Tech Meets Retail: Omni-Channel Shopping and AI Disruption

Check out the full episode below! Enjoy The Exchange? Don't forget to tune in live Friday at 12 pm EST on the Greenbook LinkedIn and Youtube Channel!

Karen and Lenny dive into the latest trends shaping consumer behavior, retail technology, and market research. Learn how omni-channel shopping is transforming retail, why augmented reality has yet to capture mainstream attention, and how AI is driving market research growth.

Plus, discover new opportunities for freelancers in the insights space and hear about innovative tech solutions like smart jewelry and wearables. The conversation also covers the legal implications of using copyrighted data for AI and highlights the critical balance between technology and human expertise in the future of work.

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Lenny Murphy: And we're live.

Karen Lynch: And we're live. Hi, everybody. Happy Friday.

Lenny Murphy: Yeah. So I'm going to jump out and whenever you guys want to start, you can.

Karen Lynch: All right.

Lenny Murphy: Let's do it. Hello, everybody.

Karen Lynch: Hello, everybody. Happy Valentine's Day, because we're pre-recording, but you're hearing it today on February 14th. And in the US, that's Valentine's Day.

Lenny Murphy: We love you. We have those little candies, you know, that you gave out in school.

Karen Lynch: We hand them out to all of our listeners. We should, for next year, get branded Conversation Hearts that say The Exchange and hand those out.

Lenny Murphy: You see, you're brilliant. But speaking of love, before we started, the gods of the internet were not necessarily loving me. We were getting some disruptions. We should probably dive in while it's not glitching out.

Karen Lynch: Yeah, we're gonna dive in. And you know, this is one of those weeks where kind of consumer shopping behavior really popped out of me this week. Those were some of the things in my feed. So I thought, you know, two different articles talking about consumer shopping behavior. And I thought, let's just start with that. Because I don't think either of these two stories are going to be earth shattering for anybody when you put your consumer hat on, you know, every now and then I like to see myself in data. So the first piece that that I had come across in this context was this PepsiCo, PepViz report about omni-channel shopper growth and talking about, you know, kind of the shifts in consumer behavior and really saying that they're going to a lot of places, right? I think, forget what the stat was from that article, but they are not, I think it was like upwards of 15, you know, different places to shop across the ecosystem. Ecosystem. And also, pigeon tailing onto that or dovetailing, which one is it? Adding on? Dovetailing? What's the difference? I think pigeons and doves are basically the same thing. And the other article talks about, you know, the trend of hopping, you know, so the idea that you would offer groceries and you hop from store to store, or you're making decisions about, you know, maybe I'm doing curbside pickup for this but I'm going into this store and I'm having this one delivered. Just the vast variety and diversity of how people are shopping in particular for food and beverage. It's so interesting. I don't know if you can see yourself in these two pieces.

Lenny Murphy: Yes. Oh, wait, there's multiple places that we, even out here in the boonies, right?

Karen Lynch: You include farm stands in your regular.

Lenny Murphy: Yes. Yes. I mean, yes, absolutely. There's probably our weekly shopping consisting of at least six different companies, including online. So not so much delivery, although, like Amazon, yes. So let's turn to the research stuff. The issue there is, look at companies like Walmart that are building very robust or Kroger 8451, Dunn-Humby, you know, through Tesco, but they're only capturing a channel, even though it is omni-channel. So as sophisticated as that is getting, the ability to collect shopper data within a specific retailer, this type of choice says there is still a need to try and understand Pat's purchase and the consumer journey and all of that, that sits outside of these, these retailers that are leveraging their data really effectively. Because we consumers are complicated things and we make different decisions. Yeah.

Karen Lynch: Well, this was cool. I hadn't looked into Pepsi, so I didn't really know that Pepsi was collaborating with retailers in that way with their own data collaboration and sharing out to their, again, retail partners. I'm like, all right, that's cool. A little business model that I didn't know PepsiCo was doing. So, you know, pretty, pretty neat. We're in an age of data sharing, right? So speaking of Walmart, and all that they're doing, and you know, it's, it's not on the retailer side, it's in the other direction as well. It's super interesting.

Lenny Murphy: Yeah, absolutely. Well, and I don't think we include this link in here. But we can give a shout out that, you know, because Cercana announced the expansion of their shopper panel. And first you think, Oh, why? This is an example why those companies that are building large shopper panels, Numerator, all of those folks that are capturing purchase data are absolutely still important parts of the ecosystem. Yeah, yeah. Yeah, it's pretty cool.

Karen Lynch: So speaking of shoppers, this piece you found also really interesting from a consumer behavior standpoint study just showing the adoption of augmented reality. Interfaces. So stats on that are that adoption remains low for augmented shopping apps, right, or augmented reality shopping. It says that 66% of US adults are unaware or uninterested or just not using, you know, AR shopping apps, or at least that feature in the apps that offer them. But I think what's really interesting is that it is down from 83% just a few years ago. So even though the headline of the article says it remains low. I mean, the drop from 83 to 66 in just four years, five years at the most, I think it is, from 2019 to 2024, that's when this study was kind of shared. Anyway, I think that's kind of interesting because we're getting there.

Lenny Murphy: I think they just haven't found the killer app yet, right?

Karen Lynch: I mean, there's the only factor that would Yeah, putting a piece of furniture into your living room or something like that, or putting a, I think I just put, oh no, I just did it. I just did it with just one bottle. No joke, I put it on my coffee table when I was sitting on my couch with my Amazon app, and I put this on my coffee table, and then I took a screenshot and I sent it to my kids, because I said I'm getting on the, you know, a wall bandwagon, which my Gen Z daughter was going to be proud of me for.

Lenny Murphy: So. We've tried it here or there, some of the painting stuff, right? With home decoration, but no, not extensively. Even the kids were playing like Pokemon Go, right? Those types of things, or Minecraft had an AR, was it Minecraft World? I think a novelty, interesting, fun for a little bit, but nothing that for us, found, like, this is invaluable in my daily life. And now my wife, she will use it, she does the reskeet, reskeet. She, she will scan, I know, I can't even talk.

Karen Lynch: We're recording this early, guys.

Lenny Murphy: She will often do the barcode scanning and look across multiple stores for comparative shopping. I don't know if that's quite augmented reality, but I think it's at least in the ballpark. But yeah, sorry, I'm going off in different directions. It's about the killer wrap. So what is the invaluable thing that just makes our lives so much better? I think that's probably the challenge in here is just finding that consistent solution that is just, I have to use it every day because it unleashes value for makes my life easier saves me money does something of that nature

Karen Lynch: Right but you know if you're if you are looking for you know again in my case it was a water bottle what what difference does it make if my water bottles on the coffee table with the other a wall of water bottles which was the joke the inside joke but if I was looking for a new coffee maker I might want to you know fill it up see what that one looks like on my counter compared to the big footprint or you know things like that like I think home appliances countertop fixtures that makes a lot of of sense to me. Pillows for my bed, that may make a lot of sense to me if I'm not going to, you know, home goods or wherever else I might buy new pillows or something. So I think there's certain, in that kind of home category, certain use cases that, yeah, I can totally see myself probably in the numbers of, you know, the 15% that are already there.

Lenny Murphy: Yep. Yep. Absolutely. Absolutely. I also thought it was interesting.

Karen Lynch: I don't know if you saw this, when you dug into that data, into that Um, article, I mean, the data was provided to e-marketer, which is where the article came from by civic science.

Lenny Murphy: So shout out. I did. I didn't catch that. So, oh, all right. Yeah. John Dick and, uh, and, and team. So very cool. Um, pretty cool.

Karen Lynch: All right, cool.

Lenny Murphy: Well, do we want to talk about industry activity? Because there was some interesting stuff this week. Yeah.

Karen Lynch: And this first one, you, you spotted this one, uh, I think in your LinkedIn newsfeed. About field notes. And I just thought, like, this is really great. So Giuliana Romano shared that smartphone qual platform field notes, right, open free access to both freelancers and job seekers. So letting them kind of run whatever sessions they may want to run, do their own research, like share their own kind of thought leadership studies, maybe like whatever they want to do with it, they can do with it. I thought, well, there you go. That is not only generous, but certainly, um, generous in spirit, but certainly, you know, a great way to raise awareness of your platform by giving people free access to it. Um, whatever pro bono projects you might want to be working on. Like, I just thought that's really cool. Good for them.

Lenny Murphy: So, and this in there, uh, so I didn't look at it at the application. In itself, but I thought there's also, my impression was an opportunity for collaboration for freelancers to, oh, I need a moderator or an interviewer for this and this network of folks, of users could pop in, oh, you know, hey, I'm free and I'll go do that.

Karen Lynch: And Julia, she shared on the, kind of in the comments when you looked at them, they're going to be, you know, doing some intro sessions for freelancers. Finder on LinkedIn, we can provide that link probably. Get it by the time tomorrow this gets live. And anyway, so join that info session, check it out. Again, freelancers and job seekers, I really liked that part because a lot of times when you are in the job market, from what I understand, people are looking for ways to just keep momentum going in the field so that they don't start to get into that depressed spot but look at me, I'm still doing stuff, I'm active, I'm contributing, and that momentum helps propel you forward to your next position. So I think it's a really, really value-added thing. Of course, I also am quite biased because I'm on the board or sit on the board for Green Book on the Insights Career Network. So I just kept thinking of all of these people that that's going to be such an asset for us, so.

Lenny Murphy: Absolutely, absolutely, and a great way to kind of re-skill and, you know, as well as things evolve. Yes, yes. Yeah, no, very hats off field notes.

Karen Lynch: A very cool idea.

Lenny Murphy: So very, very cool.

Karen Lynch: Yeah, get why that was a surprise.

Lenny Murphy: So resource tech, I'm gonna get why another 8.4 million in funding, bring this total to 64.5. Right? Which was the numbers like, wow, okay, I did not realize that they had gotten so much venture funding.

Karen Lynch: And I think that their last round was just in July of 2024. So that's at least what I had seen. So six months later, or maybe not six, eight months later, they're getting even more.

Lenny Murphy: So what does that go to show you? Yeah, shows are growing. Investors try not to throw good money after bad. So when you see those types of rounds, it's because there is growth. Strategic plan, that is, accelerating, could have been somewhat bridge, you know, funding for transaction, don't know any of those things. But it's a, it's an example that the technology companies continuing to flourish in, in this era, not all, but obviously, get why appears to have found a really good niche. So it was interesting.

Karen Lynch: That's off to them. So one other thing in this article, again, it's deep in there. I think it's way at the bottom, but it's a stat that I'm like, all right, I'll quote that stat at some point, but let's quote it now. I have it in my separate notes. I don't know if it's the same thing, but the market research services market size was estimated at 90 billion in 2024 and predicted to grow to 93 billion in 2025. So I don't know how that compares to other stats that you have. That was from a market analysis from the business research company. So. Yeah.

Lenny Murphy: It's all definitional, right? So market research services, what is, I mean, that, you know, that's a, that's a language issue. So, uh, if they're talking about technology, technology platforms that serve the market research industry and with a very small level of service, I'll buy that number. If they're talking about full service research, that would fly traditional service first business, that flies in the face of every other number that I've seen. But I won't, that's all nuanced stuff. We really need standard definitions in this industry so badly. We really do. To define who we are and what, and how we categorize everything. But that is the demand for insight. Yes, I will not disagree with that whatsoever. The tune of 3 billion more this year? Sure, if we factored in the growth of the, well, we'll talk about the, sorry, it is really early. The deep research, things like that, right? Yeah. Growth of these AI-driven solutions that are maybe to some extent eroding traditional research suppliers, but they are expanding the market for insights. I wouldn't hesitate a bit to say that everything is growing. The pie is getting bigger. How it's cut up, that's changing.

Karen Lynch: Speaking of that pie, that growing pie, You found this article about Read.AI and how they're partnering with ICE, which is the Intercontinental Exchange, on data sharing, right? So analyzing user conversations for financial industry insights. So that's a new, maybe that's, maybe Read.AI's rolled into there as well, right? As an insight company at this point, right? We've been talking about that for a while, but leveraging their discussions for new data but specifically in the financial industry. So cool, I like that application. Yep, yep, absolutely.

Lenny Murphy: And yes, so that would be part of the definition, right, of the expansion of that. And another way to leverage data and insights and conversation. And that's kind of social media analytics on steroids, but in a very focused way. Yeah, hats off to Read.AI. They've been very smart about leveraging their data asset, which is probably a good segue into, as we get into the AI part of our business.

Karen Lynch: Halfway through the meeting, halfway through the live stream that we should be really just focused on AI at this point. That seems about how it goes.

Lenny Murphy: All right, this first one I'll just share.

Karen Lynch: It's really quick. It's a LinkedIn post. Third week in a row, I mentioned it. Questioning Donovan Andrews. So again, if you are not following him, you should. Ogilvy Consultant who really has his pulse on the big four and everything that they're doing as well. So he's shared a post that talks about AI investment surging with 68% of business leaders planning to spend 50 to 250 million on Gen I in the next year. And to quote, reflecting a shift from experimentation to implementation, like, that's it. That was what was a nice two years. So two years to experiment. Here we are. It's time. Such an interesting post. Definitely worth checking out.

Lenny Murphy: Yep. And we've seen other numbers recently that we've cited that are very similar. We are in the implementation phase now.

Karen Lynch: Yeah. Yeah. So you found the CX article or at all? You did.

Lenny Murphy: That was the last. That's been an addition this morning.

Karen Lynch: So it was, I think there's a link in, there's a link in this next post and then there's another link in that. So there's actually, you know, two things to share here. I'm sorry, I'm doing a lot of talking.

Lenny Murphy: I'll let you take over shortly. No, I like your voice better than I like my own.

Karen Lynch: I'm sure our audience does too, so go ahead. The AI is reshaping customer experience. Are leveraging Gen AI to personalize interactions at scale. So again, another LinkedIn post. And this post, this is another gentleman that I follow who I think is just incredibly cool and tapped into all things AI at this point, but it references these top AI trends in CX work. And so the reason for bringing this up is sort of the adjacency that overlaps with all the things that we talk about in CX, right? Anyway, a lot of cool trends to talk about from AI personalization and CX becoming a profit center. There's a lot of different things being mentioned in there, ethical AI, et cetera, et cetera. And then there's another link within the LinkedIn post. So anyway, check it out if you're in the CX space. It's cool to think about not just how AI is affecting the insights and analytics industry, but our kind of adjacency of the customer experience industry, it's all related.

Lenny Murphy: Yeah, pretty cool. Well, that's a good segue then of the, you know, open AI, the new trademark filing, robots, smart jewelry, etc, etc. Expansion hardware, nobody should be surprised. I think that the promise is still from Tesla that we'll see their robots in the market this year. Here we are, guys. And as we talk about AI being this game-changing technology in so many ways, it certainly makes sense for embedding that within new electronics. I mean, a robot makes perfect sense. I've never driven a Tesla self-driving car or anything of that nature, but that fundamentally that AI was making decisions, etc, etc. We've seen the growth of these specific niche applications and abroad applications. And now we're going to see them being applied again. As we move into, you know, the iRobot world, or the matrix. I'm not sure which one. But right, the jewelry, smart jewelry caught my eye.

Karen Lynch: You know, we had talked about there was that pin, I remember that the You know, it's- Oh, we're both excited. Like, oh, that'd be so cool, wouldn't it? That'd be cool. The word jewelry specifically caught my eye. I mean, you know, here I have a pendant. Hmm, you know, that's interesting, you know, to think about the jewelry application. So we've got not just robots, but we have glasses, we have perhaps, you know, a pin, maybe it'll be in a necklace, a pendant that somebody could wear. You know, I think this article, if you go deep, it mentioned, you know, kind of headphones, right? Which reminded me I had bought those translation headphones that I could put in an earbud or ear pad or whatever.

Lenny Murphy: And it literally translates. And I experimented with my daughter-in-law.

Karen Lynch: It's a little clunky, but she spoke Portuguese and translated it to English for me. I was going to bring them to Bangkok with me to just kind of, you know, see how that whole thing could play out. Really interesting. Anyway, just something that I geeked out about from a translation standpoint. Anyway, you know, whether it's a laptop or a phone case or a, you know, a watch, whatever, the idea of jewelry and these smaller objects, right? We're not talking about VR headsets. You know, we're so beyond that at this point, although that's all a part of it. But anyway, open AI clearing the way for themselves should they want to get into Yes, absolutely.

Lenny Murphy: And, and they'll all be doing that. And we, I mean, gosh, everybody had a smart watch, right. At some point, uh, you know, and we'll just see which one captures back to our augmented reality. Uh, what's the killer app, you know, what becomes the thing that, uh, nobody, and, you know, I, interesting point. I was thinking my wife bought me a Roomba for my birthday back in 2010. Something like that, right? And it was pretty cool for like a month, and then it became a pain in the ass to maintain, and we put it up. And so I was like, I think about these, because while we were talking, I was thinking, am I an early adopter? And yes, I am an early adopter. I had Google Glass, just like Tim, right? I am. But I'm also really quick to say, eh, this sucks, and put it up on the shelf. That's the challenge as we're going through all these new introductions. There's a lot of folks that are going to get real excited and try it out and then realize, eh, we're just not there yet. So manufacturers do research to understand how your solution becomes invaluable. So you don't have people like me, they're like, oh, that's pretty cool. And then like, eh. I just threw away whatever for something that is going to be like the Betamax of our time. It'll sit in a box. They all are, right?

Karen Lynch: On some level, when I say they all, I mean even my Apple Watch. I just could never lean into wearing an Apple Watch because I didn't want to be checking texts all the time. And that was sort of the point of it. But I found myself, and I still to this day, when people are mid-conversation and they look at their wrist as if that text is more important than what we're. It's one of those things I have an aversion to, smartwatch. Me too.

Lenny Murphy: Got one, it was kind of cool for a couple months and it's like not even charged sitting up in my bedroom.

Karen Lynch: And I was like, I don't want to behave this way, therefore I cannot wear the watch because I am going to behave that way. So, you know, how would I be though if my pendant was, you know, I keep thinking of a pendant, cause it's like I said, it's jewelry, I went to get a necklace. You know, how would I, how would I feel if this was kind of, you know, doing something for me, I don't really know. I'm still keen on trying on Ray-Ban sunglasses. Like that is still something that I would like to do. And I just think there's something cool about those because I want to see the actual functionality of what they're doing. Anyway, again, maybe in North America, maybe we'll get a pair of sunglasses.

Lenny Murphy: Maybe, maybe. Oh, apologies. It is morning in the Murphy household if you heard background noise.

Karen Lynch: Well, let's wrap this up because there's two there's two one of them you alluded to earlier should share a little bit about the deep research.

Lenny Murphy: This is sort of an article I didn't get to digest at all. Well, actually, let's talk about AI training real quick because this was the court ruling. I think it was on behalf of Reuters that training on copyrighted data is not fair use. That has very, very broad and significant implications, right? So this has all been kind of boiling out there for a little while. Here it cuts the chase for us. We've been saying for quite some time that the value of permission for purpose-built AI training sets would increase as one is they exhausted everything available online, or it was shut down. Because it's copyrighted material. Here we are, that's happening. I guarantee you that the OpenAI is going, ah, shit, right? This has real significant implications for them, for those models of the general use AIs trained off of the internet. So what's the next step? Oh, well, we need to start building purpose-built AI training sets off of permissioned, owned, protected data. And if I'm a brand, right, I'm commissioning research, so I'm P&G, right, my go-to example. I'm commissioning research, I own that data, I'm gonna feed it into my own LLM, and I'm gonna build these solutions off of data I own, I have extracted, I've engaged with an ecosystem, our industry is already perfectly positioned to facilitate that type of model. I think it's what we do already. So I think this is good news for the industry. As far as we are in the business of monetizing, of collecting and monetizing data assets, I encourage everybody, we must think through that lens, because that's the world we live in. And this ruling, this court ruling, is indicative that that is true. There's my soapbox. Can I go down a rabbit hole?

Karen Lynch: Can I jump off your soapbox into a rabbit hole? Absolutely.

Lenny Murphy: You go down the rabbit hole as I step off my soapbox. So, yes. All right.

Karen Lynch: So, what my brain is thinking, and I'll get to the analogy that I'm talking about, what my brain is thinking of is I'm thinking, you know, you mentioned P&G, I'm thinking PepsiCo, I'm thinking Mondelez, I'm thinking all of these big CPG companies. And I'm thinking, their LLMs are only going to be as good as the data scientists and the coders and the developers that are working for them now, right? So, it suddenly makes me think about, here's the analogy that I'm making. When you are ever diagnosed with a medical condition, right? We both have experience with that. Somebody at one time had said to me, you know, oh, you want to go to the best hospital, because you want everybody in that machine to be the best they can get. So if you're having radiation treatment for your cancer, you don't just want the best oncologist, you want the best radiologist, you want the best anesthesiologist. If you have to have surgery, you want the best person reading the x-ray scans or the MRI scans. So you want all of the best people, which is why you go to these major medical centers like Sloan Kettering or Yale or Johns Hopkins, or, you know, like you mentioned.

Lenny Murphy: Mayo, I mean, I went to Mayo.

Karen Lynch: All of them, exactly, Cleveland Clinic. Because you go to where there's not just one good doctor, but you know the team of doctors working together, or professionals working together, are going to deliver the ultimate and the best care. That's why they have the reputation they do. Okay, back to this. These large consumer products companies, or any other kind of company that is going to be building these themselves off of their proprietary data need the best data scientists and the best developers, the best coders. They need the best on their teams in order for theirs to be the best technology to have the best results. So I think that's going to be a little race within the race. And hiring and who are you putting in place? Those are people that we're going to have to watch for those hiring announcements.

Lenny Murphy: Absolutely and increasingly that does not necessarily mean someone well, actually it probably does not mean you know a 30-40 year old person with a you know Masters in computer science, right? I mean a lot of the folks that are and we see it in our headlines I don't want to go into the details on all that but you know, we see examples of headlines of just young super smart Coders engineers. Yeah going in and just kind of a hacker mentality, right? And just, they've got these skills and they go in and they create stuff and they move fast and they do those things. Those skill sets in this world are invaluable and it's a very different hiring profile. It has implications for just how we think about accessing the appropriate resources and skills to build that vision. It's all interesting, you pull these threads, right? They're just like, wow, there's all types of interesting permutations that just change how we think about business and the structure of businesses going forward. Fascinating stuff. Yeah, cool stuff. All right, we're close to wanting to wrap.

Karen Lynch: We are. Let's just do that. You go.

Lenny Murphy: The opening eyes, deep research, really interesting thing to read. Analysis, oh yeah, there's lots of cool stuff. And it does a whole lot that, or it doesn't do a whole lot that is needed. And that it actually, that this reviewer's overall take, and I have not, deep research isn't available in the U.S., so I have not reviewed that. This person's take was it actually reinforces the need for smart humans and expertise to really unlock the value and create the process for, yes, a great, efficient process. I will say this week I was doing some similar stuff as I tend to do now, not using deep research, but trying to combine some things And yeah, it saves time, but it ain't smart, right? It still requires a human who understands the topic to really drive it to nuance. So I find that very hopeful and encouraging. This article does as well. And then if you're not too sick of listening to my voice and me soapboxing, our good friends at AYTM launched a podcast. They asked me to be on the inaugural edition of it. We recorded this right before the holidays. I went back and I re-listened and I thought, I sound pretty smart. We talk a lot about GRIT, we talk a lot about AI. And it is the culmination of this perspective, right? What we've been doing every week now for, what, are we going on for two years now?

Karen Lynch: Well, we're at a year and a half. We'll be two years in the end of July, I think.

Lenny Murphy: Right, so the only useful thing about a conversation like that, if you can get past my voice and me being annoying and an asshole and all those things, is that the opportunity to sit down and have that type of conversation allowed me to kind of focus all of the learnings and everything that we've been talking about in one place. In a more casual, you know, type of situation. So if you're interested in the synthesis of everything we've been talking about in one conversation, then that's useful. If you're like, man, no, no way in hell I'm listening to you for an hour, Lenny, 30 minutes is enough, then please don't click on the link. But thank you to our friends at AYTM for inviting me.

Karen Lynch: Yeah, cool. Very cool. Well, sir, that's our show. So I hope everyone Everybody has a great weekend, a great week ahead, and there will be a special guest with Lenny next week, because I will be in Bangkok at our APAC event, unable to make this show, because that's quite a time change. So stay tuned, and let's see what Lenny's bringing to the show.

Lenny Murphy: Yeah. All right, so we'll keep it secret, I guess. I think that would actually be fun. Yeah. Yeah. It's going to be great. I talk a lot. And every word is gold. Every single word is gold.

Karen Lynch: It's going to be a great conversation. Yes, we'll keep it secret because that actually feels really fun to me right now. I promise you, I will listen when I get back. So we'll talk about it the following Friday in a debrief. But you all enjoy the week. Enjoy the show next week. We'll talk soon.

Lenny Murphy: Everybody take care. Bye bye. All right. Later, Lenny. Bye. Bye.

Links from the episode:

PepsiCo’s Pepviz reports omnichannel shopper growth and food & beverage resilience 

Consumer data reveals grocery ‘hopping’ trends 

AR shopping adoption remains low 

Smartphone qual platform Field Notes opens free access for freelancers and job seekers 

Consumer research tech company GetWhy secures $8.4M in funding 

Reddit partners with ICE to analyze user conversations for financial industry insights 

AI investment surges, with 68% of business leaders planning to spend $50M-$250M on GenAI in the next year 

AI is reshaping customer experience, with brands leveraging GenAI to personalize interactions at scale 

In his post he links to this webinar: CX trends in 2025 and beyond 

OpenAI’s new trademark filing hints at humanoid robots, smart jewelry, and more, signaling potential expansion into hardware 

A new court ruling declares AI training on copyrighted data is not fair use 

OpenAI’s “Deep Research” automates multi-step analysis but lacks key industry insights  

Redefining market research: Leonard Murphy shares insights on innovation and AI