, you usually get tomatoes. You're, are you skipping the tomatoes?

Lenny Murphy: Say, oh, forget the strawberries. Right.

Karen Lynch: Don't forget the strawberries. You know, like, I might like an AI assist when I'm rushing through the grocery store. Like, I don't know what my behavior will be. But if you think about that and you deal with it and then you think about how all of that new shopper data is going to play out. Like 100, it's all compound. That's how AI is going to learn, right?

Lenny Murphy: If the AI has influence, right, so you can go right back to the beginning, right, of structuring the data, have it together because they're all going to learn and unlock these agents, it's just another deployment of the agent.

Karen Lynch: Yeah, so the NIQ piece, the M4 white paper, this Instacart thing, and then you put it all together with, you know, this ARF article. It was like, definite theme this week, right? So the ARF, what's MSI?

Lenny Murphy: Bought MSI or the MERGE, the Marketing Science Institute.

Karen Lynch: Science. Yeah. So found that AI product recommendations reinforce existing brand hierarchies while prompt design significantly influences brand visibility and positioning. So, again, another piece to read if you are exploring this piece, I mean, this space about how AI is influencing product purchase decisions. And I mean, I would. I would suspect that every single one of us that touches upon product marketing in some way, shape, or form should be paying attention to this. Because certainly, if you serve a brand, this is on a brand's mind right now. I can't imagine there's a brand that isn't paying attention to this on some level.

Lenny Murphy: Think about all of the work done, the science of brand growth. You know, and the emotional connections of branding and let alone advertising, right? Two different things, connected but different. And now there is this new wrinkle. What does a brand, what does brand relevance or emotional intensity for a brand mean to a freaking agent? Yeah. Yeah. It doesn't mean anything. And it's not how it's buying recommendations. And there's so much variability. There's another great, I guess we'll wrap up with that. The research world, good articles on agenda commerce, the reshape innovation, product development cycles, all the implications of all of this is amazing. And we'll just put one more kind of WTF component on this. And we haven't even gotten the robots yet. Yeah. That's still coming this year and next year. So we think about a gentle buying. Rapidly emerging. And if the powers that be from a finance standpoint have their feathers, you know, by this time next year, it'll be a robot doing the shopping for us, which is effectively just a walking agent collecting data, sharing data, all back and forth. This is where we are.

Karen Lynch: Yeah. What's interesting about this sidebar, you know, we have this puppy, and I had put a picture of the puppy into, you know, one of the conversations I was having with ChatGPT and it responded with the judgment that the puppy was cute. The puppy is cute. But my immediate thought was, well, how are you capable of having an opinion? Like, you know, I really like I tripped up on that. And I was like, I don't think you can. I don't think you have the ability to make a human-like judgment over a thing.

Lenny Murphy: Yes.

Karen Lynch: Right, right. So I want it. So then I was annoyed, right? Because I'm like, thanks for the compliment, but I'm not fooled by you. So, anyway, right.

Lenny Murphy: And then just tell me what I want to hear.

Karen Lynch: Yeah. Yeah. I was like, thanks. I don't need you to tell me. I know. But anyway, um. Then another kind of sidebar about robots this week: the Knicks. We're, I'm not necessarily a basketball fan, but everybody is right now in the New York area because the Knicks. Um, and my son was showing me videos of a little robot walking around outside MSD Madison Square Garden. I was like, it's very cute. They had it in a little Knicks jersey, it was like dancing or something. It's very cute, you know, it's like it's half pint size, it's like you know, maybe like, feet tall. It's very cute. And dancing. And it is very cute.

Lenny Murphy: And I'm making them that way for a reason.

Karen Lynch: I know. And I was like, I was looking at it and I had this disconnect because I was like, it's dancing. And I had this like, again, the same kind of feeling of it's not feeling the music. So it was that same kind of cognitive dissonance of like, you can't tell me there's emotionality when you're looking at a picture of a pet. You can't tell me there's emotionality when you hear music. That's going to be the struggle for these things: is that we know better. Are we who'll be fooled? Are we going to be fooled? Is there going to be a time when we're going to start to think it's normal that they act human? I don't know the answer to that.

Lenny Murphy: That. So this week, a big Steven Spielberg movie was released, Disclosure Day. Made me think of not going there. But years ago, the movie AI. God, that's probably close to 20 years old, I guess. Wonderful movie. If you have not seen the movie AI by Steven Spielberg, it is a great movie talking about this world. That we are in, those are the questions that it was grappling with, right? That's not a far distant future that right now, the future that he was looking at is probably like in the next decade, yeah. But it tackles those issues, right? The of you know, what does it look like, How do what is the yeah, uh, and it gets deeper, and it's actually a kind of a tear-jerking uh movie at the very end, but

Karen Lynch: The uh these bigger bigger issues and we're gonna have to figure that out um yeah yeah here we are fun fun fact um Francisco Lindor in a promo for disclosure day and that confused me because I was like what movie even is that so um he is a Mets you may not know that he is a Mets and he was in a promo for it and I was looking at it I'm like what is this a promo for what is this movie I should have talked to you first. I didn't know. I was so confused. Like, he's promoting a movie that I know nothing about.

Lenny Murphy: We will maintain our agreement. I'm not there yet to start talking about this topic, but it is looming. It is coming down the pike. So, very quickly, probably within the very foreseeable future, we will have to talk about this topic.

Karen Lynch: Well, the segue could have been Francisco Lindor, but that's good.

Lenny Murphy: It could have been good, good job, good job synthesizing, connecting the dots, orchestrating. Oh, my God. That was good judgment, Karen.

Karen Lynch: So, oh, my goodness. Oh, my goodness. Well, here we are. I will not see you for two weeks because of June 19th and IIEX Europe.

Lenny Murphy: Oh, no.

Karen Lynch: Friends. I will not see you for a while because then we have 4th of July. But we will have a plan and Lenny will share it.

Lenny Murphy: We will figure that out. You won't get so lucky to avoid me. Not that it's lucky to avoid you. That came out wrong. I did not mean it that way. I mean, you're stuck with me. You're going to be stuck with me for probably two of those weeks without Karen making it better. There we go. It's amazing I've been married as long as I have because I do stupid shit like that. Anyway, all good friends. Yep.

Karen Lynch: That's it. Happy weekend, everybody.

Lenny Murphy: Yep. Everybody take care.

Karen Lynch: Talk soon.

Lenny Murphy: Bye.

Links from the episode:

Anthropic: How Claude Enables Self-Service Data Analytics 

Stack Overflow for Agents 

Minerva publicly launched its AI platform for consumer marketers 

Pogo raised $32 million to expand its AI-powered research platform 

Quest Mindshare formally joined forces with Detect 

Blue Marble Research, Pye Tait Consulting, and Qa Research Unite to Create Navigator Insight 

NIQ launched Product Intelligence 

QuestionPro introduced a headless architecture 

StatSocial launched Digital Twins 

LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation of Likert Ratings 

Synthetic data is everywhere, but is it any good? 

Survey Labs launched Populations 2.0 

Measure Protocol launched Measure Predict 

Weis Markets adds Instacart AI-powered shopping carts to stores 

MFour - Consented, Connected, Omnitraffic 

What AI Recommends—and Why: Inside the Logic of “Best” Product Choices 

Agentic Commerce: A New Opportunity for Innovators