3 Shocking Things Happening in Research Tech Right Now

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!

From a $40 million startup collapse to billion-dollar private equity moves, this episode unpacks the wild swings happening in research technology and customer experience. We dive into why even well-funded companies are failing, how AI is both solving and creating data quality nightmares, and what breakthrough innovations are actually making a difference.

Plus, we explore everything from eye-tracking tools helping people with ALS to autonomous grocery robots that might be coming to your neighborhood.

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Karen Lynch: Maybe, there we go.

Lenny Murphy: Hello everybody. We were just talking about this kind of low energy, maybe it's going into a long weekend, whatever kind of thing.

Karen Lynch: Maybe it's not like I need the weekend to start right now.

Lenny Murphy: It does. So if you're watching this live, we'll see how this goes. But there's a lot to cover.

Karen Lynch: There always is. Yeah.

Lenny Murphy: Yeah. We usually don't start with, uh, I don't know, bad news, but this is, this is in our, so street bees, I'm sure everybody has heard about, uh, about street bees. Um, if you aren't sure, there may be plenty of people who haven't heard about street bees, UK companies, uh, took in, uh, what a load of venture capital money a couple of years ago, uh, like 40 million. Something of that nature. And today, well, or this week, they went into bankruptcy in the UK. And not just bankruptcy protection, they're gone.

Karen Lynch: I think one of the articles that I read about it was that the entire staff was made redundant, which is a very UK way of saying everyone was let go. So they went. Being, you know, being backed and well funded to not being able to secure a buyer and not being able to turn it around. So, I mean, it's really interesting. It's the sort of thing where my mind went to, like, if I was in business school at the moment, like, this would be really a cool kind of case study to wrangle about, you know, what, what happened with the kind of what happens? Like, is it just, you know, is it just because it's a volatile place to be in the research technology space? You can have a really great idea, concept, but it's hugely competitive. What's the reason? I would love to dig into this case study if I was in a scholarly place right now, because I think it's interesting. Well, I'm not sure.

Lenny Murphy: Yes, those are all interesting questions, and there is drama, I think, around all of that in some cases. I know a few folks were poking around to see if there was anything worth acquiring that I know. And they're like, no, there's nothing there. Um, like sub 5 million in revenue for a company that took in all of that venture capital money. Uh, no real panel left.

Karen Lynch: And not even, can we also just say not even, not even just venture capital money, but also like bias, like a solid legitimate aspirational venture capital group, right? I mean, the Guardian is not a, you know, they have prestige to them. So I think that's the other thing is where, you know, what I'm wondering about you and I and connecting dots and all that, and I think it's still too soon for us to really tell, but what does this signal to other investors who right now we've been talking about investment dollars and how they're, you know, we keep saying, follow the money, follow the money, And then something like this happens. And in that world, sometimes, sometimes the investments don't pay off. So anyway, that's what I find really interesting about this is that, you know, damn, yeah, sometimes it doesn't pay off.

Lenny Murphy: It doesn't pay off. And that's, you know, did to follow on with your connecting the dots, right? I mean, there's a lot every week we cover some pretty eye watering dollars flowing into business especially early stage seed rounds. And the reality is that investors are smart. They're certainly not dumb. They don't throw stupid money at things. They think there's a reason, but not everybody wins. Yeah, not everybody wins. For whatever reason. Yeah, for whatever reason.

Karen Lynch: Let's talk about Variant because they are in a winning place at the moment. So it's good to kind of, I think, balance the whole thing. Like, okay, sometimes it doesn't work out, other times somebody can get 2 billion, 2 billion. Um, anyway, I don't know anything about parents, but, um, but they're in the CX industry. So that was interesting too, because I'm like, okay, CX, I see.

Lenny Murphy: Well, it's more to me, it was more, it was Tom abroad. Well, so very, very, um, back in the day they bought, and I, so sorry, I don't recall the name, but there was an early stage kind of CX-oriented community platform, research platform, that became part of Varent. So their roots are in what I would consider research platforms. Absolutely. Now they're being acquired by Tama Bravo. Now Tama Bravo, and I actually just looked this up to make sure that I had this right, When Tama Bravo has acquired Medallia, Variant, User Testing, User Zoom, JD Power. So, Tama Bravo's private equity group is obviously acquiring many assets that exist within the broader CX space, right? But yet they're not combining them. They have a large portfolio. They have a very large portfolio. They're a big company, right?

Karen Lynch: The big private equity group. I wonder how many people, sidebar, I wonder how many people who watch The Exchange or listen to The Exchange do what we do every now and then, which is like pull up a website real time while we're talking to check something out.

Lenny Murphy: Right, that's what I was- You and I both did it and it's our show. Yes, yes. I want to make sure, because I had in my head that Tom Bravo had acquired SurveyMonkey, which apparently they did not, that was, I was imagining that. But the point is, here's a private equity group that is quadrupling down on various dimensions of insights and leveraging customer data in a variety of ways from a platform standpoint. But not doing the roll-up strategy, which is what you normally look for this type of thing, if they're going to combine them and you get synergies, and there's no indication of that. They're just holding these companies. Yeah. But that's interesting. Yeah. We'll see as private equity will continue to make those bets on inherently technology platforms, all of those have been really technology platforms that are embedded into how businesses engage and understand customers. So yeah, it's interesting. They're spending about $2 billion. If you're not familiar, let me give you a little hint here. Private equity does not value businesses the way venture capital does. So private equity, it is a numbers game. And it is driven by performance. So primarily EBITDA. So there is a multiple, and there's various things that dictate how that multiple goes, the key one being ARR, annual recurring revenues, which is why they're like platforms, like technology companies, because they have ARR. So $2 billion for a company the size of Rent, that's not stupid money. That's a very successful business that already has significant, uh, revenue, uh, overall, and they're banking on that continuing and accelerating. Yeah. So good stuff.

Karen Lynch: And it happens to be in the CX space, which is, you know, kind of a good segue into, um, for stuff that just dropped their 2025 state of CX report. So, um, you can check that out though. Um, you know, obviously there's a lot, there's a lot to digest. In a full report.

Lenny Murphy: I have not pulled it up, but... It's a lot about data privacy. So that's what caught my eye on that, is that what they stressed was the issues around data utilization by companies within CX. So there's some real nuance there. They picked up that a lot of customers are rethinking, well, no, just because as I called you, I'm your customer, doesn't mean you get to use all of my data for all of these other things. So there's a real thread in that of just consumers starting to recognize, I'm giving you my money, but now I'm also, but you're making even more money off of me by my data, and I'm not sure how they feel about that.

Karen Lynch: So it- to trust. In your, in your, you know, in the world of CX, you know, how much of the experience is contingent upon trust? Yes. I trust that something will happen or I trust my data to be secure. Um, you know, I trust when I order off of Amazon that I'm going to get the package that I want, for example, very quickly. That's it. That's why I would do that. Right. Instead of shopping local or whatever, I give it to them, give it to the big guy because I know it'll get here if I want the same day. But if they mess with me from a data quality standpoint, then suddenly the same trust arrangement has different parameters. And now I'm like, and now I'm not really interested in that because I trusted you for this, but I didn't, I didn't know that meant that I was going to lose all confidence in you for this.

Lenny Murphy: Right.

Karen Lynch: I didn't sign on for this other piece.

Lenny Murphy: So yeah, yes. So, trust is a competitive advantage, which we've talked about in other ways, to bring it back to the research world, right, if things just become more automated, whether it's the consumer, whoever it is, right, the buying process changes. Trust becomes a bedrock principle, right? I'm more likely to go with the company, regardless of what it is, that I already know, as long as it can deliver on the other things that are important to around technological parity and features benefits, but trust is a core driver and that stands out in that report.

Karen Lynch: So let's go to the next story that we have to share with everybody. Yes, our friends at Repdata.

Lenny Murphy: I mean, in the best possible way, Patrick and team. They put out some work.

Karen Lynch: This is actually the link that Karley can share with you when we get through the links to a LinkedIn post where they're talking about, you know, the survey and some of the results. So it's a really nice kind of briefing on this survey that they've done where 33% of survey entrants are fraudulent. It's a bold statement. Research and, you know, also going on to urge researchers to kind of rethink their processes, protect data integrity. And there's a lot we can talk about later in this episode today, but, you know, we cannot underscore the amount of work that brands are now doing to ensure data quality. I mean, we saw, you know, Tia, Tia and her team at P&G are doing a lot too, I think the quote from her in that talk was, I treat data like a crime scene.

Lenny Murphy: You know? Probably. I love Tia. She's bulldozed bunches.

Karen Lynch: Gosh, my favorite quote of all time. I think I might have quoted it in an article since then too. I love that quote so much and I spot it. But the whole idea that we're now suddenly, the brands have to do a lot of work and they're not really happy about how much work they have to do. But if 33% of survey entrants are fraudulent and they know it, then you've got to prove your worth that you are protecting that data, doing what you can, validating it, whatever you can do. Getting harder and harder. Once we get to some tech developments, we'll talk about why it's going to be even harder.

Lenny Murphy: Well, on this one, I was looking away because I was trying to find a term that they use, and I forget exactly what it is. But it's something I'm going to paraphrase, good looking. So this 33%, it wasn't the obvious stuff, right? A lot of these were responses that passed the initial flag sniff test. But when you scratch the surface, then realize, no, it was still fraudulent. Um, it was not real people giving real, real opinions. Um, but they looked okay. And that's a whole other, you know, it's like if you're buying a synthetic sample, that's one thing, right. But when you're buying a real sample and it's, it's basically synthetic, well, that's a different thing. Uh, and, and I think, yeah, it's just an interesting world.

Karen Lynch: Yeah, it really is. Yep. Well, that's the big picture. There's a ton of product launches and new feature launches. There's so many. And, um, this isn't even all of them, but I had to stop somewhere. Cause I was like, all right, we can't just talk for, well, we could, but we're capable, but you know, we're not going to just talk for an hour just on product launches. So, um, we're just going to start rifling through some of these, shall we?

Lenny Murphy: Yeah, absolutely.

Karen Lynch: You want to talk about cloud introduced and moderated research. Software, integrating qual and quant. You know, I think that that's when we share these links with one another, just, you know, looking under the hood, everybody is, you know, you click on them, and then you kind of look at them like, Alright, this one already has a great solid interface. I haven't done anything like a demo or anything. But I'm like, Alright, I get it. And moderated research software is here, friends, and got to check them all out to see if it is to see what, if you're a researcher, if you're a qualitative researcher, if you're a DIY in-house researcher, see what's happening out there and see what your competition looks like, because...

Lenny Murphy: I would argue everyone that we're talking about this week, other than Real Eye, which we'll get to, all the rest, it's some variation of...

Karen Lynch: A variation of a theme.

Lenny Murphy: Yes, yes. Uh, which, and I have to say, this is so interesting because I'm trying to wrap my head around this, but the, uh, that is the low hanging fruit use case from an efficiency standpoint. And it always has been right. The, so, uh, and to achieve product parity was your competitive set. Yes. Everybody has to do this. There's no way around it. Um, but I, it, it amazes me that I think we're already at the commoditization stage and that's for everybody out there. That doesn't mean all your, your, your business is stinky. I don't mean it that way at all. I just mean when everybody. It's so easy to launch these products and everybody's doing it because they have to, it's the right thing to do. Um, but it's quickly already becoming the, the digital qual, uh, component, a moderated qual component is quickly becoming like the car has a steering wheel. So, where's that leading businesses from a differentiation standpoint? I think those are going to be the really interesting challenges that companies have to get to really quickly. It's not about features because features are just too easy. Absolutely.

Karen Lynch: So, yeah. So if you do the, uh, the next two on our list, net quest unveiling, you know, Lendi Discuss, an AI-powered platform. Discuss, adding features. The Discuss one is really interesting because they are, you know, blending AI-led and human-led research. So, you know, more of the same. But they're also talking about vibe coding in their positioning, which, you know, every time I think about that, I'm like, you know, that's great in the tech world. So, like, of course, hats off to you because we know what you're talking about here, using the tools, but all of these companies that are doing this, that are launching these AI versus human components or complementary parts, it has to be wrapped up into something else, to your point. It has to be wrapped up into something that, why is yours better than someone else's? Because the answer may be, it's not. These are all just- From a technical standpoint, right.

Lenny Murphy: To trust. You know, I think the team will increasingly be important here as well. The trust, you got my back. Right.

Karen Lynch: The execution details, the quality of your communications, of what you're pulling out, the ability to take a look at it and think critically and say, Yes, you know, this output might be the same across these different platforms, but I am the person thinking, when I look at it to make strong recommendations, all of those things are going to have to start to bubble to the top. Otherwise, you just all, you know, using that same analogy, you all have a steering wheel. Great.

Lenny Murphy: Right. Right. Doesn't mean you're a driver. Yes, right. Yes, it's, again, listeners and companies, because we are all for innovation. We're not trying to dissuade anybody from any of that, because it's simply the way we. That's just the way it is, where you're in an arms race from a technology standpoint across the board. I just always go back to, I love the movie, The Incredibles, best superhero movie ever, truly. And the line, if you haven't seen The Incredibles, there's a line where the villain says, when everybody's super, nobody will be. And hopefully I didn't spoil it, but it's a great line.

Karen Lynch: I think it's safe to say that if they haven't seen it yet, you're not spoiling anything.

Lenny Murphy: Okay. Well, it's just great, it's a great line with the idea that, that, that unfortunately that is what happens. You reach a point with any, in any product category where, uh, features just don't differentiate anymore. And that becomes table stakes. That's the commodity. Yeah. There's other aspects, um, you know, verticalization specialization in, uh, specific business issues, um, user experience service, those things become more important, because those become the differentiators. So anyway, although I do like the vibe coding thing, guys, that was pretty cool. Discussed how to use that. Conjointly now embraces LLMs. And Conjointly is a cool company that was always very focused on streamlining conjoint studies, which is a very complex, pain in the butt thing to do. They made it really easy. Now they're using LLMs to analyze survey data. So great. RealEye launched their eye tracking tool, ReConnect. But this was cool because it enables text dictation using only eye movements. So this is one of those things like, all right, that has big implications.

Karen Lynch: I had also been reading quite a bit about this in other applications this week about the ability to use your eyes, which is something I've only seen implemented, actually. A friend of mine whose grandmother had ALS, a horrible disease, got to a stage where this was what she was doing. She could no longer use her hands to type, but she could type with her eyes. So I knew that technology was out there in the medical space, and she was. She was responding to short emails. It might have taken her a long time, and it certainly did, but she could respond. Well, it was more just where you could move your eyes on a keyboard, and if you But if you lay your eyes on the letter and hovered there for a while, it would track it. So you could type letter by letter or word by word. I'm sure there was some technology that was word by word, commonly used words and stuff. Anyway, my point is I knew that technology was out there. This is the first time I'm seeing that kind of eye tracking text dictation all wrapped up. And I think it's a great example of how a company like RealEye, who's pretty innovative for the work that they do, also tracks what technology that's available in other fields. I mean, look at those fields. It's phenomenal. Lenny, sidebar, my father has Parkinson's. There are shoes that we experimented with this week, not terribly successfully, which is unfortunate because he's too late, I think, in the game. But for people that start to lose mobility, they send a pulse up through the shoe to help free up the movement. And you think about, OK, those sensors in shoes, that's cool. Is there a research application for that? Absolutely. Like put a sensor in my shoe and you're going to track how I walk through that store, where I stop, you know, what which aisles I look at, which packages really get my attention, where when do I, you know, just loop around an end cap or window or, you know, all of that. If you look at some of those dynamic medical breakthroughs, there are some really cool potential research innovations. So absolutely, that people go check out what you can check out.

Lenny Murphy: Anyway, I do. Yeah, well, and I think we're gonna. I think that we will include the new wearables article in this one. I mean that in so that's that that's an obvious application within wearables, obviously meta keeps investing heavily in that. And if that's added in that you're, you know, controlling the interface with your eye movement, um, uh, to go through scroll through screens or to reply to surveys or whatever. Towards the tour.

Karen Lynch: It's like, like the very last thing on our list, Karley, just in case you're like, what are they talking about now? But yeah, I mean, and, and I'm also at this place where I'm thinking, how many shops did I do where I literally had to walk behind somebody or adjacent to somebody. And then when they stop, say, tell me what you're thinking. What are you looking at? What's catching your eye? And I have to interrupt the buying journey, have these qualitative conversations with them. But if we can get these glasses then now we also have an A.I. Dialogue, an A.I. Chat, like you've stopped. What are you looking at? And have that kind of same thing. Just have a running transcript of the person's thoughts as they're going through the store. You know, I'm in the produce aisle, but I'm thinking about what are the other things that I need to to make this meal that I'm making, like all of that potential insightful journey data.

Lenny Murphy: Yeah. Really?

Karen Lynch: Yeah.

Lenny Murphy: It's amazing stuff. Hats off. Hats off, realize, uh, expanding, you know, those, those use cases that, and that's cool stuff, right? When we, we find something that has applications, uh, broader than just research, uh, overall. So neat stuff. Uh, I guess finally side X, um, asynchronous video interviews. So like, that shift from the survey to the video, uh, that's inherently qualitative in form factor, if not in, you know, definition. So yeah. Yeah. Let that pace of transformation continue. Uh, all right. You want to get into some of the And I sit there and I think like, yes, I want to get there.

Karen Lynch: I also kind of want to, um, bump to the last one on this list, this nano banana thing. Because I feel like, I feel like there's a segue if you let me, if you let me go. Um, go. So Google has built this, uh, nano banana. And for, for a brief period of time, it wasn't sure it was like somebody on the Google team or whatever, maybe had a beta version that wasn't quite right. Uh, you know, this was part of the conversation that I was having in my house this week because that's part of what we do anyway. Um, but if you, if you look at the use cases of this imaging tool, it's an image tool. It's basically taking an AI image, you know, an easy way to get people. If you take a picture at the beach and there's other people in your background, you just want the water, pluck those people right out of your image, this tool can do it. But it's also like, here's the product shot, but that's not the background I want. I'm doing a table setting and that's not the right tablecloth. Like you can edit the images for your product shoot, you can edit your images for a lot of different use cases. And the reality of this is as I'm looking at And as I'm thinking about the video interviews, and I'm thinking, just when we think in the world of data quality, at least if we take some extra steps to validate the human being. I see where you're going. At least we're going to feel secure and confident. And then we have the ability to manipulate images and videos like never before. And so if you're relying on that, and I know some companies that are, that are relying on photo uploads to confirm that you are who you say you are on a screen or that you're really using a product, you can't do that anymore. Here's my medicine cabinet, put a product in it. Here's my refrigerator, put a can of Coke in there, and now I'm a Coke drinker. We have to recognize that as this AI progresses, the data quality measures we put into place might not be working today as they might've been a month ago. A month ago, we might've said, oh, phew, you cannot do that. If video editing has gotten this far, you cannot trust. It's really hard. Anyway, that's where I'm at with this. So like the video interviews and stuff, you know, we've seen people blurring their backgrounds. So we know that the capabilities are there for me to not be in this office, but to be somewhere else, to not be in one store, but to be in another store. That's why I said this is a hell of a show today, because I'm tired, and I'm pessimistic, and I'm not usually pessimistic, right?

Lenny Murphy: Just a lot of data quality stressors right now. It is. Yeah. I don't know what that's about. Sorry. I'd like to think that the solution to that is to be more real time, because maybe we're not quite there yet where that's able to happen. Um, but I'm not, I wouldn't bank on that being part of this, uh, at least a long-term solution. Uh, I, I agree. It's what does that come down to? Right. Trust engagement. Um, And you have to keep this innovative mindset that I always fall back on.

Karen Lynch: You know, I, I'm encouraging people go check out this, check out this, get that innovative mindset going because there have to be innovative solutions that are Iterated upon regularly like okay, you've got data quality master grant now good for you Are you are you looking ahead to what data quality needs you're gonna have in three months? Get on those or six months or a year from now like you cannot it's You have to just stay focused and innovate to try to figure out how you're gonna get ahead of what AI is making possible and You must say yeah you're a buyer and as Synthetic becomes more and more accessible and more and more Good.

Lenny Murphy: Yeah, right And you're faced with these choices of understanding, you know issues from a trade-off standpoint in terms of cost You certainly get to the point where you think you know what? 80% for this specific issue this business issue 80% of uh, of, uh, good enough for 10% of the cost.

Karen Lynch: Yeah.

Lenny Murphy: And I don't have to worry about all of this bullshit from a quality standpoint. Yeah. That, that becomes part of the equation that is part of the buying equation.

Karen Lynch: So the, uh, and we, and we just have to recognize that, um, uh, there's still, anyway, it's a whole other thing, but let's, let's, Let's stay with the complexity for a minute and just bounce up to the DeepGram and AWS partnership because this is why. As we're doing this show, I'm trying to say, Lenny, I don't know. I'm feeling whatever. This is why. Here's another one. DeepGram, Amazon Web Services announced a partnership to scale voice AI capabilities for enterprises. Is capturing or data capturing via voice. So you might think, oh, cool, better transcripts. Like, that's the obvious one. Like, oh, yeah, great. If something is capturing our voice right now, our conversation, we're going to have better transcripts, which means we will have better synthesis, better results. So that's like an obvious research kind of capability that could be good coming out of stronger voice capture, right? There could be better translation options. Like I think about if somebody's speaking in a different language and right now some of the tech options are kind of crap for understanding somebody speaking in a different language. So that may be better. But also then there's something else and there's all this data capture, voice data capturing. And is that really the way you have to go? I mean, do we, I know that investment companies right now are doing voice matching to make sure you are who you say you are with voice matching. I don't know whether that can be hacked too? Like, I just, we're in this world now of all of the things that we used to think were these biometrics that we're differentiating, you know, and helpful from a data integrity standpoint. Anyway, here's another layer of Now, let's think about voice and what does this mean for voice in the future?

Lenny Murphy: Right. And to be clear, this is AWS, which is critical infrastructure for business for a huge chunk of the world. And this technology is being embedded and enabled now across the AWS ecosystem. So this isn't just a single thing. This is a scalable solution that can be easily adapted. Across multiple businesses now. Yeah, it's a brave new world. So now all of these, anyway, yeah. So it's just all a part of this.

Karen Lynch: Like, you know, you think about, okay, we're looking at, you know, image manipulation for good, great for marketers, maybe not so great for researchers. You're thinking about, you know, video, can video be manipulated? We know that it can. You know, great for creatives, maybe not so great for researchers. So, you know, and then you think about this voice, great for researchers. Is there the other side of that? Which is maybe not so great. You know, we got to figure that out. And will voices be, will voice recognition be the next, you know, point of you are who you say you are? Or do we have to go right to the eyeballs? Right to scanning the eyes, everything.

Lenny Murphy: Maybe. But, you know, there's also, When authenticity and quality and engagement is paramount, there are tried and true methodologies that work for that. So I am not seeing that the era of traditional in-person qualitative is ending, right? It's not. It's still very much the right thing to do. For a variety of business use cases and business questions and continues to to do you know it may not you may not use it for as much as you used to but it's still a good book of business that is in-person you know research and we may we may see more of that uh uh so interesting I want to touch on this microsoft thing um because this is kind of I'm sorry, I got to say it's kind of what I told you. So, um, the, uh, the Microsoft unveiled their own AI and AI preview, uh, full first fully in-house foundation model. Um, and supposedly it's already a parody with, with most of the other platforms. Now here's the, I told you so, um, which I don't mean it that way, but the, you, we, Cannot assume everything needs to be based on chat GPT. Yeah They were first out of the gate. They got the first move advantage. They got widespread adoption. Absolutely, but Microsoft Runs the majority of businesses on the planet period so and if they have their own homegrown solution and It is integrated into their platform that's what people are going to use. So as we've talked about the shift towards an agentic future and procurement and business and et cetera, et cetera, and I'm the first one to admit, I used Copilot once, thought this sucks and I wouldn't use it again, right? But now I'll look forward to trying this. And if they deliver the need, then all of the work that you've done to date on these other platforms, It doesn't mean it's useless, but you're going to have to standardize on what business standardizes on. And my bet is always going to be it's Microsoft first, Google second.

Karen Lynch: Yeah, yeah. Well, Google, it's not in our brief currently, so this won't be, unless you find it, Lenny, at the same time, I was getting, you got it, the report of all the AI, the Horowitz, the report of all the- That's next week.

Lenny Murphy: We'll talk about it next week.

Karen Lynch: Not next week, but spoiler alert, there's a whole lot of Google in there. So, like, they are really, like, if you're working for Google or Microsoft right now, and you're in the Insights space, like, have fun, because you're in an arms race all around, because, you know, that fight is real. There's a lot going on with those two giants. Right.

Lenny Murphy: There's just so much more going on. So everybody, sorry, I sound obnoxious, told you so. I didn't mean it that way. That's a crappy thing to think about. About. Just be aware that, you know, this is moving so fast that we just keep it directed to because it wasn't directed at me.

Karen Lynch: I don't know if it's directed to our audience. I'm like, who in general?

Lenny Murphy: Oh, I've had the conversation with a few folks.

Karen Lynch: I don't know if they're listening or not. If you're listening, he's not talking about you.

Lenny Murphy: He's not talking about other people who shall not be named somebody.

Karen Lynch: Into it with Lenny about this.

Lenny Murphy: I just don't, I'm just not going to, I'm not going to count. I'm not betting against Microsoft. I have many, many complaints about Microsoft in many ways, but the, uh, but I'm not going to bet against them. Well, you know what?

Karen Lynch: I'm not going to bet against, and this is how we're going to wrap today. I am not going to bet against the little robot that now might be delivering me my food. There is this concept of a Robo Mart that, you know, that we've talked about before. I was such a big fan of, you know, Instacart when it came out. Still am, actually. I mentioned it this morning. Like, I really want to do Instacart because I need food and I don't want to run out because I'm really, you know, kind of tired today. Anyway, this little robot cart can, like, drive through a neighborhood so you could have ordered your food and then just up here on a little robo cart, probably not here. This is probably not the neighborhood for it. But in certain neighborhoods where there's, you know, density and volume, like, you could just go outside and, like, punch in your assigned key code, open it up, and there's your groceries. Delivered by a robot, probably shopped for by a robot, now delivered by a robot. Not dropping from the sky. Like, for a while there, we thought all our Amazon packages were going to drop from the sky. It's not what we're talking about. This is, like, a drivable thing. So check out this little RoboMart. I think it's so cute. This little rm5 autonomous food delivery locker is so cute. I'm like, all right I'd walk out to the curb and get my groceries from a robot like It's pretty cool. I think it's pretty cool right in an urban area.

Lenny Murphy: I mean it makes and it makes the perfect Campus, you know, I mean there's so many uses like of course Right. Yes It's a no-brainer. So fun to end on a robot note. Yeah, I wouldn't see that one as becoming a robot overlord yet.

Karen Lynch: So the RM five was it on this call where I was I was talking about like telling my mother like, I'm not I wouldn't like hate if I had a little R2D2 around here that just like, I really I think maybe it's the like short little code like, you know, little little RM five driving around our neighborhood. I'm down.

Lenny Murphy: Yeah. Yeah.

Karen Lynch: On that note.

Lenny Murphy: So next, next week though, next week we have, it's our hundredth episode.

Karen Lynch: Oh my gosh. It's our hundredth episode.

Lenny Murphy: I don't think we've quite decided exactly what we're going to do, but it probably will be something a little different than, uh, than this. Um, although I already have like four articles for next week, uh, in the queue, but, uh, And you can write them too.

Karen Lynch: Write them today. It's the minimum over the weekend. What do you, what do you want us to, to talk about 100 episodes. I can't believe I've had 100 public conversations with you.

Lenny Murphy: I can't believe I've talked to you 100 times.

Karen Lynch: No, it's the public. Now we've had a few where, you know, other people have stepped in for one of the other of us. So, you know, we have had a handful of those. But yeah, like that is so significant to me. That's like the most significant thing. I think that it's going to be a momentous day.

Lenny Murphy: It is we should shout if you haven't taken grit. This last weekend closes on Sunday, I think So Karley if you want to throw that up Seriously, this is an important one guys. We're doing all this change. That's what we're trying to capture and want to quantify it. So please do that. Also, if you haven't checked out our new buyers guides. We just released the latest ones this week, very cool for those who because we get, why am I not in there? If you're not in our ecosystem, you don't get included. We can only talk about the companies we know about, and the way we know about companies is you're in our ecosystem. So it's all right if you look at it and say, why am I not there? I should be in there too. You got to at least be in our directory, because that's what we draw from. That's how we build it. So keep that in mind. But they're very cool to help buyers. They're an extension of our Insight Tech Showcases, trying to help buyers, everybody, understand what's happening in specific categories and the companies and all that good stuff. So check those out.

Karen Lynch: Yeah, yeah. Thank you, Karley. And yeah, if you want to reach out to us, the exchange at greenbook.org, I'll commandeer that because you know, it's like my favorite thing to do is show that maybe it's also because I like to see Karley, you know, shout out to Karley. But anyway, yeah, like reach out to us, let us know how you want us to celebrate 100 next Friday. So in the meantime, if you are in the U.S. and you're celebrating Labor Day weekend, have a great one, a nice three-day weekend for most of us. I would say, oh, this is almost universally, this is Memorial Day, or kind of almost universally the three-day weekends we can all count on, so. I don't think Tim, Trigger and FOMO, does that mean you're working on Monday, Tim?

Lenny Murphy: I am too, so I'm kind of like, yeah, that's great.

Karen Lynch: Let's be clear, Tim is not working on Monday. We have much to do in our house on Monday. I plan on having a weekend loaded on some good relaxation, some pool time, some grand baby time. Gonna have a good weekend. I will hopefully not be this tired on Friday.

Lenny Murphy: I hope not. Everybody have a wonderful weekend. So much and we'll talk next week.

Karen Lynch: All right. Bye everybody. Take care.

Links from the episode:

Streetbees to be Wound Up after Sale Talks Fail 

Verint Agrees to Be Acquired by Thoma Bravo for $2 Billion 

Forsta’s 2025 State of CX report  

Rep Data reveals that 33% of survey entrants are fraudulent 

Glaut Do-it-yourself platform for research teams 

Netquest unveiled Bilendi Discuss 

Discuss has added new features including “vibe coding” 

Conjointly Adds 'Deep probe' Analysis Feature 

RealEye launched Re:Connect 

The Collision of AR Smart Glasses & Live AI Assistants 

Introducing Asynchronous Video Interviews: Humanizing Insights, at Scale 

Google aims to be top banana in AI image editing 

AWS and Deepgram: The Foundation That Makes Voice AI Scale 

Microsoft unveiled MAI-1-preview 

RoboMart introduced its new RM5 autonomous food delivery locker