From CRO to CEO: Nick Turner on scaling Dreamdata and building trustworthy AI

Speaker A: Don't spend time thinking about man, I'm not AI native. I'm going to fail. Like that's just not accurate. You can learn how to use AI both in your product and maybe also more importantly across your organization.

Speaker B: Welcome to the SaaS Revolution Show, a podcast by SaaS Doc. Here we interview SaaS founders from around the world who've been there and done that as they share the ins and outs of how they built their businesses, their operations, their path to securing investment and more. Our mission with the podcast is to help you, the founder, uh, learn how to scale your SaaS, maintain your wellbeing and navigate the complexities of this ever changing industry. I'm your host Alex Diemer and together we'll explore the good, the bad and the ugly in the journey to SaaS success. Meetings at events suck. We've changed that with Meetup coming to SaaS USA this April. Meetup is a one to one meetings program that'll deliver over 12,000 pre scheduled 15 minute conversations with the partners, customers, peers and investors who can move your business forward. No more wasted time, just purposeful meetings with exactly who you need to meet. Register by March 20th. Secure your place at the AI&M B2B Software Industries largest meetings event. Find out more at sas.usa.com meetup. Welcome back to the SaaS Revolution Show. I am your host, Alex Sumier, CEO, founder of SASDOC, also general partner at Back Future Ventures. Uh, today I'm delighted to be joined by Nick Turner who is the CEO, ah, at Dream Data, uh, joining me all the way from New uh, Jersey. How are you doing Nick?

Speaker A: Good, thanks Alex.

Speaker B: Yeah, good to, good to have you on the podcast. Uh, Nick. Um, uh, so recently. So actually you know the date, the dates that you announced, uh, the series B for Dream Data was actually the same dates as uh, sasdoc Europe. Uh, a coincidence, uh, I'm sure, um, uh, many fundraising announcements around that time but I'm sure yours was a coincidence. But uh, congrats on that. Uh, I think a sizable series B, 55 million. Um, tell us a little bit about um, maybe that journey from A to B, how long that take, what were the kind of, the milestones, had they shifted in this I guess kind of AI era that we're in and the metrics that VCs ah, are looking for creating growth within companies.

Speaker A: Yeah, yeah, thank you very much. You know I think we were very fortunate. Uh, we had a very good run from series A to Series B. I think the series A was, um, I joined after it was maybe late 22 is when we did it. Um, and so I think that was a, you know, roughly like I think 10 million funding round. And so, um, uh, yeah, I would say that not a lot around metrics have changed. I think obviously there's a lot of parts to how you pitch. And I will say this, this was my first time leading a funding round. I participated as basically a supporting staff, you know, to, to someone doing a funding round. This is my first time and I think, you know, so I didn't really know what was right or wrong to do. I was fortunate to have a lot of good guidance from, from board members and from uh, from our CFO Peter. He and I had a very long summer and spoke to a lot of, a lot of different investors and that was a, that was just such a great learning experience. But you know, I think the same things are, are, are true, but there's a lot more around. Everybody wants to know what are you doing with AI? Um, and I would say especially, you know, you dealt with a narrative of, of people saying hey, are you AI native? And, and are you what they call like legacy SaaS? And um, I think a lot of interesting conversations around that, especially for us. We were founded in uh, 2018 and so inherently you can't say that you're an AI native company. And I should also say when people say AI, they really think generative AI LLMs. And what are you doing in AI? You know, AI as a whole has been around for a very long time and we've been using it in our platform for a long time as well. Um, so that was a huge kind of topic of conversations. Every time is just like you mentioned, what are you doing in the AI space and how are you adapting to the new environment? So that came up quite a bit. But the metrics, I mean, look, depending on the type of uh, investor you're looking at, you've got your kind of pure vc, you got your growth equity, even private equity and things like that. I think every one of them has different like things that they want to see. Um, and so in a, in a pure VC world, you know, they want to know, well, how are you going to grow up 4x next year? Things uh, like that, you know, and, and they might care less about uh, retention, um, in a, like growth equity world, growth, uh, rates are maybe a little bit lower. They're less concerned about that. They really want to know how are your retention rates. That, that was a key, ah, a key discussion. And not that VCs don't and pure VCs, uh, don't care about that. But I think that it comes up more often as you move on the scale of pure, uh, VC going up to like private equity. Um, the other thing, I'll say that maybe I did, uh, maybe it was wrong again, like I said earlier, I don't know. But I have a very strong belief around what you focus on when it comes to retention. In the early stages of company. Um, everyone talks about net revenue retention. And um, I actually would prefer to focus on something called gross dollar, which doesn't take into account upsell. Um, and the reason for that is that net revenue is what you would just call a composite metric. It's made of two things. And when you're looking at a metric that's made of two things, it's very easy to hide. It's very easy to hide a problem. And often if you're not focusing on gross $, the problem that you're hiding is that you're not focusing on your icp. Um, so that means that you can kind of assign any deal that you want just in the name of growth. Right? Um, and um, if you do that, then you end up with churn problems down the road. So that was one of the things I did when I joined the business. I immediately kind of refocused this on a gross dollar retention metric because I wanted us to hone in on an ICP and then make sure that we could improve that gross dollar retention. I'll stop for a second because I might be getting too into the weeds. But, uh, that's.

Speaker B: Into the weeds is good. Do you think, um, that uh, that focus was something that you brought from, uh, I guess the CRO position into uh, the CEO and that sort of mindset?

Speaker A: I think so. And just to be clear, you know, I took the CEO seat six, uh, months ago. Uh, so when I joined the business it was CRO. And that's kind of when I made that change. Um, but I still believe in that change. Uh, and I think, I think every, uh, once you get to a certain point, it's different for every company. You can't say, hey, when you hit one and a half million ar, you should do X. You know, you can't, you can't say that, but you need to have a feel for when. Do I really need to weed out the companies that just aren't right for us? And I felt at the time was, was kind of right when I, when I joined the company said let's, let's make this change now. So we know that we're focusing on good customers and we're going to pick up our retention rate.

Speaker B: Maybe, uh, for the next question, you can just share a little bit for the audience, uh, about what Dream Data, uh, is and does. Uh, but the, um, and then answer uh, the question to maybe what the VCs asked you in, in that funding round as to what are you doing around AI. Uh, because as you said, like, started in 2018. So we call you like maybe native B2B software native, you know, B2B SaaS. Um, and there would need, whilst you've got AI within the platform, uh, I'm sure over the last couple of years there has been some, you know, into internal movement within the company and the product to, to become more like AI first, not necessarily AI native.

Speaker A: Uh, yeah, so, so look, we're, we're a B2B and that I should say B2B2B. We tell customers, if you don't have a CRM, we're probably not a good fit for you. Um, and so, so we do, um, attribution and activation. And that's effectively like marketing measurement. And then having the ability to say, okay, I've measured this and I know that this channel or this campaign or this ad is working very well. Um, this one is working very poorly. I can reallocate my budget to the one that's working well. And so our goal is to help marketers kind of, um, orchestrate their entire, um, uh, you know, all of their marketing budget in one place. So often I've been in Martech for 20 years. Um, I've run marketing teams, uh, though I grew up in sales. Um, and I think the, um, you know, the core thing that you see in martech, there are 18,000. This is this guy, Scott Brink, who writes about this. He's done the Martech map for years. And there's 18,000 different apps. Marketing is a very busy space. And what people typically have is you'll have an SEO person has their own platform, paid search, has their own platform, social media, uh, organic social media events, you know, like field marketing, all that. And they all live in silos. And so on average, our customers are connecting 12 different systems to us to figure out what's the actual ROI on each and trying to connect it to actual revenue. And that that can be also be the holy grail for marketing, trying to make sure, hey, what I'm doing in brand is working, what I'm doing in demand is working and it's helping support revenue for the company. Um, so that's effectively what we do. Um, to do that, well is difficult. Um, you know, I think I, we, we tell customers, look, the only thing worse than no attribution is bad attribution. Uh, and you know, because you're going to make very bad mistakes and people's jobs won't align, uh, for, for that type of stuff. And so we, we spent a ton of time on building a, a very effective data model. Um, and that's not just around data collection, that's tracking and that's also how you build the model and access the data to make sure that you're telling an accurate story to your team. So half of our, our product team are data scientists and we always nickel he's lead through data science teams. You got PhD in physics, smartest guy in Copenhagen I think, if not broader. But he, he um, is look, we deliver facts to our customers and ah, that's very important for marketers that you're delivering facts because you want to make sure you tell your CEO, your CRO or your board, hey, these are the numbers that we delivered and here's how I can prove out what that is. And so if you then like fast forward to your second part of the question in terms of well, what did you tell VCs about AI? And I will say that generative AI, like a non deterministic system, layering that over a complex data model is very dangerous. Um, AI is, you know, believes that it's incredibly smart, you know, and a lot of times it is, uh, but sometimes it's not and sometimes it's confidently wrong. And if you're not focusing on how a generative AI, let's just call it like an AI agent, can access that data, you get real problems. And so over the summer Salesforce published a study around their agents. Uh, and I was quite surprised that they did this. They uh, did it in conjunction with kind of a third party researcher. They said that their agents were failing 40 to 70% of the time. Now look, um, that is not software, that is a roulette table. Um, and that is not something that you want to put in the hands of someone that's trying to produce accurate numbers. And so very often genai and numbers are very difficult to mix together. They're getting better. And so there's a lot of work that you have to do to make sure that how agents are working with data is effective and it's not going to cost you your job. And so there's this idea, I'll go back to Scott, um, around a System of context. And what's happening is developing the system context, um, that allows agents to effectively utilize the data within your go to market. And that's, that's part of what we're doing. You know, we're of course working on, we have an agent now, we're working on several other agents. But, but I think the um, core thing when I went to market, uh, I always tell this, I don't know if it's funny but, but I think like no, I'm not, I don't know how to speak French. I might never actually because I used to work for a French company and they um, as soon as I joined the company our CEO Adrian said okay, we're all now speaking English because we have our first American on board. And uh, there went all the work I did on um, on learning French. But um, but so I'll never be a native French speaker but I can learn how to speak French. Right. And that's how I think about AI as well. Like you know, we're, we're never going to be able to say hey, we were a native AI company because we were founded in 2025. Um, that's something that you can't say truthfully to anybody, but you can certainly learn how to use AI in your organization. That's kind of the message that I would send to other SaaS founders is that you've really got to think about it that way. Uh, don't spend time thinking about man, I'm not AI native, I'm going to fail. Like that's just not accurate. You can learn how to use AI both in your product and maybe also more importantly across your organization.

Speaker B: Yeah, no, 100%. I mean I'm seeing this with um, uh, actually a well known SaaS company that I spoke to this week that their product um, uh, effectively enables you to build AI agents. Right. Visually. Um, and what I learned from the person that I spoke to is actually their role was uh, about making the company AI first internally in all the transformations of using uh, AI internally. So yes, as a B2B software company, to your point, um, look at the roadmap, if it's there now or you should be thinking about uh, how do we become uh, let's say AI first from one perspective from a product for our customers to use it, but internally, uh, as well. I think there seems to be obviously this requirement that uh, operationally companies need to be looking at how they can transform uh, by using AI. And we're, I don't know if we're behind the curve. Like, personally, we're, we're starting to use certain tools and AI sdr, you know, for instance, um, not yet seeing the results, uh, shall we say. But I think there's a lot of work that you've got to put into it and you know, train it and you know, the jury is still out, um, and just kind of looking at, you know, other elements, uh, sort of beyond that. But I feel like there's a lot of more work to do to kind of transform SAS do certainly internally to become AI first. Uh, uh, as such, whilst we're not offering, uh, you know, AI products to the, uh, uh, to the customer. Um, but, um, yeah, I guess kind of like internally within Dream Data, uh, like, how is the AI sort of like transformation, you know, what, what perhaps has been implemented that you're seeing, you know, that's working? Um, I guess, you know, there'll be different tools and uh, different things within different departments. But what are you seeing that's working and uh, producing results for the company?

Speaker A: Yeah, yeah, I think it depends on the department for sure. Um, we just went through our budget process with our board and approvals and everything, and um, one of the more interesting conversations was headcount on the engineering team. How many more do we need versus how much should we actually just, um, stock up on like AI tools? There, um, less of a conversation in terms of headcount on like go to market. Um, inherently on the. I think on the sales, especially on like a sales team and the customer success team. I, uh, think everyone's using it. Uh, you know, we. We work closely with, uh, with Gemini actually. And so our, our company both uses that as our core LLM and our product also uses that as our core LLM. Um, and I shouldn't say core. I said it is the one that we use. Uh, just to. Just to be clear, um, if anybody's listening, um, um. But I think that, um, on the sales side, I think you could see the typical use cases. Um, first off in our tech stack, like utilizing gong. That is probably one of the more common uses in terms of getting understanding of calls. How I review calls, I look at their AI summaries. Um, I see a lot of people using it for kind of email writing that I'm hesitant to do. I think for me personally, maybe I'm showing my age. Um, you know, there's a, um. There's a book, a very old book called how to Win Friends and Influence People. Um, maybe you're familiar with it. Dale Carnegie in that book. Ah, He. He talks about a letter that he received. And on the bottom right hand corner, there's this little note. It says, uh, dictated, not read. And what that means is that somebody feels very important because they were able to dictate to someone else what they wanted to say to you, and they didn't even bother to read it. Right. And so part of me feels like using AI in that respect. If you're trying to build a relationship with someone and they can tell that you use AI, it's like the new dictated, but not read. Um, and I'm cautious around that. You know, I think I like to build strong relationships with people. And, um, so I tend to use it sparingly. If I'm looking at myself personally for writing, I like to write those things myself. Um, but, uh, I know the sales team is using it for figuring out how to answer objections, things like that. We use, um, uh, a bot for questions on the product. Our system inherently has a ton of different features, and so we use that to answer questions quickly from both an internal support, um, point of view as well as we're utilizing it, uh, for. For external support.

Speaker B: If we go back to, um, when you mentioned that you've been in the CEO role for six, uh, months. Why. Why did you want to take the, uh, the job, leave CRO, go to CEO? You know, obviously, I imagine it's a, uh, a great opportunity and challenge. What, what have you learned? You, you know, over, uh, the last six months in, uh, in the role? Is it as expected?

Speaker A: I've learned a lot. I've learned that there's a lot more to learn. I think, you know, that's. That's probably what I would say. Um, as expected, that's a. That's a, um. I'm not sure if I had expectations. Uh, I think, um, that's. That's what I say. First off, I took. I took the role because, um, it was an amazing opportunity. Uh, Dream Data has built very. Something very special from a. From an internal culture point of view, from a product point of view, from how we help our customers. Um, I was. I joined because I tried to build something like Dream Data at two separate companies, and I fail. And I saw that they had built it, met the. Met the founders, and it was kind of, you know, the. The story was, look, we'd love you to come on as CRO, and if things go well, we can. We would make that move. Um, so I have an amazing relationship with, um, with Lars and Sethen, and the team overall has just been fantastic. So um, so that's kind of why I was excited to join. And um, I've always worked with marketers, so I was also very passionate about that. I felt like they weren't getting what they deserve. Both in the system, they needed sales. As a CRM, what does marketing have? But the promise of the CDP never really came through. So I was really passionate. I am really passionate about what we do and I'm passionate about our customers. Um, that's, I guess I should say dream data now. This switch from CRO to CEO might be more interesting. I, um, think that, um, uh, I didn't really know what to expect, to be honest. Um, we did kind of go immediately into, um, a discussion around fundraising. And so that became a big focus. And that was to me is just one aspect of the job, um, a very important one. I mean, there's a guy, Sam Vacos, maybe you know him, he runs Pavilion. He says know one job is to not run out of cash. And like. Yeah, that's, that's really true. And so if you're early stages in startup and you want to scale, like, you know, funding allows you to um, to do that. Um, so, so, so that was important to, to accomplish. And again, very, very lucky to um, to have gone through that. Found great partners in Peaks fan. I, I would say the thing that I've had to the, to get used to the most is the um, I would say ambiguity of relationships at this level of a company. Um, I come from both a military, uh, family. My father was in the army. I had cousins that were Marines, uh, and another so much of like military background, which means that I'm hardwired for hierarchy. Um, you know, and um, relationships, uh, are a bit more ambiguous at this level. Um, both in your relationship with the board, your relationship as being a kind of hired CEO, relationship with, with founders, you know, um, Lars. And again, I don't. I never. We work together as colleagues, I don't think. You know, I don't see him necessarily as like someone that, that reports me, but, but we're, we're close. Um, he technically is on my team. Um, he is a founder. So I have deference to him. I really think of this. Look, this is their company and I'm just trying to steward it to success for them and for the, um, for the customers. So he's a founder, he's on my team, he's on the board, which means that I report to him as well. And so it's a, um, it's kind of a unique situation that's something that I have to get used to personally and other people might be very used to that type of situation, but I wasn't. And I'm still um, making sure I navigate it effectively and do a good job on that front. So that's one thing that stands out to me in terms of getting used to the job and the differences. I would say the pressures. You know, CRO is generally, can be a high pressure job. You know, you've got a target on your back every quarter. It's similar as CEO. And I guess also I'm still, I'm technically CRO CEO. We're looking for um, a new hire right now, um, for that position. But um, I think the pressures might be a little bit higher, but I feel similar to running that role. Um, but of course I'm biased.

Speaker B: Are you changing your routine to look after uh, yourself anymore now that you're a CEO? Like are you going to bed earlier, getting up earlier, more gym sessions or whatever? Has anything changed from that perspective or is it still the same personal kind of like uh, uh, maintenance?

Speaker A: I think it's the same, that maybe I should say a little bit less. Honestly. I need to get back in the gym. Um, so, so I do need to do more work on that. Um, yeah, I guess it was, it was a long summer of um, fundraising. Um, but look, you know, my, my, my life and I know some people may disagree with this, but you know there, there are four things in my life. It's Leanne, it's Conlon, Jack, obviously my, my, my wife and two, two boys and dream data. And I'm totally comfortable with that. You know, I, I'm working in a place that, that kind of was my, my dream. This is a dream job for me, as lame as that may sound. You know, I was 14 thinking about how can I, because I'm 45. So when I was 14, 1994, and that is uh, when the Internet, I see lots of parallels to the Internet with AI. We can maybe talk about that. But um, it was such an exciting time for me and I was like, man, I would love to just start and run a software, uh, company. Um, and so I'm kind of living my dream and uh, it's passion for

Speaker B: me and with that journey from uh, the CRO role to now CEO. So you've been part of the scaling journey which is still continuing for Dream Data. Uh, uh, I guess, uh, so far from uh, the journey that you've been part of, maybe what have been some of like the non obvious challenges uh, for scaling, um, that dream Data has experienced. And any decisions from that uh, period that you would redo today?

Speaker A: No, you know, I think like AI was, is the biggest thing, uh, right now and navigating that, that switch, you know, it was hard to say, hey, we're found in 2018. Here's how we're tackling AI versus everyone. Looking at AI native, you know, um, though I will just say, like there's uh, what I, what I've heard a lot of is concern around the durability of revenue from AI native companies. You know, there's a ton of, um, innovation budgets out there. Um, if the innovation budget doesn't become a permanent budget line item, what happens to that revenue? You know, we still know. I mean, I think, um, I probably shouldn't call out specific examples, but there's some companies that were founded less than a year ago and they're doing 100, 200 million revenue and they that experience a real, um, uh, a real renewal cycle. And so there's, you know, there's a lot to learn once you get to 12 months and you say, hey, are these companies staying for more than a year? And so that needs to play out. Just getting back to that kind of, um, uh, the parallel of the, of the Internet era versus AI. This is certainly as big, if not bigger than the Internet. But there were bumps. You know, I remember going to college thinking this is going to be huge. And then like at year three of university, oh, everything tanked. You know, the end, you know, NASDAQ is tanked and am I going to have a job when I, when I graduate? Of course things turn around for the better for everybody, I think. And uh, maybe we're in that, maybe we're yet to hit that phase of this. You know, the promise. There's a huge promise that needs to be met. And um, you know, we think we can meet it. We think we can help AI meet that through the way that we've thought about giving, you know, access to data for AI agents.

Speaker B: Uh, finally, Nick, um, uh, thinking about sort of advice of founders and CEOs for the, the next 12 months as we, we enter into 2026. You know, what practical advice, um, you know, would you give for founders, uh, that are looking to build predictable revenue engines in, you know, across that period? Um, yeah, just kind of curious to uh, to hear.

Speaker A: Yeah, I mean, I think I'm, even though I'm in startups, I'm probably much more conservative, um, in terms of how I think about spending money. Um, you know, Even in the era of zirp, you know, when money was free, I still was some of those hesitant to, to spend a ton of money. Probably because my experience with what I was saying about the Internet era and looking for a job as that was kind of uh, a ah, wishy washy situation. Living through a financial crisis in 2008, 2009. Um, so I think that people need to focus on just building a good, profitable business, um, as opposed to thinking about how I hit insane growth numbers. It will come back to haunt you. Um, if you do that, do something sustainable. That's how I would think about it. Um, what else? I think what I said before about being SaaS versus AI native, keep that in mind. Like, you know, uh, you can successfully navigate that. Um, that's going to be the biggest topic of conversation when you talk to, um, talk to investors or when you're talking to customers even. But ultimately I do think there's a little bit of a problem right now and we're guilty. Don't uh, get me wrong, I think everyone's guilty is that you were talking very much about a feature versus the results. And that's like the number one thing that they tell you and go to market is like stop talking about features, start talking about how you're going to impact the business. And so if you, if you're going out and saying we're the AI native, accounts payable or accounts receivable or any other, you know, what's the value in that to the customer? Like what is it going to mean to the bottom line for your customer? Because there's really only a couple things you can do, especially in Martech. You either deliver more leads or you deliver cheaper leads. Uh, you know, and you can squibble with the name of um, we call it a lead. But, but you know, those are, those are effectively the two things that you can do. Everything comes back down to that. Um, and so just make sure you're, you're drawing a parallel to what you do to actual ROI. Ivan, I don't, I love CFOs. I've talked to more than I would refer to in my life in the last few years. And what that tells you is that everyone is scrutinizing any spend quite a lot. Um, and so you'll also need to justify yourself to finance departments. So make sure you're thinking about those hidden, um, stakeholders when you're thinking about um, how are you going to go to market, what are you going to say to customers?

Speaker B: Yeah, sage advice there. Uh, um, thank you for sharing both of those bits of advice. Uh, 100% agree. Um, Nick, uh, thank you, uh, for joining the uh, SaaS Revolution Show. Um, hopefully we'll get you back at ah, a SaaS stock. Before we started recording, I think you shared, uh, you've been to SaaS doc in Dublin in 2019. So, um, when we're now in Austin, that'll be in April, probably a little bit easier for you to travel to. But also the Dublin event is uh, still a great show, so hopefully we can make that happen in uh, 2026 and uh, uh, see each other in person. Um, but thanks for being a great guest on the show. Really appreciate it. Nick Turner, CEO of Dream Data.

Speaker A: Thanks Alec. And I gotta say congrats on 10 years. It's awesome. Um, keep it going.

Speaker B: Thanks man. Planning on another 10. Um, another 10. Thanks for listening to the SaaS Revolution Show. If you enjoyed this episode, please leave a review and follow the show. It helps more AI and B2B software founders to discover the podcast and keeps us bringing you the leaders who are shaping the future of the industry. For more resources and to join the SAASDOC community, head to sasdoc.com.