Value-First Data - Mar 24, 2026

[00:00] **Introduction** Chris Carolan: Good afternoon, LinkedIn Friends, Value First Nation. Welcome to another episode of Value First platform, talking AI data readiness with Trisha. Happy Tuesday, Trisha. Trisha: Happy Tuesday, Chris. How you doing? Chris Carolan: I'm doing great. Trisha: You're doing better than great. The last couple times I've talked to you, you're, you're almost euphoric. Chris Carolan: That's probably the right word. I mean, um, we're going to talk about why today. Uh, it's like for me, getting the opportunity to solve large problems, um, is a lot of fun and helping others solve those problems especially. Um, and this is kind of where Value First started with this set, set of traps, was literally the first, first kind of thing. Um, so when you shared your ideas for what we could talk about today, um, it, it made a lot of sense, uh, to start here. Trisha: Which is, I don't know how much, you know, and everybody knows, but I know that you have an entire AI team now, uh, deployed to autonomously executing operational functions. And I would love for you to give a very brief overview of the kinds of work they're doing for you. Um, but then that leads into a very natural question, which is this is the, the data readiness show. So what did you have to do before you could do that? Because that's what everybody wants to get to. This isn't, this is a really inspirational end state. But what do you have to do to get there? And which, which goes back to some work, a lot of work that you focused on in 2025, which are the 12 traps. Chris Carolan: Yes, the beginning of the Value First framework, um, which was a thing before the Value path and before Unified Customer view. Um, and just to show a little bit of the end state, uh, that Trisha's, um, referring to. Right, if you go to the website and all of this that we're going to talk about is available, so it's not like there's, I mean, the secret sauce for me now is finding ways to use things like Unified Customer view to dodge and weave all of the obstacles and traps that we're going to talk about to actually start to get this done, like inside of organizations. Um, doing it for ourselves first is super important and as we do it, it's just the fun part about, you know, if you've ever been a marketer that has a hard time marketing yourself inside or outside of the org, like now it's never been easier to just build with AI and then say, hey, let's make a web page about that. Let's make a new thing about that, right? So, that's what you can find a lot on the Value First team website. But AI native operations team where every agent has a specific domain, a distinct identity and genuine operational responsibility. And I kind of chuckle when I see them like latch onto this phrase as it's like how important is it? How autonomous are they? I'm still in the loop, all these things. But the fact is that I have not touched Hubspot data in a while, right? Yet Hubspot data is getting maintained and created and edited every single day, right? So the operational responsibility of data management and Hubspot does fall to these agents. And, um, so there's, you know, a lots of agents and that person or that agent in particular, so Ledger, he is the Hubspot right gateway, right? So sole authority for all CRM mutations across the platform. So I get a transcript and it gets processed by a few different agents and when it's time to update Hubspot with information related to that, uh, you know, human or company or opportunity or project or or or he's making that update. Sometimes he's asking me first. Trisha: Mhm. Chris Carolan: Often times not. He'll come back with saying, all right, the appointment's been made, agenda's been filled in, like here's what it looks like. You can, here's the URL to go link to it in Hubspot to see it. Sometimes I go check it out. Sometimes I don't. Right? So for me, it was like there's 70 because there's literally like all these separate roles across the business that I've been thinking about since, you know, 2020 about the way to structure orgs, right? And like because here's the thing, like what people are doing right now and if you see anybody selling like OS's, like operating systems that are built for AI, right? They're trying to sell you this kind of experience where it's just done for you, right? And like in SAS terms, how often has that worked? And this, these traps and this conversation with AI started with, okay, I'm going to help people with Hubspot. There's all this other stuff that gets in the way of Hubspot that has nothing to do with Hubspot. And I'm not going to keep selling into that stuff and see like 50% adoption rates of CRM and 70% digital transformation failure, right? For like let me try to solve it instead of trying to make money off of it. Um, is where this started. And it started from an organizational perspective in that I'd just finished this superhuman framework series with George. I was like, all right, another like, I was so bought in, like this is how you put humans in a good position in this moment right now of AI transition. But then I imagined like taking it to a leader and then a leader being like, I don't know how to get that done. Like, I don't know how to manage the change of sales compensation and MQL KPIs for the marketing team and the fact that marketing and sales never get along and the fact that all of our handoffs suck and the fact that, um, uh, we say we're customer centric, but then none of our processes represent customer centricity, right? Because our systems tell us we're not supposed to do it that way, right? We're supposed to have these stages and we can't skip stages in our pipelines because then it's going to break the reporting even though we know humans do not go in a linear, right? So all these things. So much of it related to silos, right? Of marketing, sales, like all of the problems of data, um, relate to that. Uh, so I said, okay, hey Claude, how would you, um, how would you build an org if marketing and sales were nothing? Like throw out like all traditional structure out the window. And he came back with like this constellation thing that I had no idea what was going on. So I knew I was on the right track to some extent. Um, but it was all about not getting in the way of value flow, right? Um, alongside this conversation, I've never enjoyed any conversation that involved word leads, like ever. Like as soon as it comes up, I'm like, okay, I'm not gonna, we're making bad decisions and like, it's just so I started talking about that as well. And this 25 years is a specific number. I mean, it was at the end of 24. Like Salesforce introduced the lead object into the CRM next to contacts. And that was the first trap that I started flushing out, uh, with perplexity actually, right? And from there, it was just a cascade effect of tackling all of the issues and like trying to, so instead of saying, AI, can you just come fix this? It was AI, can you help me understand what the problems are? Like here, because no matter how great a tool like Hubspot is or no matter how customer centric the leaders says they want to be, they just cannot get there, right? Um, and, and literally these invisible barriers, like people, good, really good, well meaning human beings, making decisions that they actively tell you they do not want to be making in their daily process. Like knowing how bad it is to spam people with emails, do cold calling. Like, I don't like pop ups at home, but it's a part of my job in marketing. So, and they work. So, I guess we're doing pop ups here. Like all that stuff was like, how do we just turn into different people like when we're at work, right? And, um, please answer, ask questions as they come up or else I'm going to go for like 50 minutes here. Trisha: Well, so let's back up a second. Um, you started asking Claude about just like, did you start with what's wrong with the system or did you start with what's the ideal system? Chris Carolan: I started with by highlighting problems. Trisha: Mhm. Chris Carolan: Um, and sharing why I thought they were problems. And then saying, like, I don't want, like, I want to solve the problems. I don't want to figure out how to make money because of the problems, which is a difference. Um, and yeah, that's, that's how it started. Um, and the leads conversation was literally like that, like why do I feel like this? Or like I think it came up to where he's giving me some some kind of content, like creating an artifact. And I was like, you know what, F leads. I don't ever want to see that on the page again. And then we went into like why? And, uh, you know, some of these like beyond leads was originally titled F leads. Um, and but all of it relates to you like, and that's where like as I'm getting this content from perplexity and these certain conversations with Claude, I start to put, you know, the dots together, right? And like traditional approaches fail, we dehumanize the process. Like because I've been feeling this inside the Hubspot ecosystem where I'm talking to a sales rep and they tell me they understand how valuable LinkedIn is, but since they're measured by calls and emails, they, and this was back in 24, I know they've progressed since then, um, some of them. But since they get measured on a different KPI, that means they can't spend time on LinkedIn or they have to lie about the other stuff so that they can spend time on LinkedIn. Trisha: Yeah, that's a great example. And on the marketing side of things, uh, I, I know that broad scale awareness advertising, you like using an ABM platform type of thing. I know that it increases the amount of the right type of people coming to your website, but there's no way to track it because if they don't convert in the same session as the one where they saw the ad. So if they see the ad and then come to your website and leave and then two weeks later convert, there's no attribution to the ad. If they see the ad on LinkedIn and go read more about you on LinkedIn, they never come to your website, they never convert, there's no attribution to the ad. Um, but I know through some like a lot of testing that I've done that you create awareness for your brand and it directly impacts how many people become interested in your brand and start asking you questions. Uh, but it becomes really, really hard to get businesses to fund that and they, that's the first thing that they strip. And you immediately start seeing declines in all of the, the efficiency of all your other ad platforms as soon as you do that. But you can't prove it. Chris Carolan: Right. And yet you're asked to prove it. You've, you've been told that you should be able to for years. Um, and that's like so the measurement trap, what you're describing was a trap number five that um, came out and that was actually the first trap said out in the open. Or it was literally uh, you know, Rob Jones and I had let's build um, community uh, let's build community content, I think was the name of the show back then eventually turned into Let's build GTM. We're like 10 minutes before I finished building this measurement trap article and this measurement like Value First measurement. And on the show with him, I went through the 10 principles of Value First measurement and it like just resonated with him so hard. Like as just the first test of anybody and I had just created it like 10 minutes ago, right? Because its other foundation was started, which is a theme here and should be a theme with anybody like AI readiness, um, like this is not happened overnight, uh, and but once you have it, it's like just the slow build of value. Um, but where we were before, like so leads trap was the first one and I was like, okay, if that um, was a thing and it came from Salesforce, like what else? Like what did that, what, what happened because of that, right? Another thing I've disliked a lot is, you know, the managed services space and like the idea that somebody builds your complex website and then you always need them to fix anything on it, right? Meanwhile, we're trying to help people in the Hubspot, it's like, no, you can change the field on a form, that's so easy, right? Like, you shouldn't have to pay hundreds of dollars an hour, like for somebody else to come fix it and manage all these security plugs, like all this dependency, mhm, that has been created over the years. And when you tie those two together, um, you create a leads object in Salesforce and like if you like the numbers of what Salesforce has been able to create leads wise over the years, like millions, millions of leads per year, right? But they're separate from contacts. So the contacts are the people that we really have relationships with. So we're going to do whatever we can to load up leads. How do we make that? How do we create leads at scale? We got to do advertising, right? Interruption, like try to trick you, like all these things, right? Just to get you to click so you can give us the email address and now you're lead. But since we really don't know you, um, because we're using these two mechanisms to try and trick you instead of qualify you, we've got a bunch of junk that everybody knows is junk. We don't want our sales team spending time on it though. So we need to qualify that group, but we don't want our sales team spending time on. So we need a completely different team. Let's call them sales development reps. Trisha: Mhm. Chris Carolan: And now it's a completely new resource in an organization, which most organizations never even got there, right? But it, it creates this complexity that now we need this super complex system to manage all of this stuff. We don't know how to do that. So that means we got to get into a contract with somebody that does know how to do it. And they're going to build it out so that we can overcome these things, but we don't actually overcome them. Um, on the opposite of these are, you know, Value First realities where on the other side of leads trap is Value First humans, right? Like when you um, like if you were at a show, at an event and, and like we met in person. There are things that I'm just not going to do because we're looking at each other in the face and you just don't do that to another human being. But if I'm on the phone or on the other side of an email or on the other side of a LinkedIn connection request or you put a like a cloudy wall up in front of us in that moment and I can't see you and I don't connect with you. Trisha: Mhm. Chris Carolan: I'm going to do some stuff I wouldn't do. Like, like ping you with stuff that I don't like myself, right? So when I say dehumanize the process, that's my only conclusion for why really good human beings would be willing to do stuff like that to another human being is if you see a leads list and I got to make a hundred calls today, there's no way you're seeing everybody on that list as another human being or else you would not do that. Right? In a lot of cases and why do you do that? Because KPIs say you have to because that's how the game is played, because that's how the industry works, like all these reasons, mhm, right? And it just leads to this cascade of of of traps and this is also why it's so hard to break free from all of this, right? Um, and like alongside that, around the same time leads was out, like AI was obviously a big deal and I just started with that one for marketing reasons, let's just be honest, like leading with AI replacement trap. Um, no way I was going to bury that. But there was also so many, there's been so many like like professional growth things related on being better humans, right? And so I don't want to lead with that because then it's just another one of those, right? It's like, oh, that sounds great on the surface, but like I'm over to the real work site and you know, we're not going to be able to do any of those things. But at the time and still like people see AI as a, as a replacement for, for human value in a lot of ways. And kind of what we're talking about here is helping you understand like why that's a trap because all the humans in your org have the context. They have the need, they have what you need to become AI data ready. AI does not have that. It's not going to get it from anywhere else other than the humans and if you start by replacing them, it's going to take way longer to get to where you want to go with AI. No matter how good it's getting right now because it's getting really, really good, but it's also turning these moments to where it's not into like real gotches for for organizations. When if you just would have still had Trisha there to see that got you from like a mile away, mhm, right? Now all of a sudden you're, you're going so much faster and you're rescaling your, your humans that you say you want to take care of like at the same time, right? So, after that, it became kind of a, so you got these, these five and, and the measurement trap. Um, like then it became like, well, these are all very like tactical things, like in order to change, like in order to change teams getting measured by leads, you're going to have to change something at the leadership level. Like the way things are done, like, um, and that's where like you get into the inevitable like culture and values and leadership conversations and that's what the opposite of these two are. So these two I actually said like, so the Value First realities of Value First AI, Value First humans, uh, Value First communication, like communicating with the audience instead of advertising to them, um, Value First content, sharing content instead of trying to gate everything and, and trick everybody into emails, Value First partners, uh, like instead of qualifying people out. Like qualify people in. Like how can we partner with anybody in in our sphere? Like there's so much opportunity cost related to, well I don't have time to think about this. So can you answer, are you bant? Like, did you answer on my bant questions? If not, like, all right, you got, you're out of my pipeline. Um, Value First delivery, right? So the opposite of managed services and this is how I've always I've always approached Hubspot. And most customer teams like, they want to build enablement and empowerment in their customer base because it's just a better customer experience, it's what they would want. Uh, um, and it just makes you feel better. Like when somebody says like, no, we got this. Like thank you, we've been wanting to do that forever and now you taught us how and like, oh, but guess what? There's more stuff to do. So we don't have to like like tell you to hit the road. Like there's so much opportunity. So Value First delivery on the other side of this. And Value First measurement here, because that was like, okay, we identified the trap, now what? Like how do you break free from the trap? Like what things do you have to do? So there's, there's no shortage of of books and content around leadership and culture, mhm. But you know, culture as a thing to talk, like to break into any of this is not the first. Like, that's not how you get your foot in the door, like start talking about culture because it's another like, oh, that would be super cool. Um, or it's like, yeah, we have a culture program. Like these are our values, like everybody knows what they are. And this is probably like eye opening part was to give Claude, say, okay, we've got this part down. We've got to address leadership and culture in some way. So what would be the traps? What could be traps? And that's when he came back with conformity in terms of like, this is how we've always done it, so you're going to do it this way too. Mhm. Um, uh, not even getting into like the lack of diversity conversation, um, but also not diversity for diversity's sake where it's like, oh yeah, we're diverse, but your idea like isn't our idea. So like you got to just do it our way, right? And there's no innovation because of that and lots of other stuff. But then the authority trap, the opposite of leadership is really trying to just control everything. Um, and that you know, like it just here blocks team enablement. Um, and just blocks the natural flow of value inevitably, right? So it was so as so like if you were starting a business right now, like you would not start with, you wouldn't start with AI implementation, I would say. You might use AI in a similar way to like figure out like what you need to do, but as you start working with other humans, like you have to start from a leadership perspective, vision, mission, values and then like do we have the right people? Do our people like ascribe to those values? Like the culture, like you start to build in the other direction, right? But most people start from up here. Like and if you start here and you have all these other traps in place, you're never going to be AI ready. Like you do just not because I can tell you what AI doesn't understand some of these things either. Like try to have an MQL conversation, like with AI, what that's supposed to be and how that's supposed to work for your organization, right? It'll come up with lots of different ways for the acronym MQL like to mean, um, and none of which may match up to what is actually going on in your organization or what is actually a qualified lead. Chris Carolan: Right. Because you've never Can you, can you give it, so since this is about AI data readiness and these are, these 12 things are things that you see are blockers to being able to be AI ready. Can you give a couple examples of sort of like, here's leads trap. This is, this is what you get if you don't solve for this and you try to layer AI on top and then this is what you get when you do, when you solve it first. Chris Carolan: Yeah. Um, we just talked about this in, in Value First office hours today. Uh, every Tuesday, Wednesday, Thursday at 11:00 AM Central. Free to join, like come have fun conversations about this stuff. Uh, the concept of attribution, right? Um, and, and lead counting and lead goals and like how disconnected they are from reality. And again, this is largely because companies like Hubspot, right? was built on top of Salesforce. At the same time, 2006, you know, um, serious decisions coming out with the water like demand waterfall, lead, MQL, SQL and um, you know, one of the uh, you know, first founding guys, or one of the first, you know, the first sales guy Hubspot, Mark Roberge, like came up with like the lead like lead qualification frameworks based on actual costs, like cost of lead. And if you have a thousand leads, then that'll get you, you know, a hundred deals and then you'll close 10 of those deals and like that's where it started as if humans like actually follow a process like that and then everybody's forced into that measurement scenario. So the measurement trap, I made it that morning because I saw yet another post about from a really like from a person I respected. Again, good human beings with good intent, really smart, playing the game of attribution versus sales. And it's like so here's what I do. I take a step back and I try to tell the story from this direction if you can be good at storytelling, then here's how you build out the dashboard. And like, so I jump into, uh, a chat with Claude. And I'm like, it doesn't matter how good the story is when sales is playing by a different set of rules. When sales could just say, we want to go to that trade show, no matter how much it costs. So go ahead and add it to the schedule because our budget is not tracked or because we can explain it because we know we're going to make one or two deals and if we close those deals, hey, budget, you know, we're, we're the ones that make money for the organization. So like, you know, take a backseat marketing, right? Like no matter what way I've seen attribution approached, there is no way to tell that story successfully unless you are doing it hand in hand with sales. And what posts like that miss and what the promises of Hubspot miss is we we have a digital measurement platform and it is getting much better now, thankfully. Marketing events in Hubspot that like you can import your trade show lists into and like, you know, connect things in ways you haven't been able to before. It's better at that. But the digital domain inherently can't track everything. And since it can't, you are having to construct a story without all of the data. Trisha: Because it's shadow data. Chris Carolan: Right. And so you're already Because probably, because probably 90% of a user's interactions with your brand happen out of, outside of your website, your emails, like Yeah. they're happening elsewhere. And so you're you're trying to tell a story with this much of the data and the circle of data is actually this big. Chris Carolan: Yeah. And that's where we get to these two bigger traps like SAS was built to try and solve problems like that and say, I've got a solution for you. So Hubspot's over here saying, do you want to manage your leads out better before? Do you want to handle lead gen? Do you want to be able to attribute your data? Like we can do that. Like just buy our platform, right? Out of the box you get these reports and that's what we're talking about on office hours earlier. Like the difference between attribution and visibility is massive. And if you don't have all the data and all the context in your system, it cannot possibly it certainly can if you get lucky, but the lengths you have to go to to trust that attribution and have it actually be the truth, it's like there's diminishing returns at some point. When instead you could just create visibility to all these things and then have a 30 minute meeting with everybody to be like, oh, here's the rest of the context. Now we know exactly which marketing channels are working and how they're working and let's do more of it because that makes sense. Right? SAS has told you we've got it for you. You don't need to know how to do this, right? Just get another tool, plug it in, right? We'll, we'll solve the problem. And it's not happened. But that's how you get to 70 17,000, you know, martech apps. Mhm. Right? And that's what AI is naturally like SAS apocalypse is here for a reason. It's because of things like this where you don't need all that complexity if you can just make the space for humans to talk to each other and not be like pitted against each other because my marketing software is better than your sales software. And like all these things, meanwhile, everybody acting like animals because in B2B, we don't sell to humans. We sell to businesses, business to business. So we're going to base everything on a company record and an account record and you look at these other systems besides Hubspot. This is always the reason I loved Hubspot. One of the few systems built and designed around the contact record. Like the human being that you're trying to have relationship with, even if they exist in another business, right? Every other system ERPs and accounting and salesforces of the world, it's account and opportunity, right? Are the main things that you're in charge of and contacts we we can call them leads, we can do whatever we want, right? To to classify this human in a certain way to fit our process. And that's where like so it was important for me to understand so that I could create something that was on top of it that had a chance that wasn't just going to keep running into the 50% adoption rates, 70% digital failure. But most of all, when you have a sales leader tell you they know exactly what they want to do to hit the goal, let's say we have five sales reps and they're based on region in the US and we've been tasked with targeting pharma. We know that the answer is to bring in a pharma expert, somebody with pharma domain expertise as a sixth salesperson. Trisha: Done that too. Chris Carolan: We don't know how to lay it across our regional framework and how everybody gets compensated for sales. So we don't do it or it takes us two years to do it. Trisha: Mhm. Chris Carolan: And those are the kind of things. Like even people who ascribe to like playing this game and like like the negotiation and a lot of things I don't align with, when they can't even break through and just handle it, that's a system problem. That's like the system is designed for you not to be able to do things the right way or in a better way or in a high value way. Like how do we solve for that, right? Because if I just brought AI into this, which it will gladly do, by the way, it'll help me get lots of leads. It'll help me, you know, come up with qualification questionnaires. Tell me exactly which other 15 tools I might need or are good for the, the problem that I have right now. But that's not going to solve it like these problems and it won't be AI's fault. Right? Like it's a whole another page on the site about, you know, training data that is built from this space. Um, and it was important for me to set this foundation because I didn't start, well, as AI gets better, like, I'd say middle of Q3 of 24 or Q4, I started thinking about the concept of AI C suite, right? And actually had, like when it was Let's build media, when I first started with Claude, I had a, uh, you know, a chief strategy officer that would help me, right? Um, and it was just a lot of work to create separate ones, right? So I had a CRO and some other things, but it just went to the chief strategy officer because it wasn't different enough. But this concept of like, I want to create the space for a bunch of people to work together, but I don't want to manage people. Like I don't want to manage an organization, like so can we just ask AI to do that and what would that look like? So alongside this, you know, all this is building out and now it's never been easier, you know, to create agents since this foundation of um, and I'll get specific here as we wrap, like understanding all these traps clearly and making sure because like it's just it's a, it's a, it's a blessing and a curse that if I see you're in this trap, there's no way I'm going to sell you something or try to help you solve the problem if we don't also solve the trap. Right? Like it's not in my nature to do that, right? That foundation led to these things which especially with the unified view is creating this decision making framework and framing that people just man, they don't care about marketing and sales misalignment anymore. They don't care about which system is doing what because they know how important the Unified View is. And I never would have gotten here if I didn't understand that, oh, yeah, Hubspot's great and it can have your data, but if it's sales versus marketing, there's no chance. Like if, if the leaders think they can just spin up a campaign and now all the leads are going to flow and that's how they're going to grade everybody on it and Hubspot's the solution, yep, that's not, that's not going to work either. You'll find a bunch of people to sell it to you and deliver it to you in that way, but it doesn't actually like serve the goals, right? So ultimately AI readiness again, like just talk to your humans and understand what your business is and what you're trying to achieve and now AI can actually help you look at the data and be like, oh, there's a gap here. You say that this is important to you, but I'm not seeing any of that data. Is that real? I was like, oh yep, Trisha, we've been trying to get her like, you know, to bring her spreadsheets into the system. Yep. But no, now here's the spreadsheets. Can you help us get them in the system? Because because Trisha's too busy like selling selling a bunch of stuff and making a lot lot of money for the company. Like stuff like that is happening like all the time now. So you don't have to be perfect to like start to use AI to help you be more and more ready every day. But you have to have a foundation like related to like I hope nobody's surprised that it still comes back to like values and like what your value prop is as an organization and who you're targeting and like if you don't know that, your data is not magically going to be ready for AI. Um, hope that was helpful. Uh, I thank you earlier and I mean that a lot. I appreciate you, um, you know, getting these kind of foundational concepts out, um, in relevant ways. Uh, I wasn't thinking about it from an AI data readiness perspective at all, but it's when you ask me directly how I got here, it helps put that in perspective and I think any organization, which is what the goal is here. If you see these traps and it's like, yep, we're in that. I feel that every day. Just start, like if I can put you in a position to say, hey AI, I think we're in the measurement trap. What's that about? Like, that's where you got to start in some cases, so. Trisha: So would your advice then be for anybody who's who hasn't gotten the results with AI that they wanted, um, to go to these 12 traps and maybe just take the information from the website about what the trap is and then feed that into your LLM that knows about your business and say like, does anything in here resonate? Like as a way to get started on how to fix it. Chris Carolan: Yes. Um, and there's also if you go to that trap page, there's a trap assessment, um, look at that, that you can take. Uh, always happy to have feedback on how that works. I mean it's kind of hard like to to genuinely because everybody knows about these traps, right? So it's like, yeah, of course you're in these these situations, but if we can help just say it in a different way, like use it in a different framing, like sometimes that'll that's all it takes to start to make progress with this, you know, this kind of stuff. So, that would be uh a great place to start for sure. And if you're watching us on YouTube, I just shared the links in the chat that I do things like that now. Trisha: Oh, fantastic. I love it. Chris Carolan: So, uh