AI, Chaos, and the Next Phase of Innovation

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!

 

AI is reshaping the insights industry at every level. From synthetic people and prediction markets to agent-driven research tools and shifting SaaS economics, Karen Lynch and Lenny Murphy explore the funding moves, product launches, and industry disruptions redefining how work gets done.

Along the way, they unpack what these changes mean for data, pricing, and the future of competitive advantage, and why continuous adaptation is no longer optional.

Many thanks to our producer, Karley Dartouzos. 

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Transcript

Karen Lynch: There we are.

Lenny Murphy: We're live. Well, we were there's so much talk about guys. We were so ready. Like, yes, let's go live.

Karen Lynch: So we can because every now and then I get this picture of like, if we were like, you know, real, real, like, I don't want to say real, that just totally devalues not avatars.

Lenny Murphy: We are not digital avatars.

Karen Lynch: If we had like a studio, like, at one point, it was probably about 20 minutes ago, I was like, hair and makeup. And I'm like, Nope, it's not gonna happen today. Because it's that kind of a morning. And I was like, those news people, The people who have The people come out while they're sitting behind The desk and do their hair and makeup and juice them up a little bit. Like they take that for granted. I'm convinced.

Lenny Murphy: Fair enough.

Karen Lynch: I mean, you know, they'd even touch up your hair too.

Lenny Murphy: Like, yeah, they're welcome to try. I have just leaned into it, it doesn't get any better than this and it's not that great. So we're just going to roll with it.

Karen Lynch: I go with The mantra. Variety in your appearance is OK, Karen.

Lenny Murphy: That's right. Oh, gosh.

Karen Lynch: So much talk about friends. So much. I don't even know where to start.

Lenny Murphy: Well, let's do The shout outs. Let's do our plugs. Good deal. Grit's still open. So if you haven't participated, participate. This will be interesting. Like, literally, the longer it's open, I'm almost curious about the data that we may need to separate it by week to see how the changes are to some of the answers. Who took it in January versus who took it in February? Because I think there could be some differences, but please take it.

Karen Lynch: Yeah, and it's rapid. I think we extended it for a few folks that asked for extensions, and that's great. More power to those people. Get on in there today.

Lenny Murphy: Get on in there today. Also, we did extend the deadline for the insight innovation competition entrance, um, till today, I believe. So if you haven't submitted yet, you got an idea, everybody, everybody can create new things now.

Karen Lynch: So send us your ideas.

Lenny Murphy: So go, go into clock or work or perplexity. Now the newest thing, a perplexed computer, vibe it out, get it done.

Karen Lynch: You know, lovable Tim swears by lovable, lovable.

Lenny Murphy: So it's a whole other topic we'll get into. But yeah, yeah, stuff.

Karen Lynch: Yeah, you know, come to our website, we've got the AI calls for speakers, we've got registration up for North America, and I think Europe. You know, what a year we are about to have in terms of our events. I really, it's going to be a very exciting year for our events. I am just the topics that are coming in, the conversations I'm having with people, like, I am excited. We are going to have a great, uh, I mean, started in APAC, of course, but I wasn't there, so I can't really speak to that, but The rest of them I'm super excited about. So, yeah. It's, uh, did we miss a shout out or is that everything?

Lenny Murphy: I think that's all The, all The appropriate shots. Although, uh, you hate when I do this, but, uh, but, but I kind of know that I hate Well, sure. But we didn't include it here. Karley, if you can find it, there was an interview with The CEO of Simile, who we talked about a week or so ago. And their aspirations that I think is, we don't need to get too much into it, but if you get it, if you can find it, check it out. Because it just puts everything else in a whole different context. That's The company, The synthetic company that raised $100 million Series A And I'll say this much, their goal is to create a digital twin of every person on The planet. That's their goal. So we'll see.

Karen Lynch: That's hilarious. I don't know why it dropped.

Lenny Murphy: Sometimes these things are, there was so much this week.

Karen Lynch: I look confused because sometimes I do deliberately drop things where I'm like, doesn't fit the narrative. And other times, you know, I drop it because I can't get The link to Or you know, whatever. And I actually don't remember. So it might not even matter. But we have so many other things.

Lenny Murphy: We have so many other things to talk about. But I wanted to get that out there. Check out that when you get a chance. Now let's dive into the stuff that we actually did intend to cover.

Karen Lynch: So yeah, yeah, profound, who? Yeah, you know, The profound raised 96 million Series C 1 valuation, marketing infrastructure, basically The marketing platform that they claim is going to be The future of discovery. So what's interesting about this one when I Read that is brand discovery mediated by AI, which we talk a lot about here at Greenbook because we are recognizing that for our suppliers' brands to be discovered, they desperately need to be in The Greenbook directory because we are discoverable, because we have that reach. In communication with The LLMs. So, you know, I, I know this is, this is a topic of interest to us, but for all of you who are involved in your firm's, um, brand marketing, content marketing, even on The supplier side, this, this does not just apply to The big, you know, The big company.

Lenny Murphy:  It applies to everybody. It's because it's the same issue we talked about before. What, what, what brand. Mean in a world where an agent is discovering the information, right? So there is much, there's pragmatic to your businesses, but also to The research world. We are going to have, we have to get a handle on and think through what these, how, you know, supply and demand, how they connect all the different permutations that define relationships. It's all changing. There's an example that with a $1 billion valuation, a company is trying to tackle that from a technology standpoint.

Karen Lynch: Yeah, yeah. And solid, you know, not quite as much money. It's only 20 million. Yeah, yeah. Solid publicly launched after two years in stealth, which can we just say how cool it is, again, you know, just the idea that they've been in stealth mode. I love that, you know, they're helping organizations that AI systems can understand and operate on their data. I don't know much about Solid. I don't know if you know more about them other than what this press release shared. But what's interesting about this one is, I don't know if you latched onto it as much as I did, because I'm a semantic fiend, right? I have content. I love words and language. And they describe a new discipline called semantic engineering. And it says in this report, as AI becomes more capable of retrieving and analyzing data, organizations increasingly need dedicated expertise focusing on defining, validating, and evolving business meaning in a systematic way. So these semantic engineers will be responsible for teaching AI how to correctly interpret data. And then it says, and this is what I want everyone to listen to if you didn't listen to me. In the last 60 seconds, today's data analysts are well positioned to evolve into this role. I thought that's so cool, because that is one of the first statements of direct skill. What happens when you upskill? If you're a data analyst, when you upskill to AI proficiency and really lean into this, there is a role for you moving forward that you need to recognize that, to me, feels like The most important thing in this release for R&D.

Lenny Murphy: I agree with that, you know, there's a broader theme to that, right? We talked about it before, that if you are not becoming AI proficient, that the time is now, period, right? How do we apply our skills, whatever they are, right, in this world of utilizing those tools? And that's a great example of that.

Karen Lynch: Yeah, yeah. Yeah, we may come back to that once we get to the final two articles that we want to spend a lot of time on. So, because there's, we're going to connect some threads. For y'all today. So we are TBD because I was like, all right, TBD.

Lenny Murphy: So prediction markets, um, been a big fan of prediction markets for a long time. The, I mean, all the way back to The brain juicer days, right. They used prediction markets or friends who knew slash consensus points. Um, but I was kind of, kind of, short shrift in the research industry. Never really took hold, but then you look at belly markets, right. And these are multi-billion dollar businesses, um, with, with a good track record of prediction. So, uh, I think everybody recalls looking at The last couple of election cycles that they were involved in and they were highly accurate anyway. So, uh, yeah, TBD is a prediction market protocol to measure verified human sentiment. Um, they're tackling The data quality issue, which kind of by default, I think that's baked into The, any of The prediction markets. So it's. Good to see another company coming out using The prediction market model and applying it to The inside space.

Karen Lynch: And what's interesting is if you, the company, The firm, which calls themselves TBD, which I just think that's clever, um, you know, for prediction market companies to call themselves TBD. But anyway, um, so we have, we have a link to The release of course, but we also have a link to www.tbd.vote. And so, you know, I clicked on it, and it is a very user-friendly interface also, where I'm like, oh, this looks vaguely familiar when we first started experimenting with that technology. And I couldn't remember the platform that, you know, before everything became, I'm aging myself here, but like, there were these platforms for voting up things all the time, right? And yes, I agree, and all of this stuff. So the platform looks very familiar to something that might have been out a long time ago. So it's super user friendly. And I'm like, All right, cool. You know, I think investors like something that seems user friendly right from the get go also. So yeah, I mean, only 3 million in seed funding, but only 3 million in The Yeah, but that's absolutely an example of where that's not stupid money.

Lenny Murphy: I mean, I say that with these big eye watering rounds. I don't think that's stupid money either. But those are good bets for something like this. There is a business application this company can scale. That's a nice, you know, I wish I had raised 3 million or so my startups, you know, to give you some runway. So yeah, very, very cool. Good stuff.

Karen Lynch: Good stuff. Alright, so where there's good, there's bad. So yeah, you know, this is not necessarily merger and acquisitions, but it is going to be, it's financially related, which is why we're talking about it here, even though it feels depressing, but WPP is planning to sell some assets as part of their restructuring aimed at countering this disruption. They admit in this press release that we're sharing that they've struggled with a growing exodus of clients and they're racing, you know, to match AI and data capabilities of rivals, and The fear that AI will allow customers to bring more marketing functions in-house, which is real based on many of The things we'll share later today also. Lots of this week, there was so much that we'll show you shortly in this space. And so kind of hear this story, internalize what it means, and think, WPP is saying this, which is a big deal. And then we'll tell you some of the, you know, innovations that are happening that they are feeling The pressure from That's kind of where I went with that.

Lenny Murphy: But, um, 100% and I think there was a broader narrative. I mean, that's, you know, obviously applicable in our space specifically that I think there's, uh, I don't think we include The link here. That's fine. It's in the news, right? But The, uh, block, The company, The financial processing company that, uh, Jack, um, whatever Jack's last name, Jack Dorsey, uh, who founded Twitter as CEO. They reduced their staff by 40% yesterday. Not because they're doing bad. They're doing quite well because they were just redundant. Um, uh, and the concerning part is seeing what these types of announcements, WPP or others, uh, The public companies, how The market responds to them. When they asked what came up, I didn't see what WPP did, but when the announcement came out from that other company from a block, their stock shot up.

Karen Lynch: Um, that's sort of The positioning of this release is that, you know, they're going to have to reduce, they say a significant part of The savings that is going to come from reduced jobs. Um, but, but yeah, the markets are seeing that. Okay, that's smart business right now. So, you know, I don't envy the people in these decision-making situations where they have to recognize what looks like smart business right now at the cost of human capital. This one's probably gonna hurt. And anyway, you know, we'll keep watching it, but this one will probably hurt a bit. Hopefully, you know, they're saying here, uh, eliminate duplication and finance and take out some layers. Hopefully, um, you know, hopefully the peers of yours, peers of ours are not impacted by this. So, but hopefully not.

Lenny Murphy: It's, uh, yeah. What do they call it? Uh, smart sizing. Um, yeah, we'll, we'll see. But, but, but here we are, we're in full disruption, right? We've been kind of up to now, like, you know, Oh, cool new stuff. The, uh, Now we are seeing The profound business impact across enterprise, not just The early adoption and experimentation phase, but now that these things are being implemented, The cost savings, The ROI, those things are being, we're seeing those now being embraced from enterprise. At The bottom line, that's The top line, and that's The cycle, and to your point, It, it, it, it sucks too. So for humans, absolutely. Uh, The, uh, uh, backed media, uh, in Philly and that bought media math, um, bought Catalina. Catalina is interesting. Kelly is kind of an old school company. Been around for a long time. If I remember correctly, Catalina was made from Nielsen and IRI. I think back in the day, it was kind of a JV between them. Um, uh, been around for a really long time and doing kind of the same thing a long time off, of purchase data, purchase data, shopper data, shopper data, shopper data. And that data is valuable. So, you know, uh, so I'm filling in, uh, acquired them combined with media math. I'm sure that they're, they're aiming to, you make better ad targeting, um, and, uh, more effective advertising.

Karen Lynch: They're saying, um, proving that with this kind of integration, they're going to be able to prove how media spending drives sales. Like they're, they're, they're banking on that or betting on that, you know, that The ability to, to show The correlation, this media spend equals this boost in sales, um, lack of spend, maybe not. We don't see those boosted sales, flat sales are declining. So that'll actually be really interesting also for those clients to see that and to see that integration in action.

Lenny Murphy: So, yep, yep. But if you have a historical data asset, right, if you're thinking, oh, we've been running this company for 30 years, it has value. Unique data assets are a defensible moat that has value. And I think there's a really good example.

Karen Lynch: Speaking of media, which is six or seven or eight more times today.

Lenny Murphy: The rebrand 55 blue. Um, I couldn't figure out exactly what that name was. It didn't, I didn't know.

Karen Lynch: I'm so glad you said that because I, I clicked, I, you know, I Read The, Read The, you know, The press release and then I, I go to The 55 blue site and I'm like, it's not intuitive. And I felt really, I feel like it's not intuitive. Bad saying that because you know, this isn't an inexpensive venture. Um, they were acquired by HIV capital, um, in 2025 kind of, you know, leave The Cantor network and, um, 55 blue is their new identity. But, but I'm like, it says nothing to me. What am I missing?

Lenny Murphy: I know I'm, I'm there with you. So sorry guys. Can't start marketing.

Karen Lynch: Like it's there. Like people blue 55. Like, anyway, I feel really bad.

Lenny Murphy: Is it like roulette? That's the only thing because of me, like, you know, blue 55.

Karen Lynch: And I really tried. I really wanted to understand The rename and The rebranded connection. I was like, it's got to be something, you know, um, hey, that's not Cantor.

Lenny Murphy: And I think that was the operative thing of like, not We've got to change this. So, um, yeah.

Karen Lynch: So if anybody knows, go ahead and give us some Intel, email us The exchange at greenbook.org and say, here's where that came from, because it wasn't intuitive to me and clearly not to you. So there you go.

Lenny Murphy: So please, yeah. Give us a hook. Because there was no context in that name.

Karen Lynch: There certainly isn't going to be brand equity for 50, like, you know, like maybe they wanted The absolute departure. Fresh start, maybe?

Lenny Murphy: No legacy brands? Who knows?

Karen Lynch: Who knows? I don't know. I don't know. So yeah.

Lenny Murphy: Now, this is the other big theme that we've been talking about as we go into partnerships. Telium with their OpenAI Connector for real-time intelligence across customer journeys. So we're seeing now this other side okay, we have a data asset or a technology plugging that into The infrastructure layer. In this case, OpenAI. If you're an OpenAI shop and that's become your default organization, now accessing these external assets to use, to build from, or to incorporate into whatever solution. So that was pretty big, I mean, Tealum's not a small company, they're a pretty large data aggregator overall. And then the same thing, LiveRamp with Scout for integrating their first party data signals for AI-powered optimization. So that's if you're a panel company, if you own proprietary syndicated data assets, That's right. I mean, here's a way to think about that. Here's The other part of The equation of that integration directly into The kind of The orchestration layer of The AI platforms.

Karen Lynch: We're not just talking about products and features. You know, we're talking entire ways of doing business.

Lenny Murphy: What what? Yeah, we could go on and on about that. I have been so embedded in that thinking this week around infrastructure, and orchestration. Those have been the words this week, right? That has just those concepts for everything. And I think we're seeing examples of that, you know, here in The news, which is probably why I was thinking about it. All right.

Karen Lynch: Then, uh, you go, because I know, I know you're close to The folks at, uh, you know, Walmart and The data benches there. So talk about this scintilla in store, which is, you know, building on their scintilla portfolio, I suppose.

Lenny Murphy: Uh, so like everything they do, there's, there's applications specifically for, uh, their clients who they see as brands, um, uh, to capture more data, uh, you know, in store in real time, but there's also research application here as well. Then, you could shop alongs, you know, you can do secret shops. You can, you know, so these things that we've thought about from a research standpoint that have been kind of subsets, you know, uh, in very specific things for retail environments, audits, you know, uh, which often go hand in hand with secret shops, The, uh, they're, they're empowering all of that, uh, with their tools, with their technology. So no reason to use third party apps or anything of that nature. They just have The whole shebang with multiple use cases, uh, across The board.

Karen Lynch: Speaking of being able to use It's The whole shebang. SurveyMonkey decided to give that as well. Here you go, friends.

Lenny Murphy: It is. Free tools. Free tools.

Karen Lynch: A hub centered on its AI survey generator. Anyone can just go and create an AI-powered survey and access a suite of user research tools. No account required.

Lenny Murphy: Talk about low friction.

Karen Lynch: I just think it's going to be... Anyway, it just kind of floored me all right now. I'm sure you know without digging too far into it I'm sure there's then, you know paid upgrades, etc, etc, but The reality is for those For her or you know small businesses for people who are just you know, just don't have funding don't have a research budget You know for anybody who wants to just get out there and ask some questions Look, they're freemium model served them well, I'm sure that you remember as vividly as I do that, you know, a couple, 10 ago, I'll survey monkey dismissive survey monkey.

Lenny Murphy: That's not real research. Wait, WTF. They get a billion dollar valuation. I remember that day very vividly.

Karen Lynch: And I mean, I think The obstacle. The obstacle might've been, I don't really know how to write these questions because I'm not a quantitative expert, survey research expert per se. I've been talking to some people. I got, you know, am I writing the wrong questions? Maybe, you know, am I wording this the right way? Am I introducing bias? Like all of The things that would get in The way of a DIY-er, not wire, DIY-er, you know, of somebody who's doing it themselves, that might be The barrier to using a tool like SurveyMonkey, because you don't really know what you're doing, and you don't know The right way to word it, or The sequence, or how not to introduce bias, all that stuff. And now, don't worry. We've got a solution for you. Will help you.

Lenny Murphy: And that actually brings up a really interesting point. I won't soapbox on this for very long. But there's some things. I think I'm going to term AI slop. Part of me that's like, I'm, I'm offended by that now. It's like, I shut up The AI slot bullshit, right? Is that right? Is it accurate? And is it? Is it informative? That's all that matters, from my perspective. And it's also justified by reducing AI in that, but I absolutely get in some cases, originality, creativity, you know, voice, those things are important. Surveys, not as It's really one of those things where that's very important. It is more important that it be right, remove bias, structure correctly, et cetera, et cetera. You know, your own, as much as we might like to throw in our own, you know, little language here and there, it's really not needed to write a good survey. It's probably detrimental to writing a good survey. So these tools, you know, are very effective because you can make sure the quality standards are there. So hats off to them.

Karen Lynch: You know, I'm working with whatever their AI chatbot is, I'm assuming there is one if you're getting The AI assist, like, I need The right question around, you know, liking or something, you know, and it's gonna give you, I would assume, like, you know, kind of The best in class version of a Likert scale, like, you know, 100%.

Lenny Murphy: And you want to divert, you know, a five point scale versus a seven point scale. You know, I'm always getting impatient with those things. Let's remember The net promoter score really was a dominant model. And so we talked about five or seven or whatever. Three worked just damn fine, didn't it? So yeah.

Karen Lynch: So obviously, to all of our friends who have survey tools, check out what they're doing. Check out what their suite is at SurveyMonkey, because you need to find your point of differentiation for sure.

Lenny Murphy: And maybe it is too much for the kids.

Karen Lynch: Sure you're better. Your expertise is better than theirs. Yes, maybe it is.

Lenny Murphy: We only use The seven point scale. Maybe that is the point of differentiation. Oh, goodness. We're wasting time. Continuing on. Boy, but now we know we get into the agent world. Stravito, their deep research agent. And of course, that's, you know, they are a knowledge management platform. No-brainer application of agents to pull together information and present it in a new way and connect that into The workflow. That's all for them. Resonate, which is an agentic marketing platform, now uses predictive consumer intelligence for campaign creation and targeting using agents to do that based on data. Mirroring that in. Now, you've been talking to Thomas.

Karen Lynch: I have.

Lenny Murphy: So did he give you a hint, like, we're going to create ads on The fly now?

Karen Lynch: Well, and if you didn't partake in The Green Book webinars that they just hosted, first, Thomas kind of went out and shared just a presentation of it. And then I interviewed him in a follow-up webinar.

Lenny Murphy: We're talking about neurons. Thomas Ramsey of Neuron Z. Sorry.

Karen Lynch: But yeah. Where they're giving, they're making recommendations kind of, you know, in addition to just generating ideas, they're also kind of making these visual recommendations. So, you know, what's cool about Thomas is he, I always learn something new from him. And he was talking about, you know, yes, there's generative AI and there's, you know, predictive AI, but there's also suggestive AI, which I hadn't really heard, which can also be called, I'm forgetting what else, but it's this whole idea of, Yes, it can make recommendations if trained properly, which in their world, they've got The tools to train it properly to be suggestive. And so it's a really interesting breakdown of thinking about how those three types of AI are different and how they play out in the creative loop that they have there at Neurons.

Lenny Murphy: So very interesting. So I don't think they go this far yet to actually create whole new ads on The fly, but they can next week. I mean, you know, some of these new technologies are coming, that will be next.

Karen Lynch: And, you know, we talked about the kind of creative tension that a lot of, again, agency folks in particular are managing right now. The creative tension between, well, I'm The creative thinker, I don't want AI to be doing my creative thinking. So there is a lot of tension in that space right? But you know, the best thing to do is recognize the use cases and how it can help and assist further your abilities. So we also have that conversation in The second webinar as well.

Lenny Murphy: So yeah, just stuff. Interesting stuff. It is interesting stuff.

Karen Lynch: If we if we go back to and we'll talk about, you know, kind of Nielsen, adding segments to their Nielsen one using Scarborough's National Consumer Day So basically, you know, Nielsen doing what Nielsen does, adding more segments and all that, which I don't mean to, you know, sound like that's not a big deal. But again, there's these moves in the media. And if you think about what's happening at WPP, and then you think about some of The new tools to, you know, not just create new media or new creative, but then also measure and The intelligence link and all of it is like that subset of our industry. I feel like if we're all disrupted there in a frickin earthquake this week, they are. And that's what that's I think the most poignant thing for me and we'll keep talking about this but you know, advertising and media are like I don't even know. It's like my head spinning at all of the different things happening there. So they're feeling the extremity that even us and insiders are feeling.

Lenny Murphy: Well, and I think so, you know, if we go back to this kind of through line here, in my mind, we've talked about this for a long time now, what are kind of defensive votes, right? And they fall into different categories, but kind of fundamentally, you know, data, you need data assets, how you use that data to drive business impact. And then your expertise around specific categories. So you look at these companies, I think that's what they're doing. They're recognizing, you know, okay, the process is out the window, right? We can't, but we have this unique data that drives business outcomes. And we better just focus the shit out of those things and how we monetize those effectively. And scale them, become part of infrastructure, you know, part of The orchestration layer, blah, blah, you know, these buzz terms, but that's just where we are. And yes, it is as disruptive to them from a business model standpoint as everything else is for everybody, for every other, but they have assets that are monetizable and so they'll get there.

Karen Lynch: Yeah, yeah.

Lenny Murphy: We've still got a couple more things we want to get through. Tell Lickley, Lickley, Lickley. It's kind of fun to say, Lickley, The Read Amplify, and it was a standalone man and services company. That was, uh, I just, I just thought it was fun for The name Lickley.

Karen Lynch: Anything else about this is, you know, what they say, you know, they're, they, they decided to kind of put a stake in The ground and say, this is a solution for mid market and boutique teams that are priced out of The enterprise tech stack. So I'm like, all right, that's interesting. You know, so, you know, making a play saying, you know, this is where we're going to live. We're going to live and we're going to serve these customers. So hats off to them for having a very defined audience. I give them credit for that.

Lenny Murphy: Let's just get these two big. This has been The undercut.

Karen Lynch: Here's what we've got next. We've got two big kinds of tech developments, which just continue the story. In our arms, not our arms race, in our AI race right now. And then two big stories for your reading list. So Anthropic expanded their Claude co-work, you know, lots of, you know, connectivity with Google Drive and Gmail and DocuSign and FactSet and other customizable plugins. I actually, you know, I'm like, all right, I'll download it to my Mac, which is kind of like The point. And then it's going to be able to search me if I give it permission for that. And I'll see, I mean, I have a few different logs, I'm not sure, but I'm open, right? I'm open. And then same with Perplexity, right? Perplexity launched their Perplexity consumer computer. So, you know.

Lenny Murphy: And I have a Perplexity that is my default. So I say The difference here is that Perplexity's positioned itself as that orchestration layer. Layer, because they pull in multiple models. So you want to access Claude, you can do it through Perplexity, as well as their own models. So I think that's really interesting. Their play is, say, they want to own The orchestration layer rather than The core fundamental layer.

Karen Lynch: And there's a use for that. I mean, yeah. There's those moments where you say, do I want to ask Gemini, or should I pop over to Claude, Chat GPT like, you know what, you know when you're when you're struggling to figure out which one it's a great use case for perplexity, you know 100% actually and see what it says Going to discern what you might not be able to discern it's funny because you're Stephanie and I was in a call with The client about what they need to do and We're talking about what platform they should use.

Lenny Murphy: So literally yesterday is like a shameful perplexity. You can't build stuff for perplexity but perplexity rocks. Yeah, well, now you can build stuff in perplexity. Now, go back to them and say, look at perplexity, because now you can execute, you can build whole applications, technologies, and you know, it's part of The stack.

Karen Lynch: So I have to, for those of you not tracking, because you're like, I'm perfectly okay with my GPT month, $20 you know, and not exploring the other paid versions of The other ones. Also, you know, just got the little pop up on something I was doing in chat GPT. That's like, do you want to bump up to business? So you don't have to go all the way to pro for a month, 200 but now we've got business, which is 30 a month instead of your 20 a month. And I'm like, I see what y'all are doing.

Lenny Murphy: I upgraded yesterday perplexity from my pro individual pro account to The professional enterprise pro account. But now I want to use this, I have to go to enterprise max. And that's like 200 bucks a month.

Karen Lynch: Like certainly in our case at Green Book, like Lukasz really has to look at our budget for, you know, who's using what. And I mean, this is not easy work for him to manage. Like who's using which, which AI platform as part of our tech stack. And what do we have an enterprise, you know, it's like, it is, that is a job right now that needs to be wrangled in your organizations. Cause you want to empower your employees to use the resources available to them. It is essential to your business for them to use and experiment every single freaking day. We talked about that last week. Like you have to be. So which paid versions are you? You know, what are you paying for? Anyway, it really makes your head. And let's segue into this pitch book article, because you can pitch a book article, a Q&A with Francisco partners on software sell off. So I want you to talk more about it. But there was a line in there that is connected, which is people don't like change because it requires effort, right? Customers who want customers want to use their incumbent vendor, but they want the vendor to do better and give them tools and provide more value. So that feels like there's your little glimmer of hope. Your customers don't want to not use you. I mean, I don't want to stop using it. I like it. I named mine. Like, I don't want to experiment with Claude co-work and I don't really like using Gemini, but I will. I'm being forced to, I have to. The same can apply to any company in our ecosystem. Your customers don't want to explore the world outside of what you've offered them. If they love your service, they just want you to do better.

Lenny Murphy: System one, system two, right? I mean, it's the same thing, right? I don't want to expand on something that I don't have to. And so, yeah, just, I hired you, you know, you just do what you're supposed to do and make me look good and all is good until you're not, then I have to do something different. And, and that's what Francisco partners, they're a mid market, um, that were actually a very large, um, private equity and investment fund. Um, The, uh, but they play in The mid market in SAS. And I think that was The, The, interview is really interesting because kind of The, I think The least going in was what's up your portfolio screwed. Look, you know, none of them can perform. And this guy was like, no, that's The case. We've been, we've seen this. We've been helping our investment companies prepare for this from a process standpoint. And we're counting on switching costs. Um, you know, uh, so that was really interesting.

Karen Lynch: Really interesting. And I, you know, I just want to build on something you said, because it sparked all kinds of stuff in my brain when you, you know, you talk about system one and system two, during a time of disruption, right, we are all using system two thinking because we have, we don't know, we, we don't have that quick, intuitive, you know, gut responses, like that is not what's happening. Our system one is sort of like not being able to be utilized, because we are so kind of operating well out of our frame of reference, right? We're all learning something new.

Lenny Murphy: So I think that's really interesting aha.

Karen Lynch: That is what's happening right now is we are all required to use system two thinking and our system one thinking days are not over, but they've been there. They're halted. That's why we're so tired at the end of a workday. You know, we're like, Oh my gosh, I'm exhausted. A lot right now. It's a lot.

Lenny Murphy: It is a lot of process. I was Last night I I was up at 2 o'clock in The morning thinking about this stuff and I woke up thinking about it and you know Now you're probably know well Lenny you're always like that No, I'm actually not but but this it was just one of those days where things were just kind of connecting and neurons are firing There's not many left. So this view that I have is still, you know working overtime and Yeah, and then we get to The last article because this is for our industry You want to talk about it? I know you were really excited about this one.

Karen Lynch: I'm excited about this one. So but I don't know who s a, who sas tr is as a s a s t r faster, faster, faster. I don't know who they are. So do you know who they are? Or is it just something?

Lenny Murphy: This was part of a pitch book, it came across if they're just a company that manages, or, you know, SAS isn't dead.

Karen Lynch: A lot of people are saying SAS is dead, right? Thought Producer Service is dead. But what is this piece here? The last thing we'll share with you today. What this argues is that kind of what is dead is The old b2b growth playbook. And it's not so much that sass is dead, because it's really not. But the playbook has changed. And so interesting. And some of the highlights because I have this article this, this pulled up. There's changes prototypes get built in days, not months. We've talked about Lenny, right? You can bring something new to market really quickly. Shipping, right? It's shipped faster. That's just the way it is. Anyway, AI is creating new competitors, which we talked about earlier. Outliers are hitting, it says 100 million APR in 12 months, becoming budget magnets. So if you're an outlier, you're getting this funding because you've tapped something, and that's, again, changing the playing field. Yeah, The old quarterly releases, The old cadence of quarterly releases and annual platform updates look absurd. Like AI native companies shipping genuine capability improvements weekly. And we're seeing some of those, we can't talk about all the ones that we see where it's like, we've updated, we've updated, we've updated. And I'm like, we cannot, Lenny and I cannot share all of your weekly updates. Hats off to the people that are doing these weekly. It will serve you well. Even if we're not shouting you out, because we can't shout out weekly updates for your company.

Lenny Murphy: That's what we'd be doing. I mean, it would be like ticker tape, right? Yeah, exactly.

Karen Lynch: But you're in the Hall of Fame right now, right? So there's a massive reluctance to buy more products or seats from slow-moving vendors. That I thought was really important, because I'm like, OK, get your acts together. Get your timelines in place. Nobody wants to spend a budget that doesn't show massive ROI or ROI almost immediately.

Lenny Murphy: And I'm like, Oh, yeah, well, because you know, that inertia switching costs, that's not a moat. That's a, that's a bump. That's like a speed bump. I mean, it is an obstacle. Yeah, it is by no means a defense. Yeah, yeah.

Karen Lynch: So yeah, and then the last thing they call out here is years of price increases have created real frustration, even anger at some vendors. So like, like books here, you know, talk about faster, better, cheaper, like, they're basically saying, it's unacceptable for you to be slow or expensive, you know, of poor quality, like, nope, not anymore. We're getting more. And we're not going to sell for less.

Lenny Murphy: And the models of, you know, so I think pricing, it's a whole, we'll see how this goes. But we're seeing examples of companies that are just going with all you can eat flat pricing, you know, um, obviously I'm a big fan of buffets, right. Um, when you see me, so, but from a procurement standpoint, et cetera, et cetera, I mean, there's, there's lots of dimensions here in The traditional SAS model. Um, yeah, I liked it. It's not dead. It's not dead, but it has to be retooled, right. There's competitive pressures and it goes back to The thing, all this stuff that we're talking about now of The, uh, The buried entry for competitors. It's very low now from a technology standpoint. So, so you, you know, you cannot rest on your laurels, uh, thinking I already have an embedded relationship. They've already paid their annual license fee for The year. You know, we're embedded. We are part of their infrastructure stack today. All right, but somebody can create a better mousetrap easily and a hell of a lot cheaper than you did tomorrow. So we have to be careful.

Karen Lynch: And we know, connecting the dots of these last two articles, yes, we know that people don't like change because it requires effort. But if you're not changing, if you're not giving them what they want, and then somebody gets ahead of you, in front of them and says, I will solve all your pain points. Then at some point, their decision's just going to go to yes. And, um, it's really interesting.

Lenny Murphy: So, and we see that playing out in The market, follow The money, right? The capital market, The investments, The, you know, these rounds, those aren't going to companies with no revenue. Those are companies that have already, they have pilots that make their, their, that switch is already happening with those companies. That's why the investment dollars are flowing to them. So anyway, we ran 45 minutes, but we knew it was going to there's so much. And guys, let us know whether you think this is too long or whatever. I know we've come a long way from we're gonna do it 20 to but there's so much happening. We hope that you find value in our analysis and you know, sharing this information because I think it's only going to increase.

Karen Lynch: And today felt like a little bit of a pressure cooker, a little bit of a downer. There's a lot to take in today. So, um, have hope, have faith and, and, you know, and keep that system to processing going. Don't, don't slow down because, um, you gotta just, you gotta just stay with it.

Lenny Murphy: We are, we are a problem solving species, so we'll figure this out. All right. Everybody have a fantastic weekend.

Karen Lynch: For sure. We'll see you next Friday.

Lenny Murphy: Bye everyone.

Links from the episode:

Profound raised a $96M Series C at a $1B valuation 

Solid publicly launched with a $20M seed round after two years in stealth 

Funds and Launch for Prediction Markets Firm TBD 

WPP to sell assets and cut jobs in radical shake-up to counter AI threat 

Shopper Data Firm Catalina Becomes Part of Infillion 

Kantar Media rebranded as Fifty5Blue 

Tealium launched an OpenAI connector 

LiveRamp partnered with Scowtt 

Walmart introduced “Scintilla In-Store” 

SurveyMonkey launched a free tools hub centered on its AI survey generator 

Stravito launched “Deep Research Agent” 

Resonate announced “Resonate Cortex” 

Neurons introduced “Visual Recommendations” 

Nielsen Utilizes Scarborough To Introduce 200+ New, Advanced Audience Segments Via Nielsen ONE 

RAD Intel launched “Lickly” 

Anthropic expanded Claude Cowork toward an enterprise-grade release with connectors 

Perplexity launched “Perplexity Computer” 

PitchBook shared a Q&A with Francisco Partners on the software sell-off 

SaaStr argued SaaS isn’t dead, but the old B2B growth playbook