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Demystifying the conversations we're already here at RRE and with our portfolio companies. In each episode, your hosts, Will Porteous and Raju Rishi will dive deeply into topics that are shaping the future, from satellite technology to digital health, to venture investing, and much more.
Raju: Hello listeners and viewers. Welcome to another episode of RRE POV. I’m General Partner Raju Rishi at RRE, and today I’m joined by Dan Rosenberg, currently founder and CEO of Octane11, which is an RRE portfolio company. He’s also a multi-time startup guy and a very good friend.
So, let me just start by saying that although we’ve done many, many prior podcasts, this is our first, inaugural video podcast. And I’m happy to have Dan on here because he’s a very good looking guy. I had to prepare differently. Wore a shirt and pants and, you know, kind of had to fix up the background, and strangely, I put on cologne today, you know? Just because that’s my, like, when I’m prepping, that’s what I do. You know, obviously don’t need to do that, but—
Dan: You smell good from here.
Raju: All right, thank you. Thank you. It’s good to know. I’m going to start with Dan’s bio, which is really deep, but I think it’s important to frame, kind of, what he’s done in the past, and then we’ll talk about our relationship and how we got to know each other a bit. Background wise, he’s a longtime New Yorker, you know, started at Horace Mann, Harvard, Harvard Business School guy, did a stint at Maveron as a venture capitalist, a brief stint at Virgin Mobile, which was one of the earliest MVNOs out there, actually pretty successful.
Then he joined me at Rave Wireless, which I have a lot of great stories about, did a brief stint at a hedge fund, and a long stint at MediaMath, where I think you had practically every role in the business, including corp dev, business dev, business development, you were a GM, Chief Strategy Officer, Chief Marketing Officer, and now finally, founder and CEO of Octane11. Because I know Dan so well, we’re going to start with a few stories, [laugh] which may or may not be embarrassing. Actually it will always be embarrassing to some extent. Yeah, you remember the first day we met?
Dan: I remember it. Down in Chelsea, Manhattan.
Raju: We had started—this was my third startup, Rave Wireless, and we had maybe, like, six or seven people in the business. And I was interviewing for the head of business development. So, just for people’s context, Rave Wireless was a startup that was providing applications to universities, mobile applications to universities in higher ed. Not only did we provide the applications, but we also provided, in many cases, the telephones. And so, we were an MVNO, and Dan’s experience with Virgin Mobile was very relevant.
But, you know, kind of a hot startup in New York, and I was interviewing a number of people that day, and in shows this guy—in shows up, Dan Rosenberg, he’s in a tie, well dressed, comes in, and our office in Chelsea was, it was an apartment, actually, and we had eventually shoved, like, 25 or 30 people into that thing. I don’t know how we fit it, but we were really, really scrappy. And we had, like, a two-bedroom thing, and one of the bedrooms, we did the interviewing. So, I had him come into one of the bedrooms, and I asked him a bunch of questions about, you know, the business. And the guy was super prepared, like, had read everything about the company, you know, had sort of memorized, sort of the value proposition, how we were going to market, which our customers were.
And I said to him, you know, “Look, I’m not sure. Like, I think that you’re, like, obviously well prepared, incredibly well groomed, and probably would be good for”—but, like, you get a lot of people being interviewed. And we had just assembled at the office. And what I mean by assembled is we bought a bunch of stuff from Ikea, and we put together maybe, like, half a dozen desks and a couple of bookshelves. And there was a big pile of, like, IKEA boxes piled up next to the front door.
And you know, who knows what was in it. Mostly box material, but could have been like boards and nails. And while we were walking out, I said—and it wasn’t anything like, sort of, intentional or planned—I just said to Dan, “Man, it looks like a big pile of leaves. It would be kind of cool to, like, kind of jump into it like we did as a kid.” And this guy did not even hesitate. It wasn’t even, like, a fraction of a second, just like, turned toward the pile and just dove in. And I was like, I got my guy [laugh]. That was a hell of a story. Like, I just can’t believe you just kind of dove into that thing. That was, like, a miraculous, like, you know, spontaneous exercise.
Dan: You got to go for it, you know?
Raju: Yeah.
Dan: I don’t think I told you this before, but that’s part of our interview process at Octane11 [crosstalk 00:04:47] dive into—it doesn’t have to be a box. It just has to dive into something, anything. Something crazy.
Raju: That was remarkable. It was really spectacular, actually. I was like, I didn’t expect it, and I just basically looked at Dan and said, “You got the job, man. That’s, like, crazy.” I will tell you, like, one of the things about startups that’s really, really important is, your first handful of hires outside your founding team sets your culture, and this guy was the epitome of a person you wanted on the team, just, like, had a startup founder mentality and willing to do anything. I think you basically had every job at Rave at one point because every time we had a gap, “Dan, you got to be the head of hiring,” and he just took it on and did that as well.
Dan: I appreciate those [unintelligible 00:05:34]. I mean those, like, early hires are just so, you know, so critical, you know, the early team has to be just willing, just to do whatever it takes. I’ve found that through all the startups I’ve done since then.
Raju: And it’s a culture thing, right? Because what’s going to happen is you’re going to bring in five to ten more people soon, and you can’t be the one sort of indoctrinating them with the culture of the company; it’s got to be some of the early employees as well. So, if you get the wrong people, it really goes sideways. I have another story.
We are negotiating deals at Rave Wireless. So, Rave Wireless, I mentioned, once again, offering solutions to universities, mobile solutions. Those solutions are pre-iPhone, actually, and so there weren’t a lot of devices that could handle, you know, a complex application. And so, sometimes we had to, you know, when people rolled into the university, we had to give them phones. Part of that is you create a university phone.
And we had, like, a Montclair University phone, and we had a University of Florida phone, a bunch of different ones out there, and we would have to negotiate deals with officers at Nextel and Sprint. We coined this term—I don’t know if we coined it—but it was like ‘the designated drinker.’ And Dan was my designated drinker. We would go into these contract meetings over dinner—I think the statute of limitations has passed—
Dan: [laugh]. I think so.
Raju: Many, many years ago, but we would order, like, a round of rum and Cokes because that was Dan’s favorite drink, just FYI. And we would get three of them. It would be one with the officer from the carrier, Dan and I would get one. And when the guy across the table wasn’t looking, Dan would swap his finished drink with my full drink. And would take two for one with the executive, and I would have zero. And at the end of the day, we would roll out with a contract that worked very favorably for us [laugh].
Dan: You got to protect the boss, you know? You got to project Raju, you got to do those negotiations. I actually learned that in China. Because before I was at Rave, I worked in private equity in China, and we’d be going around to, like, factories that we are investing in. There’s a company called ASIMCO, which is a private equity firm out there—one of the first actually—and we’d be out at factories, meeting with teams, and we’re talking about making big investments, and we’d be having dinner, there was lots of, like, [gumbe 00:08:06], like, drinking, and then all sudden, you’d look up and the people that, like, the management team of the factory wasn’t there anymore, but like, the biggest guys ever were like, around the table. They, like, swapped in, like, you know, a body man to, like, be the heavy drinkers against you. And that, like, was a big part of the—again, that was my job, for some reason, was to, you know, go toe to toe.
Raju: Well, you kind of fall into what you’re good at, which you were very good at [laugh] that role, a very, very sober drinker, which was amazing. But that actually reminds me of another story. We’re in New York, subways are down. We’ve just gotten done with a business meeting, and the subways are down, and we’re, like, we have to get back to the office for a critical meeting. So, Dan’s going to—“I’m a hellcat.”
And he winds up hailing down this cab. And we hop in, and this very attractive Asian woman knocks on the door and says, “I’m really late, you know, are you going uptown?” We’re like, “Yeah.” And she’s like, “Can I just share the cab with you?” And she jumps in the cab, and I’m like, “Okay.” So, you know, it’s no big deal. We’re, like, all three of us going the same way.
And she’s open. She mentions a couple things. She mentions she’s Mongolian, and Dan breaks out in fluent Mongolian to her. And I’m like, what the hell is going on? This is the guy. This is a guy. Jack of all trades. But that was amazing.
Dan: You got to be prepared. Yep.
Raju: Yeah, you got to be prepared. Anyway. I could talk all day about these experiences that we’ve had together. In fact, I will actually jump in, you know, as we talk about additional moments that we’ve had together, but I’ll tell you, that crowd that we had at Rave was pretty spectacular. That was an unbelievable company.
The roster, I’m sure you remember, like, Tricia Han of MyFitnessPal and currently CEO of Mistplay; we had Kai Bond, who’s a Courtside ventures partner; Obviously, you’ve done multiple startups; Andrew Feigenson, InformData; Ted Sullivan, GameChanger; Nobu Nakaguchi who did Zola; and Rodger Desai of Prove. That whole crowd went on to do multiple, multiple, multiple founding teams. Anyway, that was fun days. Okay, let’s go to, sort of, the core of the lessons that people want to learn. One core lesson you got to learn is, like, if you can ever work with Dan, do it [laugh]. That’s a lesson here for listeners.
Dan: That’s good because we’re hiring right now. So, uh…
Raju: I love it. I love it.
Dan: [crosstalk 00:10:32] appreciate that.
Raju: Do not hesitate. I’m not even kidding. You will learn a ton from this guy, and he’s just, like, got a litany of experiences, but he’ll surprise you every day with things that have gone on. Okay, let’s just jump forward. I know you’ve done a bunch at Virgin Mobile and Maveron and others, but let’s move to MediaMath because I think it’s the most relevant to where you are today at Octane11.
And I know you did a whole bunch of things there, from business development to CMO to Chief Strategy Officer, and you mastered sort of marketing and ad tech there, but the company had, you know, sort of an astronomic rise. I don’t say meteoric. Meteors crash. I don’t know why people say meteoric rise. It seems like an oxymoron. But anyway, an atmospheric rise, let’s just say that way.
Then it had, you know, some decay. And so, I’m sure you were there through a lot of that, and would love to hear, kind of, some of your lessons. Let’s start with a couple of the positive lessons, like, what MediaMath did really well that, you know, you kind of absorbed, and you know, are putting in your toolkit for this startup and other things that you do in life.
Dan: Yeah, I mean, MediaMath was an incredible experience. It was early in a big expansion in programmatic advertising. And Joe Zawadzki was a founder, and he, kind of, saw that happening and around, like, 2008 and said, “Okay, there’s a couple of trends converging here, so we better—you know, here’s a big opportunity for the buy side, optimizing, the buy side of advertising.” And I think the first thing was, like, just assembled an incredible team. It was a lot, like, you know, what we talked about at Rave. Like, the people that we brought in were just incredible, just super committed, wanted to go the extra mile, like, really cared.
We didn’t have, like, a churn-and-burn mentality. It was like, we’re really trying to solve, like, real problems. And a lot of the thesis for MediaMath also was about, like, getting to the truth and, like, transparency, real business outcomes. And it wasn’t about, like, let’s make a fast buck. And that was like, creating the culture where, like, we really kind of went the extra mile for customers, and that was huge. That was, kind of like, the blueprint.
And we went—when I was there, I was maybe, like, 60, employee number 60, something like that, and we grew to about 750 people. And we did, like, the triple, triple, double, double, double that you talk about for, like, you know, top tier SaaS companies. But it really started with, like, the blueprint of the people in those early days. So, that was a great one. I would say, maybe one other lesson learned from the MediaMath—and believe me, I have a lot on, like, the positives and the what could you do better—but super partner focused. So, it was really about, like, an ecosystem play. And that was actually part of my job was managing the ecosystem and setting up, like, win-wins with partners. And we had 500 partner integrations. [crosstalk 00:13:31]
Raju: That is crazy.
Dan: Yeah.
Raju: 500 integrations back in that day?
Dan: Yeah.
Raju: Back in that era of just, like, unbelievably complicated ecosystem that you had to sort of juggle and create value from. And people wanted to work with MediaMath. I mean, it was just like the company to work with. That is pretty astronomical. It’s kind of like, you know, you reflect upon it, and it was one of the, you know, sort of cornerstones of how middleware got created, you know? Before middleware was middleware, right? It was pretty, pretty intense.
Dan: Yeah. We can talk about this more, but like, being that, like, translation layer, that middle layer that has, like, that has the data across all different partners, all different clients, and is learning as you go. So, it’s not just, like, a pipe connecting A to B, like, there’s real intelligence in there. Like, that’s a really interesting business model.
Raju: Absolutely. And then just, like, it got to this pinnacle, and then it just didn’t get escape velocity, you know? Just maybe one or two lessons—and if you don’t want to share, that’s fine—but like, love to sort of understand kind of what could have been done a little bit differently, or how they would have—you know, some of the factors that—or one of the one or two of the factors that affected that.
Dan: Maybe the biggest thing was, while we were trying to do so much problem solving and helping clients, like, on the edge, we were maybe trying to do too many things for too many different client types. So, there’s something, really, to be said for, like, super focus, like, really nail your ICP. Like, as hard as it is, like, sometimes you got to say no to certain customer types or certain projects, you know, if there’s revenue behind it. Like, a comparable for MediaMath was The Trade Desk. And it looked very similar on paper, you know, seemed like basically the same company, same business plan, and to be honest, like, in the early days of my corporate dev role at MediaMath, we were raising capital, like, they weren’t in our competitive set when we were talking to VCs. It wasn’t even on the list.
Raju: Wow.
Dan: And The Trade Desk kind of just came, like, year after year, growing really fast. And they just had, like, a great focus on, like, one particular customer type. It was in the name of the company: the trade desk, which was like a tool for agencies. It was a category of tools for agencies. So, they really focused on that customer. And that helps you with how you design your sales, but also, like, your product and the features and, you know, so they just did a really nice job on that.
Raju: I love that. I love that. It is actually, like, one of my mantras that I share with all entrepreneurs. Like, more startups will die from indigestion than starvation.
Dan: Mm-hm.
Raju: And you know what you just described with MediaMath, which is, like, you know, amazing, like, focus on the customer, and you know, desire to be, you know, helpful to them and building that ecosystem, but maybe taking on too many things. Like, and that’s an indigestion problem. Like, if you try to do many, many things concurrently, you’ll likely do all of them, mediocrely or poorly, and you know, you won’t have this, like, winning value proposition. The second thing I say is, like, there’s a corollary, which is the greatest startups in the world have the greatest sequencing. So, after you nail that first value proposition, now you have the opportunity to broaden to the second and then the third and then the fourth.
And knowing that sequence, and kind of thinking through that sequence is super, super important because you don’t want to pick something that should be the fourth step as your second step. It’s really kind of like concentric circles, like, just going to that next concentric circle, or, you know, what I call, like, trying to cross the river on a bunch—you know, without getting wet, and there’s a bunch of stones. And so, you can jump from stone to stone to stone, but if you don’t see the pathway all the way to the other side, you might jump on a stone where you have to go backwards because it doesn’t have an adjacent stone to get you over. And so, I love those lessons. Those are important, and I’m glad you shared that. I appreciate that. Let’s jump to Octane11, where I [want to spend most 00:17:39] of this time.
Dan: It’s an AI platform for optimizing B2B marketing. So, what we found at MediaMath, so we were managing about a billion dollars of digital marketing spend, and in the industry, about 20% of marketing is B2B. MediaMath’s footprint, it was way, way smaller, but we had big clients like IBM and Dell and Aetna and AmEx that had a B2B use case like selling to big businesses. And so, we got to really know that and see the pain points of it in that category, and that’s kind of where we started to think about a solution for it. But the big problem in B2B is that it’s not like in B2C, you can click on an ad and then go buy something, or you hear an ad and you hear, like, you know, use this code to get a discount, and then you can understand exactly which of your marketing is working and close the loop.
In B2B, nobody clicks on an ad and buys, like, an IBM installation. Like, [crosstalk 00:18:42] right? I mean, it’s a long sales cycle, there’s a whole committee of buyers who need to make a decision over a long period of time and get buy-in, not just from the end-user, but like, from the finance team and from the procurement team. They all need to know about your product, and so you need to reach out. And what’s really hard in advertising and even digital marketing is that that’s all anonymous. The ads are going out into the world.
Like, people like to advertise on Facebook or Meta, and it’s a great platform, but it knows all about, like, your demographics, but doesn’t know anything about, like, your job or you know your title, your seniority and all that. So, like, we saw that problem by mapping all the engagements across all these platforms like Reddit and Meta and CTV, and we mapped that all the actual companies. And once that’s connected to the companies—
Raju: Can you just do me a favor and describe the—I know it’s account-based marketing, but, like, that is, like, the focal point of the type of buyer you’re trying to sell to. Can you describe what account-based marketing is a little bit further so that people understand it?
Dan: Sure, yeah, I mean, account-based marketing is a term, and this means, like, marketing to accounts. It’s a term that’s become really popular, but a little bit misunderstood. Some people think of ABM means, like, oh, I’m just going to try to follow like, this one person with this one title at this kind of company, or maybe a couple of companies, but like, you know, in our view, like, B2B marketing, you’re selling only to companies, so everything should be account or company-based marketing. The way the typical marketing works in B2B is, okay, what’s our ICP, our Ideal Customer Profile? What are those companies, maybe it’s 1000, maybe it’s 100,000, and then we want to develop a message for those companies that moves the needle based on, like, what we know about what their pain point is for that ICP.
And then we want to find those people wherever they are, whether it’s in podcasts or CTV or they’re on Reddit or they’re on LinkedIn, like, wherever they are with that same message, then you need—and that’s, like, people understand that challenge and that, you know, that strategy, but then the last piece, which has been really hard and is kind of a big gap and a big white space that we’re solving, is then tracking all that activity at the account level across all those different channels and matching it back to those companies so I know which companies I reached and engaged, and then attaching that to sales data, actual business outcomes that’s tracked in Salesforce or HubSpot or Microsoft Dynamics. But all together, and what’s interesting about it is, like, it’s amazing for just one company to have that data, but if you’re a service provider, like, an agency that works with multiple companies, imagine having that data across your whole portfolio companies. And as a platform business, imagine having that data across hundreds or thousands of companies.
Raju: So, you can tell—let’s just focus on a particular company for a second—but you can tell a company, based on all their marketing activity to, let’s say I’m IBM, and I’m selling to, you know, I don’t know Merck, and I want to basically—I’m advertising across lots of mediums. You can tell IBM the effectiveness of their marketing ca—of each of their marketing campaigns to that specific customer or across their entire ICP, and you can tell them which ones they should spend more on and which ones they should spend less on. Is that correct?
Dan: Yeah, absolutely. I mean, the real kind of unlock is taking the what—they call it in the industry, pseudonymous means, like, it’s anonymous, but there is some kind of identifier on marketing activity, and then you match that to the company. So, it’s actually knowable what company people work at, even if I don’t know it’s Raju, like, I can know that it’s someone who works at RRE or in the venture capital industry, I can actually map that back, and then across everybody at the company. So, I get all that activity with all those people at that company. And so, I know that, one, have I reached them? Like, has the marketing I paid for actually reached those users? Like, you got to have that as a yes. And then, did they engage? Did they click? Did they like? Did they share? Did they comment? Did they scroll? Did they finish the video? All those kind of indicators that they are engaged.
Raju: That’s a lot of details, that’s tremendous. And so, what integrations do you have that give you all of this insight? I mean, obviously you have to have a ton sort of, like MediaMath, right, because you have to be able to ingest all of the different marketing channels that I’m leveraging.
Dan: Yeah. There’s about 50 right now, and we’re just kind of keep adding more. There’s definitely a Pareto rule. So there’s, like, you know, the 50, or probably, like, 80, or maybe 90% of all, like, the budget. So, like, we’re actually pretty good, but you know, what we’ve got, but we’re always adding more.
I mean, if you have one client sign up and said, “Okay, well, we love all your integrations, but here’s, like, 50 more, like, publishers, we want you to integrate with, like, Business Insider, Wired Magazine, New York Times,” like this, on and on, which is great. We love that with our customers. And this one happened to be a very big customer. It’s a Fortune 50 company went to their vendors and said, “Okay, you got to integrate with Octane11 because we want to be able to measure it all with Octane11.” That’s a little bit of our kind of network effect. You know, some of the big ones, obviously, like, LinkedIn, all the Google properties, The Trade Desk, like I mentioned, Beeswax was one of your former portfolio companies. That’s in the media, but then, like, all the email platforms like Marketo, Eloqua, HubSpot.
Raju: You’re getting it all. So, when you talk about your ICP, you know, it sounds like you might have more than one here, but maybe can you describe who that ICP is? Like, somebody out there—you know, we get a reasonably large swath of listeners—if there’s businesses out there that want to leverage Octane11, basically, to understand the effectiveness of their marketing and to see where they should double down and where they should kind of back off I mean, Octane11 seems like the right solution, but what is that, like, ideal type of customer? Like, manufacturers are selling screws and bolts, or is it going to be larger, higher price point products? What is sort of that, you know, natural fit? I’m sure you can do way more, but like, what is the ideal? And then it sounds like you do work with agencies as well. Who are doing a lot of this on the behalf of many of these companies. So, maybe describe each of those to us.
Dan: Yeah. I mean the real, kind of like, center of the bullseye are large enterprises that are selling high price point products with a long sales cycle. And it really works across different industries. We have clients in FinTech, transportation, industrials, water industrials, just kind of a wide range. All it means is, if they’re selling business to business with a large group of buyers, these kind of influence a large group like, that’s what really defines it. There is B2B, which is kind of smaller where, like, I get it all the time. I get ads for, like, a podcast tool or something. You consider that B2B if you’re selling to a business, but, like, that’s really just one buyer who needs to kind of click and buy. So, it’s really for, kind of, larger ones.
Raju: Where there was multiple influencers in the deal, and maybe each of them needs to be engaged in that process, or at least be aware of the company so that they’re not, like, caught off guard when the decision needs to be made.
Dan: And then where Octane11, really shines because of our background is for companies that they spend quite a bit on advertising because that’s, like, that’s our background, and that’s where we’ve got, like, some real know-how, and that’s a bit of a white space right now, so if they’re spending, like, a million or more, is typically, like, cut off for us on digital advertising, like, that’s a great sweet spot for us. And then I’ll just say, like, the service providers for those companies as well, like, those are—so we sell with and through those companies, too.
Raju: Give me an example of that.
Dan: So, it’s like marketing agencies so, like, you know, large agencies, like, just Global. We just published a case study with just Global. It’s an agency that just focuses a hundred percent on B2B. We actually just published a case study yesterday with them on the work that we did for a large software client on Reddit. Working with agencies is really big, but we also collaborate really well with media platforms. So, we actually, like, go-to-market with Reddit. We co-promote with them. And then also with LinkedIn because part of our product is helping to show the impact of their product on actually moving revenue. So, that’s a great partnership there.
Raju: Hmm. That’s interesting. That’s super interesting.
Dan: It’s a great one.
Raju: A lot of relevance here from MediaMath. It’s really interesting. It’s almost like you took the, you know, sort of core capabilities that you were good at it at MediaMath, and did exactly what you talked about, which is focus it on a particular domain. But broader than just ad tech. Obviously, you do marketing as well, and so—
Dan: We went deeper in one dimension, and then we went wider.
Raju: Let’s talk about AI because, like, you cannot—like, in today’s world, like, we’re moving so fast with AI, like, nobody wants to sort of like, lock in on a particular relationship if they don’t feel like the company is going to be leveraging AI down the road or even currently, and what their strategy is around it. How does AI, sort of like, blend into your platform, both inside the platform, and maybe some of the things, if you can, that you’re sort of thinking about down the road and the possibilities? Because everything’s a sequence here.
Dan: Well, I wrote an article in HBR before I founded Octane11, which really kind of had the kernel of the concept. And it was really, it was about AI in marketing.
Raju: Did it make the MIT magazine? Because—
Dan: I don’t think so.
Raju: —I don’t read the other one. [laugh]. I’m kidding. I’m kidding.
Dan: No, but the basic thesis was, like, AI is going to be super powerful for marketing, obviously, but it’s not going to be valuable unless you get your data in order. So, you need all your data from all your channels synthesized in a way that the AI can act on it. And so, like that actually is, like, the blueprint for the Octane11 business plan is synthesizing the data and then applying AI. And so, like, that’s where we’ve been building towards the whole time, just synthesizing the data across the channels, unified data model against companies and revenue and all that. And what’s interesting, really, is, like, about a year-and-a-half ago, we plugged in Gemini 1—right now we build on the Google stack—plug in Gemini 1, it was like, okay, good, but it wasn’t, like, super smart.
And so, we said, okay, let’s not build all, like, the tooling around, like, an AI experience, right now. We just keep focusing on the data model, more data, more connections, better synthesis and all that because we know the AI is going to keep getting better. And so, six months later, Gemini 2, we plugged that in. It was like, still not great, let’s keep going. But, you know, we’re kind of, we know where the puck is going, and we kind of like skating towards it.
And then in November, Gemini 3 dropped, and we plugged into our platform, and it was like, insane. First of all, it knows a lot about marketing right out-of-the-box, but like, plug into our data and plug into our knowledge base. So, it’s got, you know, years of information about, like, how this works, and the integrations and accuracy levels across different partners and cadences and all that kind of stuff, and so it’s now incredible. Like our clients log in, they—we use it in the sales process. So, like in our platforms, imagine—we can get into a demo if you want. I’d love to do that.
Raju: [laugh]. Yeah, I don’t know if I’ll have time for a demo, but—
Dan: We don’t have time for a demo—
Raju: I know you’re so excited about that. I love that.
Dan: It’s just crazy. And you know, so we use it in the sales process. Our clients, day one, like, they’re just asking, like, the Octane11 AI assistant, like, “How does this platform work?” And it just will lay out, like, a, you know, an education series for you. You know, so it’s like, great for onboarding new customers. Like, “What are my insights?” “Write an email summary to the team about what happened last week.” “Send an email to the sales team to say, like, these are the top accounts and why, and what you should talk to them about.”
And it’s just getting better and better. You ask, like, where is it heading? And the AI right now will make recommendations, like, what should I do next? I mean, you can ask it to but it kind of already does, you know, because every answer it gives you, like, a, would you like to do this next?
Raju: Yeah, interesting.
Dan: I recommend, you know, if you’ve got another $100,000 a budget, spend it on these audiences, on these channels, with this creative. And, like, the protocols to then connect that into the other platforms is evolving very rapidly.
Raju: I see. So, then it moves from recommending to actually executing.
Dan: Yeah, it can. With, you know, a human in the loop. You know, a lot of our clients are agencies, like, they’ll have the opportunity to take advantage of that too or not, but like, that’s really coming. And there’s a protocol emerging now, which is kind of a spin on an MCP, which is the Model Context Protocol, just kind of the general API for AIs and LLMs to talk to each other, to talk to data platforms, but there’s a version that’s there’s a working group building an AdCP, which is, like, it’s an MCP that’s particular to advertising industry. And so, you know, it’s not too hard to imagine, like, our MCP talking to AdCP.
Raju: If you look at industries that can be absolutely impacted by AI in a positive way, you know this is definitely one of them. And I love the fact that you guys, your audience is very—you’ve isolated it, right? You said, look, it’s B2B spend, it’s people who have a certain level of spend, and a product that, you know, is a pricier price point with a longer sort of sales cycle, but more importantly, like, you’re basically the owner of their data, both internal and external, like, you’re grabbing it all, and so that is a giant moat in terms of the business. And then you’re applying, sort of like generalized AI. Is there anything sort of unique that you slant the AI toward? Is there a small language model sitting inside of Octane11 that’s sitting there saying, “Hey, you know, I’ll use Gemini for X, Y and Z, but like, some of this core thinking, you know, we’re just capturing and we’re going to get smarter and smarter as we work with more and more clients and agencies. Or maybe you don’t divulge that. I mean, it’s up to you, but, like—
Dan: It’s a great question. I can definitely see us going that way. There is a ton of training that we do to the models and it’s mostly in the instructions that we’ve accumulated over time in that knowledge base and in our documentation that’s, like, makes it smarter and smarter. In terms of, like, the selection of the LLM, like, we built with Gemini mostly for convenience. It is outstanding and Gemini 3 is great, but like, you are seeing, I wouldn’t say divergence, but maybe just kind of, like, one-upsmanship on the different models [crosstalk 00:33:36] now.
Like, I’m going crazy on Claude. Like, I don’t know if you saw that I built a video game using Claude that’s, like, it was more of, like, a promotion for Octane11. I said, “Well, can you create, like, a tech mobile game that’s, like, a B2B marketer?” They have to collect data, match it to companies, build reports, get AI insights, and that’s how you win.
Raju: Like Office Worker, or like Restaurant Worker where it was like—
Dan: Yeah.
Raju: [laugh]. Like, a sim, right?
Dan: Yeah, that sort of thing. And you can throw reports, you can shoot reports. You got to dodge the baddies. You know, I made that in, like, the first version, like, literally, one minute on Claude.
Raju: Yeah, that is crazy.
Dan: I mean, that’s just to say, like, Claude is definitely doing some interesting things that the others aren’t yet.
Raju: I mean, this is—I’ve talked about this on a previous podcast—I mean, we’re living in an era where internet and AI are very similar in nature, in the sense that, you know, they’re both query-based architectures, and, you know, you basically ask for something. In the case of the internet, they’re just finding links and providing them to you. In the case of AI, they’re performing some intelligence and deciphering and maybe even some creative. But the platform companies are all trying to out compete one another, like they did in the internet. And you know, you basically had Excite and Lycos and Alta Vista and Ask Jeeves and Yahoo and Netscape and Mosaic and Firefox, and they’re all building the same functionality, but there isn’t a lot of you know, true differentiation. You might be better at one point in time.
That is great for companies like Octane11 and application companies because you can leverage the most inexpensive, you can leverage the best performing at any given time, depending upon what you’re trying to accomplish. So, it’s basically, like, a really powerful way for a company like Octane11, that has the relationships with the agencies and the enterprises and has access to their data and is accumulating that level of mode to use and utilize, you know, LLMs for, you know, relatively generic purposes. That’s kind of what I’m saying, but as long as, you know, you’re maintaining that training data, and you’re getting smarter about what you’re asking and how you’re asking it. So, really awesome. So, just quickly, how do people get in touch with you if they’re interested in your platform?
Dan: The best place to find me is on LinkedIn. I mean, I’m on LinkedIn all the time. So, Dan Rosenberg or look up Octane11.
Raju: But if they want to ping your company, go to your website?
Dan: Yeah, the website is there. And you know, play the video game. Go to octane11/game.
Raju: [laugh]. I’ve been playing it for the last half hour. I haven’t been paying attention. It’s excellent. Excellent.
Dan: I’m working on getting a leaderboard in there.
Raju: That is fantastic. Okay, I’m going to just move to the Gatling gun section. I don’t have a lot of questions. Actually, I’m going to tell one more story. I have to tell this story. Rave’s first office, you remember our first office? We talked a little bit about it? On 11th and, I think, 23rd?
Dan: Yeah.
Raju: We were actually attached to the High Line before the High Line was anything.
Dan: Yeah.
Raju: Wow, what a place that we had—like, we just were ahead of the curve on a lot of things. I remember we had, like, 20 people in it, and you used to arrive at the office first, and you kind of like, use the key to try to get in. And the doors locked, and you’re knocking, nobody’s there. And so, you went to the back, and I think you went up the stairs, like, the emergency stairs or fire escape, and one of the windows was broken.
You know, the High Line wasn’t super, super safe. I think people walked in and saw a bunch of laptops and, you know, monitors. And Dan pulls this Spider-Man. Like, he literally, like, crawls into the broken window. It’s like, one of the top all—like, you know, like, I don’t know how to get in, and he unlocks the thing, and he’s, like, calls the police. I mean, that’s the kind of guy you are. Like, it was—I was unbelievable. I remember that. We had to eventually move, but [laugh].
Dan: We got broken into several times.
Raju: Yeah, we did. We did. I don’t know, like, listen, you do what needs to be scrappy. But, you know, we had 20 people in there. We knew we had to live. Okay, so the Gatling gun is, I want to answer just two or three questions. Just give me your, you know, off-the-cuff answer. And, you know, these aren’t planned. So, favorite ad tech campaign.
Dan: For some reason, the one that kind of jumps in my mind, which is, like, really funny actually, is, like, there was one campaign that we saw at my MediaMath days which was performing so well, and it was, like, getting so much engagement. And we were, like, “What is that ad created?” We had to go in and look at it. And it was an image and it looked like there was, like, a hair on it [laugh].
Raju: [laugh].
Dan: And so, [crosstalk 00:38:20], that people were seeing it on their phones, and they were like, trying to, like, move it—
Raju: Oh, my God, the hair [laugh].
Dan: You know, kind of brilliant, but also, like, it just kind of tells you, like, clicks alone, like, aren’t really, like, a thing. Like, you need to, like, track all the way through to a purchase. Like, that’s really, you know, what’s going to move the needle.
Raju: That is hilarious. That is so funny. Yeah, people are really, kind of, like, really creative that way. They find ways to click, but you’re right, like, just the click itself doesn’t really matter, right? Like, it’s getting the clicks that you want, right? So, all right, so you have three children, which one’s your favorite?
Dan: [laugh]. All of them. All of them.
Raju: [laugh]. All right, all right. Favorite hair product?
Dan: Oh, gosh. You know, I once did a costume as a kid and I had, like, Dippity-Do. I had, like, [crosstalk 00:39:13] my hair up. But like, I haven’t used hair products for a while.
Raju: I just—I’m like, I would love the roundness of your head. Because I don’t know, like, if I shaved my head, I don’t know what it would look like. I’m terrified of it actually doing that.
Dan: There’s some new tech coming down the pipe that’s, like, gonna solve [crosstalk 00:39:28]
Raju: Like silly putty that you can, like—[laugh].
Dan: There’s like, a real [unintelligible 00:39:31] for male pattern baldness and, like, it’s coming out in the next couple years. So, I’m going to have gray hair, like you.
Raju: Oh, you’re going the other way. Okay.
Dan: I’m going the other way.
Raju: Yeah, I was trying to think maybe I’ll go, like, you know, less hair at some point in my life, and I’m just afraid. I’m afraid of what we look like. And so, I think, like, you’d have to, like, kind of use some kind of putty to, like, round it out.
Dan: When I was in China, something else we learned as an expression, less on top, more inside.
Raju: Oh… I like that. Yeah, there we go. Well, thank you so much, Dan. This was a wonderful podcast.
Dan: Yeah, really fun.
Raju: Just want to say thank the listeners for, you know, chiming in this time, either by video or by audio, and we will see you again next time.
Dan: Thank you.