Speaker 1Hey everybody, it's Sam Jacobs. Welcome to a special episode of Topline Spotlight. Topline Spotlight is a small segment of the Topline podcast released on Thursdays, and each episode features a one-on-one interview between a guest and one of our hosts. This time, it's me. And our focus is on understanding a business problem that one of our guests has solved over the last 12 to 24 months. We like to bring in high-profile GTM leaders, CEOs, founders, and investors, and today we're lucky to have on the show Nick Turner. Nick's been in commercial leadership in the MarTech space for nearly 20 years, helping to scale software companies from seed and Series A up to $75 million in revenue, and he recently took on the CEO role at DreamData, where they just raised a $55 million Series B to help marketers own their GTM. You know DreamData because we've been talking about them. They've been a sponsor on the show for the last couple of months, and we're huge fans. So, Nick, it's great to have you on Topline Spotlight. Welcome to the show. Thanks, Sam. Thanks for having me. I appreciate it. We're excited to have you. So, we want to dive into a business problem or challenge that you've solved over the last one to two years, but before we do that, we do want to focus on your baseball card and figure out exactly who you are. So, you are the CEO, but you actually joined DreamData. As the chief revenue officer, if I'm not mistaken, for those that aren't familiar, what is DreamData? Give us a little bit of background on what the company is and does.
Speaker 2Yeah, yeah, for sure. So, DreamData founded it in 2018. A couple of guys out of Trustpilot, if you're familiar with Trustpilot, they had the problem of figuring out, hey, where are we actually producing our leads, you know, marketing measurement, marketing attribution, specifically for B2B. And so, if you know Trustpilot, they had a really great kind of, you know, PLG motion. They had outbound, they had inbound. They tried to figure out what was working. And so, that's what we do. We help marketers, specifically B2B marketers, understand, you know, what's working and what's not working, take on the reporting of that, and actually take action against it. So, it's one thing to measure what's working and what's not. It's another to be able to take, you know, great action against it. So, that's what we do.
Speaker 1How old is the company? Where is it based? Tell us a little bit about the Ordwin story.
Speaker 2We're seven years old now, and I joined almost two years ago, like you said, as CEO. We are with the intention of making the jump to CEO if everything had gone well. So, it's actually a Danish company. I was the first U.S. hire. We're based in Copenhagen. We've got about 50 people right now, and we've got about 15 in U.S. So, obviously, U.S. is a big growth market for us. So, we've scaled the team up pretty quickly, and we'll probably, you know, double the size of the team in the U.S. over the next 12 months as well.
Speaker 1Oh, wow. That's incredible. And so, the space is kind of, you know, how would you characterize the category that you
Speaker 2operate in? Yeah, marketing measurements, attribution and activation, you know, that's our space.
Speaker 1Cool. Awesome. And, you know, before we dive into the business challenge, which you may cover, but talk us through the journey of becoming a CEO. You know, I think this is your first time as a CEO, if I'm not mistaken. So, how to walk us through that evolution? Because it's inspiring for all the GTM operators out there that are listening, knowing that they can make the leap to the big job one day.
Speaker 2Yeah. No, I would say it was, everyone says it's humbling. It is humbling. You know, and I think I had done go-to-market for nearly 20 years, as you mentioned, and I really wanted the opportunity to learn more about the rest of the way the business is run. And so, I was, you know, I obviously had strengths. You know, I grew up in San Francisco. So, I had a lot of strength from sales. I had had marketing under my belt before. So, I had some strengths there. Post-sales, of course, I think every CRO typically, at a minimum, you're owning sales and post-sales if you've got a CRO title. But then kind of making the jump, I think, a lot to learn. You know, I'm still only six months in. Well, now, actually, now I'm almost nine. It's going quick, I guess. And at the same time, you know, as soon as I took the role, I was like, I'm going to be a CRO. I'm going to be a CRO. and I think when I joined, we were 50 people. We will have grown revenue by 3X, and we're still 50 people. And so I think getting our burn multiple down, things like that, were really important to us. So we focused on those metrics. We focused on retention, and that also informed kind of who you're going to end up with because I didn't want to end up with an investor that said, hey, in 2026, we need to see 5X growth. I was like, well, we just did 2.5X. When you get bigger, it's not going to accelerate. It doesn't usually. We actually did accelerate our growth some, but you're not going to say, okay, we're growing at 2.5X at $10 million or whatever, and now we're going to grow 5X. That's never going to happen. And so I think we wanted a partner that had good realistic expectations as to what our growth would be. So all of those things were super interesting to go through, and again, I will say I was just fortunate to have a great board, to have a great team, so you got me through that, given it was my first time.
Speaker 1Yeah. Well, congratulations, and Peaks Band is a great firm, and really in the same vein as my investor, Elephant Ventures. You know, Elephant, Radian, Peaks Band, they're all kind of like quasi-venture, quasi-growth equity, but focused on investing in profitable businesses that are growing quickly, which is great. Yeah. The premise of Spotlight is a business challenge that you've tackled over the last one to two years, and certainly to your point about, you know, meeting with investors, I think AI is top of the heap, right, for all of us. So walk us through, what was the challenge that you specifically navigated in the shift to AI for Dream Data, how you accomplished it, what you encountered, and sort of what happened as a consequence?
Speaker 2Yeah. Yeah, I would say we're in the middle of it. I don't know that. I don't know. I don't know that I've accomplished it, but I would say that how, you know, we're making good progress towards it, and we're proud of what we're doing. You know, our business is around measurement and attribution, which means complex data models, complex numbers. And, you know, the fact is there's still, when we look at that and we think about putting that in front of our customers, we want to make sure that, you know, the CMO or VP of marketing or demand generation person, they're going to take our numbers, they're going to give them to the board or to the C-suite and say, okay, this is how. We're performing and we need to make sure that they're credible. And so we approach that very carefully to make sure that if we're going to insert AI and have it run around on top of our data model, it's going to make our customers look good, at least look accurate, you know, give them good, accurate data that they can make decisions on. And so I've seen teams wiped out utilizing a generative AI on top of these complex models completely because they made mistakes by just trusting what the. Uh, the, the, the bot was saying. So, so we've been very careful about how we approach that. Um, and, uh, you know, we're, we're working on releasing a few new items in the, in the coming year, in the upcoming new year, I should say. Um, that's very exciting. And we think we've solved a lot of the problems around, you know, there's really two things that we think about. There's obviously the hallucination side, lots of, lots of, uh, progress made on that front from the large language models and, and in our products as well. Um, but then there's also the problem. With people that don't, that aren't educated well enough to prompt properly. And so how do you make sure that you don't give the, the right answer to the wrong question? Does that make sense? Yeah. Somebody asks a question, expecting an answer and they, they get a right answer, but they get the right answer to a different question. And so those are the two things that I think you have to be very careful with. If you have a product, um, that is focused heavily on, you know, large, large amounts of data, numbers, calculations, make sure that you're actually, um, uh, you're giving accurate answers to your, to your customers, because like I was saying before, uh, at the end of the day, and we're, we are, um, not victims. We are, um, we've done, we've done this as well. You know, everyone is putting AI in front of the name of their product right now. And, you know, that's just not a good, um, good idea for, for marketing. You're not selling the benefit, you know, you're just saying AI accounting or AI. You know, marketing attribution to actually provide value to the customer. And the way that we do that is that we brought accurate information and data to them when they're trying to make decisions on where they should spend their marketing dollars.
Speaker 1Yeah. I think to your point about prompting, I think that's part of the trough of disillusionment potentially, which is, I think the premise of gen AI, we were talking to Kyle Poyar on our main show, uh, recently, and he was saying, you know, this interface. I think it's pretty novel when it comes to technology, because I mean, I think that's the role of product, right? The role of product is, is not to leave an, a blank canvas up to your user and say, ask it anything, but to say, I'm leveraging the technology in ways that you may not even see, but these are the ways that you use the product and click this button to do it.
Speaker 2Yep. Yeah. Yeah. That's, that's exactly right. Um, and so I think that, you know, there needs to be more educational upfront still, uh, and how people. Know how to use the, use that as a, as a product.
Speaker 1So what, what do you, so, so the, the product enhancements are really like layering in gen AI to provide, to make it natural language based, but still make sure that you're, you're deploying and providing the right information and accuracy, and then also probably using templates and coaching to make sure that the user gets the right answer to the right question, as opposed to the right answer to the wrong question. Is that accurate?
Speaker 2That's correct. Yeah. And. You know, Salesforce, um, I don't know if they published a study, but there was a study done over the summer on, on agent force where they were saying that agents were failing like 40 to 70% of the time. And that is not a place where we can be. Um, and I think that is, you know, that's a roulette table. It's not software. And so you have to make sure that you're actually, you know, it works, works well, but the way that we, um, effectively people want to be able to chat with their data and get correct answers. Um, the problem is that on the, the other hand, uh, other side of that. Is, you know, they answer confidently, like there's, there's no like gray area. It's like, this is the right answer. Um, you know, we name all these things, uh, like we have a lot of bots, like female names, they should be male names. Cause they just send a mansplain and, and just think they're correct every single time. And so we have to think about how we're naming these, uh, these bots, uh, in that, in that regard, but yeah, you know, but seriously, I think, um, you know, you do have to think about, you know, you have to make sure that, uh, when somebody comes into your product, especially our product, that we are giving accurate answers. And so, you know, that, that involves, uh, you know, I, like I said, product is my weak spot. So I'm not gonna try to explain the intricate details of it, but it involves a semantic layer to make sure that the, um, uh, the agent.
Speaker 1Private question and stop it before it provides a numerical response, maybe structured into a query into the database that gives you actual response. Exactly. Right. Like that.
Speaker 2And then the, the other side of that. To make sure that someone that doesn't know how to prompt under understands, um, what they're getting. Yeah. You take the SQL statement that you're using to query the database, and then you show it to them in a format that they can understand, because I cannot, I mean, 20, 12 years ago, I did learn how to, to use SQL. I couldn't do it now. And so you put it in a format to where somebody can look at it and say, okay, this is, um, this is what I was asking for. And this answer makes sense to me. Um, so it, it can't just be a black box of, uh, Hey, here's a text. Question. Here's a text answer. You need to know where that, how it actually came up with the answer and then present it in a way that's attractive to you or to your stakeholders.
Speaker 1That makes sense. What's, uh, tell me about your outlook for 2026. What are you most excited about and, and, and how is dream data approaching the new year? Because to your point, you know, maybe we're past the peak of AI hype. You probably, you know, you need AI in your product because you need the same way you need, you know, other basic web applications, uh, in your product. But how are you thinking about differentiation as you, as you look ahead to, you know, whether it's three X, four X, two X, whatever the growth rate is looking to continue to grow profitably into next year.
Speaker 2Yeah. I think I'm definitely excited about our product development. That's the, that's the number one thing that we've, we've focused on. Um, you know, we've been, just been watching the market and seeing how people have developed till now and just been patient. Cause one of the other things that you have to have to realize is that everyone is working on building their own agent. Um, but. Uh, Google, uh, open AI, all of the major, you know, LMS are trying to make it really easy for you to build an agent. So you can spend a ton of resources just doing all of that work yourself, or you can be patient and wait for them to make it a lot easier for you. Um, you know, they're spending billions in dollars that we don't have. I mean, look, 55 million is a ton of money, but it is not 4 billion or $8 billion to do this. And so there are companies working incredibly fast on trying to get that, that regulation. for the market in general. And, you know, we'll focus on the application layer versus any infrastructure or kind of platform play. Do you think large enterprises,
Speaker 1they're going to, are going to build their own agents? You know, you think that, I don't know, some big Honeywell or Martian McLennan are going to like spend a lot of time developing their own internal software agents? Or do you think it's still going to be the way that it's been for, you know, the last 40 or 50 years, which is they're going to use companies like Dream Data for specific product use cases because you have technology goal and domain expertise and you've built the product to interact with the end user what do
Speaker 2you think i do think it can be a little bit of a nightmare if you have a company like honeywell i don't know 10 000 15 000 employees each one of them each one of those employees might be able to develop their own agent that they use independently is it getting the same answer as their colleague are they are they getting the right information and just from a business standpoint let's set aside ai um and just think about innovation and and business in general i think it's important that people focus on their core competencies um and they're efficient in that on that front so i do i think um there is a lot of talk about everyone's just going to build their own agent or their own software maybe some of that happens but um you know we've been talking about low code no code for years and and that hasn't really taken off in large enterprises they still go to external people that have a core competency to build this stuff so i do think a little bit of that comes back to just you know general best practices of this is our core competency we do x this other company can do y much cheaper much better than we can and that will drive it i agree with you you could
Speaker 1probably tell by the way i was asking that question but yeah exactly uh we're this is a short show we're almost at the end of our time together nick if if you wanted to pay it forward a little bit uh thinking about books podcasts people investors things that have had a big impact on you that you think we should know about uh give us give us some
Speaker 2inspiration yeah i have a non-standard one um and i actually uh talked to kevin dorsey about it recently he mentioned that he had read it and i was so surprised because i'd never met anybody else in tech that had read this book it's called the uh the e-myth uh if you're familiar with it it's from like late 80s early 90s um i would recommend it it's how i thought about building process and operationalizing a company the premise is so it's the the it's just called the e-myth there's those multiple um uh multiple uh versions of it um but the idea is if your professional services say like a lawyer a doctor dentist anything like that um you have to decide do you want to work on your business or do you want to work in your business and it talks about effectively kind of building out a franchise you know how do you systemize your business um in a way that you can step back from it and just work on building the business as opposed to being inside of it uh so i really like that book i read it uh once by the time i owned a construction company that's another day um and i read it to help build that and i use the same principles from the e-myth to um work on um you know how do i build process at a tech company i'm
Speaker 1on amazon right now and it looks it's trying to sell me the e-myth revisited but i can't find the original maybe i just got to
Speaker 2there's probably not a whole lot difference to be honest you know they added a couple pages or added a preface by somebody that was more recognizable now as opposed to in 1990 um but no i i really like that book i would i'll just call that out as one because i hate giving lists because people don't know where to focus um but you know that that is one i think is pretty unique and if you're newer in the space i mean like maybe i'm dating myself now but but crossing the chasm is just always a great um i think it's a great book and i think it's a great book and i think it's a great reference as well yeah it's a great one it's it's for go-to-market folks i think understanding crossing the chasm is uh is really important
Speaker 1agreed nick if uh if folks want to learn more about dream data maybe they're having attribution issues maybe they need accuracy they don't need the 70 of failing agents sold to them by mark benioff what's the best way to get in touch with you what's the best way to inquire more learn more about how people can get more insights on how they're spending ad dollars so that they can drive better
Speaker 2performance yeah so i'll be sure website dream data to io um i like to talk to marketers one-on-one i set aside two hours a day to do that um if you find me on linkedin i've got a calendar link on my profile book time there we'll chat one-on-one i um you know i really like doing that so feel free to do that or if you if you want and i won't sell you if you go to dream data to io and you do a demo request the sales team will sell you and uh just so you know that that will happen great
Speaker 1uh nick thanks so much for being our guest today our guest on the show uh congrats on the on the promotion of ceo congrats on the fundraise on being a great pavilion member which we appreciate and your support of the show and we're excited for an incredible 2026 for dream
Speaker 2data great thanks sam
Speaker 1thank you okay and against all odds you're still
Speaker 3here look if you want more top line check out the top line newsletter at topline.com topline.beehive.com beehive is spelled weird it is b-e-e-h-i-i-v.com topline.beehive.com or if you're a video person because video is great check us out on youtube top line dash media is what you want have a delightful day everybody Transcription by ESO. Translation by —
PodcastTranscript AI