Jeff Breunsbach: Alright, welcome back to another episode of Chief Customer Officer. We're coming to you live. This will be coming out Thursday, March Jay, what's going on? Jay Nathan: Not much ⁓ have been Mr. Mom over the past three days four four days I know you guys always have sickness in your house too with all the kids and My wife got some version of the flu which was awful. So I was nursing all weekend long so happy to be at my desk and Upright today. So how about you? How are things at your house? Jeff Breunsbach: Getting into things. Yeah. Good where I think we're over the flu. We had we had the flu a couple weeks ago. So My son's my son is in a t-ball right now second practice he had so he's like very Excited into they got to like run the bases They taught them, you know You hit the ball then run to first base and then you wait on first base before you go to second like for the other kid to hit the ball so it's pretty to me it was it pretty I guess eye-opening to it because I I just don't remember that, know growing up but like you know, trying to convince a kid that you have to stay on the base and like wait to go to the next one, you know, and then like trying to convince them they have to, they have to wait to bat, you know, behind all the other kids. Like, it's just pretty funny, ⁓ watching them. So we, we had that this weekend and then just, just hung out with some friends. But yeah, it was, it is, I told my very quickly though. I'm going to have to be. I'm a very competitive person played sports my whole life. I think I'm gonna have to be like off. Jay Nathan: It's fun. Jeff Breunsbach: I won't be the parent that is like shouting and stuff, but I think I just need to be off by myself because I still have the thoughts and don't think I can surround myself with other people. And wife's like, I don't think they keep score. And I was like, I will keep score in my head. ⁓ I don't so, I'm pretty sure. ⁓ Yeah, I know. We'll see. We had the game yet. I think it's still two weeks away from the first game, but I was like joking with my wife. was like, yeah, I'm gonna have to be in the corner, ⁓ just in my own ⁓ Jay Nathan: They don't keep score? What? Socialists. my God. Jeff Breunsbach: even though these three in that shouldn't matter. I can't, no, no, no, I can't let it go. Jay Nathan: ⁓ my gosh. All right. Well, that'll be fun to watch. I'll come to the game just to watch you. ⁓ I didn't tell you this. we're catching up on personal stuff and I knew probably nobody wants to hear all this, but my daughter committed to CFC Vera. Yeah. So Jeff's a CFC grad. If you didn't know college of Charleston. So my daughter, ⁓ that's right. Yeah. Yeah. Yeah. So we're excited about that. All right. But Jeff Breunsbach: Yeah, that'd be great. ⁓ cool, that's awesome. Yeah, and my wife, we have two in the household. Yeah, that'll be awesome. She's gonna go the whole downtown experience though, right? She's not gonna live at home and go to CFC. Jay Nathan: Yeah, yeah. ⁓ yeah. That's absolutely yes. That's happening for sure. Yep. Yep. Jeff Breunsbach: Awesome. All right. Well, I think we've heard from the people that about what we're doing with AI in our businesses is probably the most interesting topic. So we're going to share a little bit about some of those things today. But before we do, think there's the article or there's many articles now making the rounds. That would good to maybe just surface and talk through it a bit, see if we have Jay Nathan: Yeah. Jeff Breunsbach: you know, similar or differing opinions, but block laid off, think roughly was it 6,000 employees? Yeah. ⁓ 4,000. Okay. ⁓ and so I feel like I've, I've seen now, I've probably myself seen seven to 10 articles and half of them lean one way, which is like AI is coming for everything. This is like the reason of AI. The other half is like, Jay Nathan: half, 4,000. Yeah. Cut, off half, you know, about half their team. Jeff Breunsbach: Well, if you look at their hiring patterns and some of the past behavior of Jack Dorsey kind of mismanaging businesses, it looks like they over hired. And so, you know, I think that's kind of the both sentiments maybe from either side, but I'm curious, what's what's your opinion so far? Jay Nathan: Yeah, a couple data points here. Number one is when Elon bought Twitter, remember what he did? He 80 % of the workforce. And guess what? Actually, think Twitter's probably, according to many people, is in better shape than it's been in a long time, right? With 20 % of the employees. don't know, maybe that's crept back up a little bit. that's one data point. Another data point is in 2019, 100 employees by 2022. They had 12,000 almost 12,500 employees during COVID. Yeah, like that was a big like hiring binge for them. And I don't know that their that their revenue and their margins of certainly their margins could have increased correspondingly during that time. But obviously now by 2025, Jeff Breunsbach: So they hired 9,000 employees over... Wow. Jay Nathan: they were back down to about 10,000 employees, right? Which is where they're cutting from today. They were at about 10,000. But I think what this is highlighting is that we're seeing more and more software companies using AI or intelligence. They're not even saying AI, but these new intelligent tools as being part of the reason for these layoffs. want people to think about and understand here is that. decisions are being made independent of the technology itself. What I'm seeing with AI tools, we're using them every day now, Jeff and I talk about that on this podcast, and we'll dive into that a little bit later as well, more of what we're doing. they replacing parts of jobs, in cases, still not replacing entire jobs, at least in the tech world. They're making every individual we have on our team much better, and probably do more of the edge work, edge case work that they wouldn't have done before because now we can sort of automate some of it. But in general, I have not seen replacing people. In fact, we had Olson the podcast last week who's the chief legal officer at BlackBaud. He's got a team of 14 people. now have an agent they use to do redlining of their customer contracts haven't cut. a single person off their team. that presumably would have taken a long time for people, but have lot of other work. They have acquisitions, they have partnerships, they presumably lots of legal matters to be dealt with. And that's just one department ⁓ at BlackBot, never cutting out of that team based on this technology. I think to say intelligence, quote unquote intelligence or AI, this technology is the ⁓ reason for these cuts. Either you have a reason to say that, so think Salesforce, right? And their big layoff a couple years ago, they're trying to sell Agent Force, right? Which is their agentic platform. you're trying to use AI as air cover for cutting a large part of your staff, which probably should have been done many years ago. Something we talk about a lot, right? On these and our newsletters and just being efficient with capital. 2019, 2020, 2021, 2022, much like year from financial crisis of 2008, nine forward. That's not really reality for technology companies, right? was very much by investment dollars rather than customer revenue dollars. anyway, that's my on it. Jeff Breunsbach: I think I landed in the same think the, I would say like the one thing that I picked up from, ⁓ read like Dorsey's statement. And the thing that I did find interesting is that he said smaller teams ⁓ with autonomous, with this technology, with these two intelligence tools are driving like better outcomes. I do, I just think that's an interesting nugget to me because You you start to think about how businesses over time, right? You start to just build up and you kind of just, you know, end up having people doing work, getting things done. ⁓ I don't, ⁓ I think this is like, I don't know, like some, I don't know, big gold nugget that he put into this statement, but for some reason I like just focused on that because I started to think about like, yeah, what are, to me, like, what are some of the best teams that I've worked on or that I've been a part of? And it's usually small. Jay Nathan: loop. Jeff Breunsbach: nimble, quick teams that have autonomy that are making decisions and that are like getting the relevant information quickly. And so I think like to your earlier point, right? Like, do these intelligence tools help us to do that? And I think like the answer is yes. And so like, if you can get the right teams together, and you know, in the right kind of fashion, and then put them onto specific problems in your business, I just keep thinking about how that's got to be a good recipe for success right now and like, You know, it's not like, okay, let's just get more people doing all of the same work, right? But like, how can I get more focused people doing work on specific things that are going to drive something forward and then give them these tools in order to go actually do that. Right. So I think what's interesting to me or some of ⁓ conversations I've had recently have been with lot of like rev ops people. I've been in this like rev ops kind of CS ops world for the last like month to two months because of kind of deploying some technology at my company right now. And I would say like a lot of the interesting conversations I'm having is, along the same veins that you mentioned, but it's lot of, Hey, I don't actually need to go get almost like a full-time Salesforce developer or a full-time like backend developer, because I can now use tools like Claude code or Claude cowork to essentially like get this information more readily available for me. And even like some examples that I've like done myself, right? Like I can feed in, Claude cowork. to our HubSpot MCP and then I can ask Claude Cowork questions like, hey, tell me what our schema is for contact records and then tell me which fields are being used the most, which fields have actual data piping into them and then show me all the fields with all the records that are relevant. like, so I don't know, like this to me felt like years ago you'd have to kind of have a full staff person who is like only doing. Jay Nathan: Mm-hmm. Jeff Breunsbach: these like one technology or only doing these technologies are the only person that could kind of engineer this stuff on the back end because some of these UIs are complicated. think some of these admin consoles are complicated. now I think like these MCPs are almost like bringing some of that information forward where it's like, I can start query. So like, you know, in the matter of an afternoon, ⁓ actually on like what I spent my time doing in an afternoon was I said, Hey, here, I want you to map all of my fields from HubSpot. Jay Nathan: Yeah. Jeff Breunsbach: that we use across contact company and deal records. I want you to go, and then I set up a plan hat MCP and I said, I want you to go to plan hat. And I want you to tell me like, which fields am I missing in terms of like mapping over that you feel like would be most relevant. And it came back with a field list of about 20 to 30 fields and then reasons why I should add them. And then, you know, for me to basically go and a button and add those into the systems. And so like, I don't know. work to me, like you were mentioning earlier, feels like it's much closer to the business side of things versus just solely being a technical person. Jay Nathan: Yeah. Well, and there's a lot of advantages to that, right? Because there's nothing lost in translation there because you know exactly what you need. in a smaller company, that would have been a part-time role. Like you probably wouldn't staff a full-time person on that kind of work because there's just not quite enough yet of it to be done. In a larger company, you might have two or three people doing that kind of work all day long, they can actually, the list that those people have to work on Jeff Breunsbach: Yeah. Jay Nathan: is way longer than they'll ever get done, right? They oftentimes are just sitting in defeat because they can't get to the end of their lists, There's just so much to do. The roadmap is so long, but these tools will speed them up. So ⁓ got the dual effect of maybe you wouldn't hire that fractional HubSpot person, right? From an agency or ⁓ an contractor, but Jeff Breunsbach: Yeah. Yeah. Jay Nathan: you'll be closer to the work. So it's got that benefit and then it's got the benefit of speeding up the three people who were working on it full time for a thousand person company. I was gonna ask you, how did you set up the MCP Did this plan already have that or did you have to create something? ⁓ Jeff Breunsbach: So they have, they've got like a configuration. I to go into essentially like Cloud Co-Works JSON files and like set up access to it and like get my credentials and like ⁓ off codes stuff. So I'm delving in territory that I don't know about, but I just like followed some instructions. It was pretty, honestly, like pretty like somewhat simple to set up. And then again, it still, you know, uses like our API credentials to access it. But they've got effectively like kind of three modes set up across the MCP that you're able to query certain things and into essentially all the data models that they have. Jay Nathan: So just for everybody's edification, you know, we don't ever, our goal is never to talk down to anybody here, but just so you understand what MCP is, that's like the, it's like the API for AIs to talk to one another. And so that means I can talk to HubSpot has an MCP Pendo has an MCP server that you can turn on plan hat clearly has one. That means you can talk to your those platforms from whatever LLM you're using. if you're using chat GPT or Claude, Claude, co-work, even a better example, then you can actually interact with those, with those products there. So yesterday, for example, Jeff, what I was doing, I literally spent five minutes trying to figure out how to enter somebody into it. Sounds ridiculous, but I was like messing around with HubSpot trying to get a record in there. I was like, what am I doing? I had already connected my MCP or connected HubSpot's MCP to my Claude cowork instance. And so I was like, you know what? I'm just going to tell Claude to go update the record in plain link, plain English. And it did it. And I was like, why was I farting around with it now? The thing that I do think, and this gets into a little bit more of the technicals behind it, but it's, I think these tools are still wildly inefficient when it comes to ⁓ they call token usage, meaning like for updating a record, it sits around and thinks a lot and it tells you how many tokens it's using. It's like, Jeff Breunsbach: You Jay Nathan: wow, basically you're using electricity right now. That's the downstream impact. think it's going to be really interesting as things continue to evolve. One of the disciplines that, and gets into something else I want to talk to you about, but one of the disciplines of building products around these AI tools is using the right models at the right time for the right purposes to make sure you're not overspending. ⁓ Jeff Breunsbach: Yeah. Yeah. Jay Nathan: Are we making efficient use of the tokens that we're generating for the task that we're trying to complete for our customer? That is a skill engineers going to have and yeah, are going to be able to. Jeff Breunsbach: And, and, and, um, like along that, along that same vein, there was something that, um, startups in AI, uh, Jason, I can't think of his last name right now. It was part of the all in crew. Um, one of the Jason's, uh, Calic anus, he, um, there was something that I thought he, said that was interesting. This is now probably a couple of weeks ago, but he basically said like, as you start hiring people, now you're starting to think about not only like Jay Nathan: ⁓ Calacanis. Jeff Breunsbach: base salary plus benefits plus bonus, but you're also thinking, okay, I'm going to put like a token usage per person. so like, are they, you know, like now if I'm adding a hundred thousand dollars worth of tokens to Jeff's salary for this year, like is Jeff producing, you know, X plus a hundred thousand dollars. Like, that, is that part of it? And so think like to your point, like that's part of the equation. The, um, the other nuance that you're talking about, which has, uh, I was thinking about this weekend when I was interacting with like Claude cowork was Jay Nathan: Yes. Jeff Breunsbach: just how, frustrating UIs have been to us, I think over the last years. And it just like to me, even in like tools that I'm using today, I'm still like, I can't believe I can't just like drag and drop that thing over there, move this over there. And it's like, so frustrating. And then working with like Claude Cork, I just kept thinking like, wow, are you eyes kind of like. I think of the past almost right. Like our. Jay Nathan: Yes! ⁓ my god. Yeah, yeah, yeah. Jeff Breunsbach: data entry, is that ever really going to exist in a button click, find the field format, or is it all going to be text based? And then you're just going to have a bunch of charts. But it just makes you, I don't know. So it made me start thinking and visualizing like, okay, software of the future, the interfaces with humans probably looks different and it probably feels different. Like there's just an evolution that's going to happen. Yeah. Jay Nathan: Yeah, it's natural language. It's natural language. It's not this field. Now I will say you always need a backup. Like you always need to be able to go into these systems and tweak and tune. Cause I could tell you like even this is interesting, right? Like even I was using Opus 4.6, which is Claude's most expensive best model, right? To, run those cowork tasks, to go update a few records in HubSpot. And it's still got a couple of things wrong. I had to go in and tweak it. Right? So like, Jeff Breunsbach: Yeah. Yeah. Jay Nathan: That's the other thing that to give everybody some peace of mind. If are a doomer and you think, my God, my job's going away, like it's not going away anytime soon. And by the way, like, as these tools get better, you're going to evolve and you're going to be doing other things. So like as as these tools are getting, they are still not good enough to go without a user interface. And, you know, I was listening to Monday.com CEO. on the 20 DC podcast last night. I'm always interested to hear how these public SAS CEOs are thinking about, like, I want to hear their perspective on the future of SAS. We could other thing, you know, we could talk about is just of that the whole SAS apocalypse and stocks crashing the past couple of weeks. Monday dot com was hit really hard. But as you listen him talk and if you use these tools, you see that, OK, like we are not going to be able to do without systems of record. No way. I do think is going to be really interesting, the way that existing companies can win, here's maybe controversial take. I'm sure many boards and CEOs would take issue with this, but I think it's probably one of the only ways for the incumbents to really win. This is all about disruption. Jeff Breunsbach: Yeah. Jay Nathan: know, native companies that are building with AI first, not having to learn how to do that slowly and painfully like maybe ServiceNow is or HubSpot is or Salesforce I the way for these companies to really lock in their advantages, ⁓ are their existing customers, brand, current contracts ⁓ that lots of remaining performance obligations, which is basically our partners, they have an ecosystem. Jeff Breunsbach: partners. Jay Nathan: to lock in those advantages is to go in with an aggressive strategy to disrupt your stealth, starting with the pricing model basically to your customers and tell them, okay, for the next 24 months, every time you get an invoice for us from us, you're gonna see something happening. You're not gonna see your price going up. You're actually gonna see it going down. And here's how that's gonna work. Because right now, like I'm looking at HubSpot, I love HubSpot. We love HubSpot as a company. Jeff Breunsbach: Yeah. Jay Nathan: Like obviously one of the leaders in our space, they've been innovative, but I can't justify what I pay for HubSpot, frankly, for what we do with it. And I want more. I need more of the capabilities. I'm just not willing to pay what they're trying to charge for it. Not when I, in theory, could go out and build it myself. I'm not going to do that to be very clear. I do not have time to build my own CRM. And I think that would be a foolish thing for me to do. But, Jeff Breunsbach: Yeah. Jay Nathan: I think companies should, have to have a self disruption strategy. Now to be able to do that, have to have funding to do that, whether it's through your own profits or through outside investors who are willing to go on that ride with you. And I think that's what monday.com is going to do. At least that's what their CEO described on the 20 VC podcast that I listened to yesterday. But it's almost like the days of moving from on-premise software to SAS. They called it swallowing the fish because What would happen is in on-premise days, you'd buy a piece of software and it was like buying a car or buying a computer, right? It's like you paid a big lump sum upfront. The software company took all that revenue on their P &L on day one and, you know, charged maybe a 20 % maintenance fee for support over the next however many years they used the software. If it went away, it wasn't that big of a deal because they were working on the next big software sale. Treated it like a CapEx kind of spend. As you move to SAS, you get into this monthly recognition model where the purchase, I now have to spread that out over the course a two years, three years, one month at a time, and the revenue appeared to drop. Adobe famously cut the cord and said, we're going all in on subscription in SAS away from this one-time purchasing model. And they got beat up for it for a while. And then they came up. out of that way ahead, right? So I started drone on here, but I think like the same kind of disruptive is happening now. The cost of building software is going down. you to, somebody else is going to disrupt you. In your margin is my opportunity, right? Your gross margin is my opportunity. So if could build the products faster, why wouldn't I go in and undercut? the biggest SaaS companies on the planet with a much lower price point solution and to reap some of the benefits of what they've sown. ⁓ I think you gotta do it yourself before it gets done to you in this new world. Jeff Breunsbach: The other thing that I'm sitting here thinking about too is, you know, I feel like over the last number of years, acquisitions in software have kind of meant, you know, I'm taking big software A and big software B and I possibly, you know, it's way too hard for us to basically squish these together. So like, we're just going to, I'm going to acquire B because I want them as a part of our portfolio. And essentially then we'll have two products that we can bring to market. I don't know. That's usually what I feel like the most strategy has ended up being because okay, this is the easiest way for us to basically not create a lot of tech debt or like ways that we need to basically like, we don't have to spend a lot of cycles trying to like merge these things together when we can actually just go to market with both of them because they serve a purpose in the market. And I wonder now too, if like the way that coding and like the cloud codes of the world and everything are coming together is like. there actually an advantage to acquiring some of these smaller, like you said, the smaller AI first nimble companies that are building because there is actually easier ways to basically take that. I'll call it point solution or early solution and actually embedding it into our larger solution. Like, is there actually an easier way for us to do that? Now these tools exist. and you were mentioning, right? Like the kind of the cost per or the cost for us to essentially build these solutions is going down. Like, does that also mean some of these incumbents could actually make. acquisitions kind of earlier, faster and saying, Hey, that might be a point solution that turns into something great. Let's just buy it now. So we have somewhat of a speed advantage there, get ahead of that company, hire that talent and just put them in here and just say, Hey, why don't we actually just build that as a part of this solution? I don't know if that's actually true or that would happen, but it me thinking that maybe acquisitions are easier to sew together with like the way that coding, like, you know, kind of these tools have come up with AI. Jay Nathan: I mean, in theory, in theory, yes. I mean, I think the answer to that question is probably pretty wide and varied depending on how all the platforms were built. Jeff Breunsbach: Yeah. The reason I thought about this is like, I think I read an article, I might be getting the numbers wrong, but I think Salesforce has made something like six or seven acquisitions over the last 10 months. And it's all kind of around agent force. And so just got me thinking to like, ⁓ I wonder if they're like kind of spotting deficiencies and then just kind of like all of sudden try and like merge all this stuff together and basically come out with agent force 2.0, but it's all still on the same platform versus all these point solutions that you're trying to sell separately. Jay Nathan: Probably. Yeah. Yeah, maybe. mean, Salesforce still has Slack, which is largely independent, right? Tableau didn't they buy MuleSoft? They just bought it something else to it was an Informatica. I think they might've just bought Informatica. That's an old company, right? data tools. I'm sure they're having a resurgence. ⁓ What I listened to. sorry. Go ahead. Jeff Breunsbach: Yeah. ⁓ No, go for it, I was gonna switch topics, but. Jay Nathan: Well, I was just going to say like on that topic, I was listening to the CEO of Palo Alto networks. I think he was on Brian Halligan's podcast. The it's a pretty cool podcast, by the way, if you haven't listened to it. And done a couple dozen acquisitions in his time there and they've all been meaningful. I maybe all I'm sure, you know, historically, you know, if you look at acquisition strategic acquisitions, meaning one technology company buys another technology company and they think there's a better together story. Only 35, 30, 40 % of those work. Most of the time they just fail. Jeff, I think you and I have been part of maybe a couple that didn't turn out so well, right? And we've been part of once I did as well. But one of the things he was talking about in that discussion and part of their playbook for those acquisitions is They build the product roadmap for the combined solutions before they close the deal, because they're trying to keep the founders involved. They do all kinds of stuff with the equity and the compensation to make sure that the founders for several years and help complete the vision. part that is actually having a vision. ⁓ So your point, that's where a lot of acquisitions fall down. like, hey, let's hand These things will be better together. It'll be great. Jeff Breunsbach: Mmm. Yeah. That's cool. Jay Nathan: Okay, great. How? Well, we'll figure that out later, but there's no figuring it out later. I promise you. Like it's hard. It's always hard. So. Jeff Breunsbach: Yeah. Yeah. Yeah, I'm with you. I know we've got probably about maybe 10, 10, 14 minutes left, 15 minutes left. So a of things I thought would be fun is just talking about, you know, stuff we're working on stuff we're doing. So one thing that I've gotten in motion wanted to talk to you about and see if you have other ideas that I could be augmenting. So ⁓ I had our team kind of go do the grunt work. So we had to go do some, ⁓ entry. but we've essentially now got all of our upsell and cross sale deals, captured at least the ones that are kind of active that we're working on. And that's like visibility we didn't have before, just, you know, because process and kind of data hygiene didn't exist. And so, you know, now I've got roughly, I'll call it like 30 ish deals that are in play that we can, you know, we're kind of working on, we're staging. And so, you know, I was talking to my team about, built a rubric of staging, right? Here's the stages, kind of like one through five about where a customer could be, you know, are we demoing, we in negotiations, are we closed one, like those types of stages. And so, you know, I built a rubric, I trained them on this and we're kind of walking through what are some of these questions that you need to answer, stage gates that need to help you move, you know, and. And it just got me thinking, well, I think AI can also help us solve this, either by surfacing that information directly to the CSMs that they can fill it out or by also going to actually fill it out itself. And so we use Fathom as a call recorder. And so what I've got right now is ⁓ the of it. So it's not working yet, but I've got it set up in theory. And so essentially what it's doing right now is feeding the ⁓ call into PlanHat. Plant hat then is surfacing up either open AI or Claude. And then we're running a playbook on top of that, that essentially is looking for key information in order for us to then put it into specific staging. And then having it actually move the deal to the next stage. And then it'll also capture key deal notes. So like what has changed from ⁓ the before, what's the same and key deal notes. Think about things like, you know, their volume looking like? What types of tests or panels do they want to do? Like kind of key information will be valuable for us. It surfaces that and puts it into a field called key deal notes. And then the next action step is actually like a, I usually think of it as literally like what's the one next action we're taking on this. Like if there's nothing more you can have. And so then it actually puts the date and then puts the next action step in there. And then kind of all three fields are updated for the CSM. And so really what I'm asking them to do that at this stage is just go validate. those, like you said, like we need, ⁓ kind of need to go back and do the double check. But, it logs all of that in the actual deal record. And then it also still logs the Fathom call with like the full transcript and it's got key details and other things in there. So again, I've got it kind of like wired up. haven't pressed the button to make it work. So I'm sure there's going to be kinks, but I'm pretty excited about it. think it just, to me, there's a couple advantages. One, again, reduces the manual nature of data entry. Two, Jay Nathan: Yeah. Jeff Breunsbach: I think it also starts to create more of a systematic approach to staging and forecasting and accuracy is like, okay, we're at least we're having a single model do this versus who all have different opinions about what stage three means, even if I give you criteria. ⁓ and then the third part to me is, is I think this is, I've kind thought of this as like a cliche about like how call recorders like sell you the call recorder. Jay Nathan: Yes, that's exactly right. Yep. Jeff Breunsbach: But like, I do think it actually keeps the team focused on the actual customer conversation they're having versus worrying about capturing notes, capturing, okay, they said this, let me go capture the 15, you know, like I've actually seen and watched these like call recordings, right? And you just start to see how the behavior changes of our team where they're like locked into the actual conversation. Oh, okay. So tell me more about that. Like why, and they're not, I don't know, they're not looking down with their notepad. They're not changing eye contact. Jay Nathan: Yeah. Like, hold on, let me, let me, ⁓ let me write that down real quick. Let me, let me take a note here. None of that. Jeff Breunsbach: Yeah, yeah. I actually think it kind of carries more weight with the actual relationship we're building with the customer. like, okay, I'm actually locked into what we're talking about. So those are like three things, three advantages I see from it. Jay Nathan: Totally. Yeah, that's great. I think a lot of sales teams are starting do this. hear more and more about pipeline using tools like this. Of course you got to trust but verify it still right to your point. But the I really like about what you said is that your criteria for what stage of deal is in can be a little bit more objective as opposed to ⁓ subjective. And maybe teaches every team member a little something too. Like you can train your model. You can train your agent to say, Hey, look, like this is not a stage four negotiation deal until we've actually sent a contract and you know, blah, blah, blah. it will be able to pick up on that and say, well, it actually gives you reasons why it's not stage four, right? Because it knows that you have not had that conversation about the contract yet. ⁓ Same thing with renewals, by the way, it's just a different type of opportunity, but renewal opportunities, cross sell upsell opportunities. Jeff Breunsbach: Yeah. Jay Nathan: even softer items could be done the same way. Jeff Breunsbach: Yeah. the last point I'll mention, and I would love to hear, you know, you're working on something right now, but, another activity I did with Claude cowork yesterday was, we have not historically, we have not created deal records for renewals. So kind of all I have in HubSpot is just the original deals that we've closed. that's kind of it's in there. So I asked. Cowork using the HubSpot MCP. ⁓ Jay Nathan: Mmm. Yep. Jeff Breunsbach: I said, I need you to go look for this criteria of customer, basically current customer has a deal that's closed one. I need you to pull all those customers. I need you to pull all those deals. I need you to replicate those. And then I need you to essentially pick the future renewal date, the close date, it would most likely be at some point this year or next year. And then I want you to carry forward a bunch of information from that deal, like products, SKUs that we're using. of relevant information. And so then it pulled the list. I think there's, you know, a couple deals that essentially I just created yesterday because I was able and ⁓ I didn't have go do I didn't even have log into Excel and say, Hey, let me copy and paste these rows. And I didn't have to figure out the lookups. You know, I mean, like, this to me is just like another like one of the advantages where I literally told it to pull all those things. I mean, I did some spot checks and like made sure Jay Nathan: Mm. Jeff Breunsbach: And now my team's going to go through and do spot checks. But essentially now I've uploaded a couple hundred renewal records into our renewals pipeline that has all the relevant details from the original deal. It's got the ARR involved. It has the future close date coming up. like within, you know, again, kind of a day, I was able to essentially now create visibility, not only for upsells and cross sells, but now renewals. And then like you said, like now I can have the AI do not only upsell and renewal staging or upsell and cross sell staging, but renewal staging as well. Jay Nathan: And now you can a forecast based on those renewal records. You can have team validate, you know, whatever the AI forecast is ⁓ for, those, then have, you can facilitate a meeting with your team where you have them sort of walk through their accounts that are coming up for renewal in the next, you know, 16 to 90 days with the current status is, and then you can teach your team how to think about renewals, right? Right. Jeff Breunsbach: Yep. Yes. Jay Nathan: That's just a big difference from like, you know, and praying that your renewals are going to come through and that you actually have something to work against as a leader. Jeff Breunsbach: And so the last thing I'll mention, then I promise you, we'll get to you, is because the other thing I got excited about is like, for these upcoming renewals, I have not created this yet. I've just written the idea down. But could you actually create an agent that tells you what type of deal options we should put in front of the customer? Right? So usually, like right now, we're only selling like a 12 month contract. That's just typically been what we've done historically. And so now, not only are like Jay Nathan: It's okay. Yeah. Jeff Breunsbach: I want to create a standardized rubric, right? Hey, here's some options that we can go with the customer. Here's certain, you know, numbers that we need to stay within or percentages or whatnot, but could actually just feed that rubric into an AI that lives within plan hat and looks at every renewal record and basically says, Hey, I think this customer is most likely like this option is most likely going to be the best for them. And that way, like ⁓ CSM now has guidance on like, deals we can present to the customer, what we can put in front of them, numbers, percentages, whatever that is, but that can live within a deal record. historically, that's just been another challenge. We have go to the sales team and ask, hey, how would you price this deal? again, so just another option an AI agent that could essentially help us price out and scope renewal deals. Jay Nathan: 100%. 100%. And I would say your next frontier is I'm just giving you the roadmap here. You know what I'm going to say because you've done this with me before. like at some point having a bunch of CSMs managing a bunch of renewal opportunities is probably going to break down. And so where we found success or Jeff and I felt success on this before is by carving off that renewal motion into a very specific team because of what you just said, right? Negotiating renewals getting sort of the most out of renewals from the most value and getting the most value in return from a business standpoint. You want somebody who thinks about that all day every day, and that's not necessarily a CSM. A should be about how do we make sure the customer gets the most value out of this product subscription that they have every single day? And then ⁓ we can of. put the commercials over to somebody else, then you don't put them in a weird spot of having to do both. I think that's a scale. It's a privilege of scale, right? You get there at some point, but ⁓ then to be able to have that rubric and have AI help with that decision point as a starting point a ⁓ powerful thing. So, cool. Jeff Breunsbach: Yes. Yeah. And I think like the thing that's been interesting to me is, is, think there's like a bunch of tools that are out there that are trying to become, I'll call them point solutions for AI agents. And I do think there is something of, of value that I've got right now where I have a system of record that also is building agents inside the system of record. And I just think that there's like a power of like, okay, now I can manage the AI agents inside of the platform that like my team is also managing like our whole stack. of customers. so like, I do think that there's like, that's been an advantage for me, like, at least right now, because I don't have to go fiddle with connections between tools, I don't have to go, you know, kind of build extraneous ways to get that data into like the tool that I'm using, like, there's just a lot of like speed advantages that I feel like it's it's had right now. Again, there's probably some great, great solutions that are out there. But like, I think like, that's another thing that I'm thinking about right now is just I have been a ⁓ Jay Nathan: Yeah. I agree. Jeff Breunsbach: In my career, I have naturally let technology sprawl because I get interested. think there's something cool, right? Like it just, it's kind of natural to all of sudden, oh, we had two tools. Now we have four. And it's like, it's all right. We'll keep managing them. But now I don't know. You start to see how that disinvent, this is a disadvantage of speed because now I've got to worry about four tools, manage four tools, think about all the fields, the mappings, the integrations. And so, um, I do think like with all this AI technology, it is trying to figure out like, okay, how can I actually bring the tech stack back closer? Jay Nathan: Yeah. Jeff Breunsbach: to each other and like only focus on a couple things that can do it. Jay Nathan: Yeah. I mean, that's why I'm sort of rooting for HubSpots in the Salesforce is of the world, because that's actually the best place to do this stuff, right? Not in a silo somewhere else. And you know where I'm going with that, right? So I'm not going to get into anything, anything too deep, but I'll give you like just a, but I'm not actually working on this, but I had a call with a good friend of mine who is, who is just taking a new role at a pretty large SAS company and he's pivoting. Jeff Breunsbach: Yeah. Yeah. Jay Nathan: the customer success motion there to be 100 % focused on customer value, I would call the value journey, the customer's value journey. So everything we talk about when it comes to renewals and adoption and implementation, ⁓ all steps that we have to do with the customer to get them live to first value, to ongoing value, that's all, I call that service blueprint, right? That's how we provide our service. That's not the customer journey. The customer journey is, Okay. I bought this product to get return on investment or X value out of it. How am I evolving to get there? That might include organizational transformation. It might include technology adoption. It might include training and enablement for people to things in a new way that they've never done them before. And so he is built an entire, what I is the future customer success platform. Jeff Breunsbach: Yeah. Jay Nathan: which has nothing to do with account records and customer contacts. It has everything to do with where is the customer on that journey using whatever data we have to inform it and to drive those conversations with them. It has nothing to do with the service blueprint. It has everything to do with value. And so I think further, like more and more, we have to keep those two concepts separate as we build these systems out. But we can talk more about that one next week. I'm hoping he'll come on and talk about it at some point once he He's got to get a little further along and roll it out to his team, but then he wants to come on and talk about it. Jeff Breunsbach: the, the one thing I'll just say quickly too is I think that might be the most clear way I've ever heard somebody talk about the customer journey versus the service Like I, I now it has me like thinking about how like the customer journey really is ⁓ all steps of change management that the customer has to go through from point A to point B. in order to realize the most value. that's things that just like live outside of the software. It's stuff that lives in the software configuration, probably in best practices and things, but it also is like the enablement, the change management. How are you enabling the stuff outside of our software? And I think like that to me is like, like you just described the customer journey. And then, I dunno, that's just like the most, that just like almost in my mind and printed implanted a vision of like, I mean, in our, in our onboarding deck, we should have a slide that basically shows that like, Hey, if you're going from point A to point B with our solution, here's all the things that need to happen. And like, here's how you do that across all those. I don't think that's as clear today. So it's interesting. I love that. Jay Nathan: Well, there you go, Shelby. There's the newsletter for this weekend. Maybe we could have her help us out with that. I like it. We probably have written one on that topic at some point in the past, that, you know, it clarifies things. All right. I got to jump. All right. That's the podcast. Talk to you soon. Bye. Jeff Breunsbach: Yeah, it'll be cool. Yeah. Yeah, alright cool. Sweet, it was good to talk to you. Alright, we'll talk next week.