From Publishers to Platforms: Evgeny Popov on CTV, Career Exits, and the Future of Television

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Careers in AdTech don’t follow a straight line. They follow the market.

In this episode of Signal & Noise, we sit down with Evgeny Popov, a global media operator whose career cuts across publishers, agencies, AdTech platforms, and now television data—from News Corp to Lotame, Verve, and today at Samba.

This isn’t just a career story. It’s a map of how the industry actually works.

Because Evgeny has seen every layer of the ecosystem up close—how publishers monetize, how agencies operate, how data platforms scale, and how companies position themselves for exits. 

And now he’s sitting at the center of the next major shift: the transformation of television into a data-driven, measurable, and programmable channel.

1. From engineer to global AdTech operator Evgeny didn’t start in media—he started in engineering. That technical foundation became a career advantage as the industry shifted toward data, automation, and programmatic systems. 

2. Building a career across every layer of the ecosystem Publishers → agencies → DSPs → data platforms → CTV This wasn’t random. It created a rare, full-stack perspective on how media actually functions—and where the leverage sits.

3. What actually drives successful exits in AdTech Evgeny has been part of multiple acquisitions. The takeaway: It’s not just about product. It’s about timing, signal, and positioning within the market.

4. Why relationships matter more than people admit In an industry that constantly reinvents itself, networks compound. Or as Evgeny puts it: “I collect good humans.” 

5. Inside Samba and the rise of ACR data We break down how Automated Content Recognition (ACR) actually works—and why it’s becoming one of the most important data signals in the CTV ecosystem:

• What’s actually being watched (not just served)

• Cross-platform viewership across streaming, linear, and gaming

• A deterministic layer in an increasingly fragmented landscape
  

6. The real state of CTV (beyond the hype) CTV is growing fast—but measurement is still broken. Fragmentation, inconsistent currencies, and platform silos are holding the market back.

7. Television is becoming a data problem Not a media problem. Not a creative problem.

A data + identity + measurement problem.

And whoever solves that layer controls the future of TV advertising.

We’ve spent the last decade talking about:

• Programmatic

• Identity

• Data platforms
  

But television is where all of it converges.

And for the first time, we’re seeing:

• Deterministic signals (ACR)

• Cross-platform measurement

• Real competition for the “currency” layer
  

This isn’t just the evolution of TV. It’s the reconstruction of the largest media channel in the world.

• AdTech operators thinking about where the market is heading

• Anyone working in CTV, streaming, or measurement

• Early-career folks trying to understand how to actually build a career in this industry

• People who want the real version of how this ecosystem works—not the slideware version
  

If you strip everything else away, this episode comes down to one idea:

The people who win in this industry aren’t the ones who stay in one lane. They’re the ones who understand how the entire system connects.

Evgeny is one of those people.

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Read the full transcript bellow: 00:00:03:11 - 00:00:13:16

This is signal and noise bringing clarity to data. And AI.

00:00:13:18 - 00:00:37:16

Hey, everybody, welcome back to Signal and Noise. I'm Brett House, joined by my co-host Rio Longacre. And today we've got Yevgeny Popov. Who has if you don't know him, he's at samba TVs. But one of the most interesting careers in modern media. His path across publishers, agencies, adtech platforms, data companies is pretty unique, right? And you've had leadership roles, of getting it.

00:00:37:21 - 00:00:57:09

We'll call you. Yeah. I've just to simplify the syllabic, aspect of your name, multi syllabic aspect of your day. You've been in York, News Corp Australia, so you were on the media side lo to me, which is certainly interesting, was around for a long time with Andy Manfredi. Acquired that long ago. Yep. Yeah. Verve.

00:00:57:11 - 00:01:12:04

One of the last data management platforms to be acquired. Although I know you guys had a lot of pivots. And now sort of a TV, and you've, you've, you know, you participated in a bunch of exits, a bunch of company exits, which, some of us have had, I think you see it three times, right? If I'm not mistaken.

00:01:12:06 - 00:01:30:05

Can I just clarify that statistic because I think people go, yeah, go for it. When you say exit, you know, people say, well, you don't have founders. You actually exit the business as a founder. So have one exit, which I have company which I founded and exited, which is US Coffee loyalty app, which was back in Australia. I can tell you more about that.

00:01:30:09 - 00:01:48:11

So it's it's a it's a real statistic. And then two companies which have been acquired, you know, and me being part of that. So just to be on that caveat that yeah that us. Yeah. Just because I think that I'll, you know, when you're the founder, you just make more money out of the whole deal. All right as well.

00:01:48:13 - 00:02:10:11

So so bragging rights to. Yeah. It's awesome. Right. Yeah. And I'm, I probably make a fool of myself saying that now, but out of two of them, I made $0. So yeah, you know, I've been through two exits, in the DP world with X late in New Star and the identity data tech world, with TransUnion. And to your point, yeah, D came out okay, but definitely not the founder model.

00:02:10:13 - 00:02:28:08

To your point, but, you know, Ria says you're one of the best connected, most network guys in the. And there's a lot of people, which you which I'm interested to hear more. So why don't you tell you all? It's a little bit about yourself for those that don't know. Yeah, yeah. No, thanks. Brad. What? What a wonderful introduction.

00:02:28:13 - 00:02:53:10

Brian, the video. Thank you for having me here. Such an honor. Energetic question about connections. I think I'm a collector. I like to collect good humans. And from my career. That's exactly what I've been doing. You know, I've been ex-pat for the past 26 years. I left Russia in 99 and moved to Australia and spent 15 years in Sydney.

00:02:53:12 - 00:03:12:23

Moved to Singapore, spent five years there, and then came to New York in 2018 and 19. Then I have done one year in Latin America just just for the fun of it. So like, you know, I've been around, but one thing is, you know, you move countries, you move continents, you move companies. But the one thing you have is you collect good connections and network.

00:03:13:01 - 00:03:41:02

So I think I'll, I'll take this compliment. I don't think how true it is. But throughout this, you know, 25 years of, of moving around, you definitely meet a lot of people, surprisingly, in our industry. Brad, you probably can attest to that. A lot of the same people. So, yeah. So if you talk about measurement incrementality of my network and how fast is growing, it's a you know, I was always surprised that I was still in Sydney back in the days coming to a programmatic IO.

00:03:41:02 - 00:04:02:13

Like, you know, when it all started, 2013 then and then it's one degree of separation. You bit the same people in the early stages and still meeting the same people. So it's it's interesting to see. In fact I don't them they names, but you see people who account managers when I met them and now the cro of of of public companies, you know, and it's like wow.

00:04:02:13 - 00:04:22:08

Like you know, you see the evolution and how some people are supercharging their careers. And I've been so fortunate to, to be part of, of that. So, yeah, that's an it's definitely a journey. But I can I can tell you a bit more about, I guess, how it all started. And yeah, if you, if you want to tell us your or your story.

00:04:22:09 - 00:04:38:09

Yeah, yeah. In fact, maybe before you jump in too. I mean, I think that like, like that's the reason I, I'm sure listeners want to hear about that because I think it's a cool story. Right? I mean, looking at your resume and like, and this was what I thought would be like really fun discussing is I get crosses, not only all these different layers of the industry, right?

00:04:38:09 - 00:04:54:19

Publishers, media agencies, programmatic and now TV data. Right. So I think that looking at your journey, understanding and like I love to hear insights, especially your current role, but maybe we we table that for a little later right about like how you're taking this vast experience, how it's applying to to CTV to measure. I mean, it's a rare perspective.

00:04:54:19 - 00:05:11:02

So I think it's going to be a really cool discussion with all that's going on, especially with CTV. So maybe kick us off there. Tell us about how you got started. So how's that? You're kind of like like many of us, an accidental media executive. So I love to start there. I like that I like Accidental Party because it's exactly.

00:05:11:02 - 00:05:36:16

Was that so to Brad's question earlier about the exits and how it's all started, I started as an engineer. You know, I've started my career working for, Microsoft, joint venture with, one of the publishers in Australia, in Sydney. But before before that, I actually came to Sydney to work on one of the first meta travel search engines that called Hotels club.com.

00:05:36:18 - 00:05:55:16

That was the first exit which got acquired by Expedia, believe it or not. Okay. Yeah. Yeah. So by Orbitz but then it now it's an experience hands. Yeah. And so it was an interesting way I was head of kind of technology had big team. I was like 20 or something. Had 25 people coding and, you know, doing all this cool stuff.

00:05:55:16 - 00:06:18:07

And then it's got sold and they didn't know anything about stock options, what the transaction should look like. But, you know, I got I kind of come in with engineering and data, pedigree back in the day. So that's always was my DNA. Even now, you know, it just it works in the adtech, martech space because of the just the technical knowledge.

00:06:18:07 - 00:06:35:17

It just helps a lot, because we do end up going down those paths quite frequently when we talk to. Yeah. And, you know, Ryan, I met at, I just spoke really briefly at Market Alive, and I was selling. I was like, hey, I'm. I'm shipping code again, you know? And my team was looking at me like, what?

00:06:35:19 - 00:06:53:16

You can code you, you know, it just feels good. You know, like it's kind of free 60 going back to your it's going to, you know, obviously at a much faster velocity with, with with the ability to with, oh my cutting. And you know, I can go into the weeds of that, but there's just like, phenomenal pace.

00:06:53:16 - 00:07:16:14

It's, it's so good that my wife van need to work on Sundays. So, I'm not allowed to touch keyboard on Sundays. That's how I deal, because that's so addictive. You know, it's really is. Yeah. So free up. Getting open call for a bot implemented on my Mac. This weekend, by a common friend of ours from snowflake.

00:07:16:14 - 00:07:33:04

And so I'm going to be diving deep. I use Codex a little clod as well, but it's, it is incredible. Well, just generally speaking, I find that, like, so many things like that in my job that. Yeah, I was doing ten, 15 years ago, I'm able to do again and I'm Deb, do it faster. I'm will do it better.

00:07:33:06 - 00:07:52:22

It's really cool feeling. So yeah, I know where you from. Real like it's so cool that I was at the gym this morning. It's a true story. I've purchased a domain on the fly. I created a shell of the project that I'm working on, which I'll be deploying, and I've built a scaffolding as I was doing it between repetitions, like, this is not the job.

00:07:52:22 - 00:08:10:20

This is what's badass. Yeah. And this is stuff that would take you potentially weeks. But this was this just this morning. I have it and I'm about to deploy it after this call. And I'll send you the link. So like that's all done and to and, you know, architecture deployment hosting domain names already. Isn't that incredible. Yeah.

00:08:10:20 - 00:08:39:15

And like you and we we're learning these things sort of on the fly and it's happening. So like just as an example in my life, I just so the guy that's, that's implementing this bot on my computer and getting me open educated, took my website, ran a full audit of a site that I spent. I hired a team, you know, outsourced that built all this content, spent weeks doing this, like, back in December, you know, weeks and weeks and weeks getting this site up, you know, and I'm like, I'm still not particularly happy with it.

00:08:39:15 - 00:08:58:12

High signals.com. And he over lunch, he's like, I'm making lunch right now and I'm going to rebuild your website. And, you know, an hour later he sends me the rebuilt website, completely hosted. Almost so much better. You have all the assets and it just blew me away. I was like, oh my God. And it wasn't just an imitation.

00:08:58:12 - 00:09:25:12

It was a reconfiguration. There was some better packaging, some better like, sort of how we engage, how we work type of workflows that I thought of about, but I just hadn't implemented. So it's pretty amazing how quickly that stuff can. But you're right, time to market is, you know, it's a godlike ability and, you know, kind of taking it back to the engineering days when you understand how the code works, you can understand what's under the hood.

00:09:25:12 - 00:09:46:00

You understand technology, understand product. You're a builder. That's one of my virtues. Like in a you are that like that takes you to a different route, a different dimension. And there's so many different extensions, so many different utilities. We can talk about, how to virtualize things. You have, like I have a five agents working with me when I it's called vibe code.

00:09:46:02 - 00:10:10:14

One is an architect, one is a product manager, one is a like, you know, and they all swarm in each one. They all talk to each other. They talk to me. I'm a main input, but they helping me fast track things so much faster. They contextualized on the project of what I'm working on. Right. So you can like they understand the semantic meaning of what we're building so they're not just in a Claude agent who has zero context of the project you're working on.

00:10:10:16 - 00:10:33:01

And then you can expand on that. You can kind of, you know, train them on the data which you're building or trying to build on. So they become smarter. So it's it's unbelievable. Like what you can do on your, on, on very this laptop we just talking on the phone before this is all pretty new is like the whole like the gentex workflows like really like got like I'll do it like last November, December.

00:10:33:01 - 00:10:53:07

They really got to a point. You could just deploy them. So it's it's new and it's amazing. Like how quick how quick it's moving. You know, it's it's it's really it's really remarkable. So yeah I it was cool to hear you're digging in as well. I mean like, as many of us are. So if you have any maybe just get getting back to the to the the questions here like looking at seabirds, grouse, pubs, agencies, data companies, programmatic platforms.

00:10:53:07 - 00:11:08:12

Fair to say this was like I mean know some really cool jobs off there to say this was this is a deliberate strategy is more like you or was it right? I love if you could tell us about that. Yeah. Thanks for it to keep me in check. Otherwise I'll be a gigantic all the way. So. Yeah. Thank you.

00:11:08:12 - 00:11:30:18

We could riff one now for a while. No, no, I know back to the story. So, so coming out of the, you know, you know, that exit and joining in Dynamo sandwiches JB with Microsoft and working on that, you know, kind of bringing the Microsoft Exchange in 22,009 and working on Atlas and etc. and the names probably only Brian or Kelly and the you guys remember.

00:11:31:00 - 00:11:55:04

Right. So yeah, I remember that. Yeah. So, so working with those that the built in the behavior profiles and the retargeting for the first time rich media anyway. So that was kind of an invitation to advertising on the publisher side. But then one of the recruiters came up to me and said, you have the this is just one startup launching in Australia called Brand Spring, and it's one of the first Asian DSPs.

00:11:55:08 - 00:12:15:15

Would you like to join that team to build a product and technology and being part of that team, just to look at the partnerships. And I set this up on our to be like, you know, and that was that was the 2000, I think ten when, you know, ten. Yeah. Just under when that just started and and by accident as commerce complete pivot.

00:12:15:15 - 00:12:38:12

I took a leap of faith. I was very comfortable where I was okay. You know, had the team was in charge of VR and physical stuff and, you know, innovation in rich media, but then pivoting to absolutely unknown and taking like a leap of faith on technology, which I do not understand, but that propelled me just, you know, to this universe of, first of all, you know, to commodity.

00:12:38:12 - 00:12:54:16

Like no one knew what programmatic was back and that it's, you know, one of the first people who build in something you talking to Ed Mills of the world is talking to companies that don't exist or been sold acquires like Egon, Zlatan, Paul. Yeah, yeah. Excellent. That's right. Yeah, that's what I was. And so it's funny, we all have that origin story.

00:12:54:16 - 00:13:12:20

You start, you're just like, I remember my eyes being wide up and going, I can't believe all this is possible. And got it. We've come a lot further since. Yeah. So you have any a little, little background here like, Brett and I met at a small media agency where we were actually, you know, pre programmatic or just we were just doing like buying kind of arbitrage.

00:13:12:22 - 00:13:32:22

Yeah. Right. Yeah. It's performance marketing stuff. Yeah. A lot of it was CPA or they would pay you CPM. You'd arbitrage a CPA for different like three response brands, you know. So that's how we that's how we met. Yeah. That's awesome. That's awesome. Yeah. And eventually that type of tech orientation to to your point gets you connected to other places.

00:13:32:22 - 00:13:50:13

And then you're like, you know, I'm, you know, and you know, remember when big data was a term like big data, you know, that that that's what kind of led me to excel at I was like, I want to get into the space before they were even a data management platform. They were a data marketplace that just had they were like a cookie farm, that was founded in Israel.

00:13:50:15 - 00:14:08:03

And so I joined that. And then we sort of evolved that. But that was a yeah, getting early in, in that journey and and seeing how it's evolved has been fascinating. Oh it's so fascinating bro. Like, you know, Bluekai just entered the Australian market, you know, and and the Omar technology was like, wow, we know DMP right.

00:14:08:03 - 00:14:31:10

So like data meant like big data, right. So to your point, like how do you manage customers data assets and what that means in marketing activation? So I think it was phenomenal. So that was kind of the inception of like programmatic going into China, working with Baidu's of the world back in 2012, beating out on cost because of structure was so expensive back in the days, like so many mistakes, so many.

00:14:31:12 - 00:14:52:03

So much to learn in fact, Kadri on was had one person in Australia and we were built an image DSP just for them. Right. And that for a key as well. And kind of you know, they had this agency tried this remember to to use this was kind of just just surfacing up and we competing against media math.

00:14:52:06 - 00:15:13:14

The brand turns data z IP a lot of our IP, XR and and maybe, maybe that's a trend that wasn't even even born yet, you know, so like, yeah, yeah, yeah, yeah, yeah. So that was like the epoch of ad corneas and ad networks, right? So I was like, Tony, I remember that. Yeah. Yeah, yeah.

00:15:13:17 - 00:15:35:10

Like the. Yeah. That was like the height and yet but you know, close to the end of the ad network thing. Yeah. That's right. So building on that and developing technology which was amazing. So that's kind of was my induction into the, into the programmatic into real programmatic world through people in Australia, new with, you know, with the help that was going on and, I wasn't one of them.

00:15:35:10 - 00:15:53:07

So, yeah, that's for sure. And this was all before this is before you joined, Verve. Right. It's before news. Like I saw those after that News Corp and like, you know, remember another acronym now. So that acronym not agencies try this, but publisher Trade desk so you remember those ones. So we kind of built in the programmatic capabilities.

00:15:53:07 - 00:16:13:16

Think of it. You know the waterfall after you know, the remnant inventory. Remember those conversations that how can we sell at that at the open auction and built in a stack behind that? So I was instrumental of, of actually building and, you know, bringing partners like Rubicon Project and adopted back in the days and building that just kind of like the, the like.

00:16:13:17 - 00:16:31:02

Like what? Like before actually yield management solutions even came out. Right. This is kind of the predecessor to that real that was that like I'm proud of this moment. You know it's I'm not sure people know that. But we were the first. We ran the first PMP in Australia for Rubicon Project. Like that was the first PMP on News Corp.

00:16:31:04 - 00:16:54:00

That was first deal ID of a crane in Australia. You know, for that technology. Yeah. And that's McKnight. Yeah. So you see like and and sparks of Gorski was the one that brought those companies tremor the tremor video tremor media was originally it became tilapia that joined Rubicon Project and they formed it became magnate. Yeah. So you've been on a lot of these pivots, right?

00:16:54:00 - 00:17:12:23

Like like the, you know, lo to me went through a bunch of different pivots, and started out as sort of a data management platform. And, and they got into data collaboration. They were like the last DMP standing. Everybody was like, you know, sold and aggregate knowledge sold and bluekai sold. And everybody's like, what's going on? Tell us a little bit about that experience.

00:17:12:23 - 00:17:35:13

And, and verv similar, similar a of. Yeah, it's with verve you live I mean it's bright like a lot of me, it's such a demand for a big shout out to Andy. You know, a lot of his energy, his vision and kind of, you know, journey on his team, effectively initially on the DMP side to some SAS to publishers, South Australia moving to Singapore.

00:17:35:13 - 00:17:55:17

But then we realized, hey, there's a untapped opportunity to build a data marketplace in Asia in that pack. So I've started doing that as a solo, kind of a lonely wolf. They called it, you know, running a different markets, you know, going in traffic. Yeah. You were effectively like a general manager of that, like. Yeah. Well, I don't know if you could call me because I was interviewed for a 60 trafficking assets.

00:17:55:20 - 00:18:25:23

Right? Yeah. I was trafficking ads in DV. I was going to publish this required data. So I was like end to end from acquisition to to prioritization to opening in emerging markets like Taiwan and Hong Kong. In fact, Jeff was Jeff Green was in Hong Kong when we were kind of working with Trade Desk. He was living there, you know, so interfacing with him back in the days when he was approachable, you know, in that capacity, before obviously, you know, the growth I have had so been in that stream was amazing.

00:18:26:01 - 00:18:49:10

And frankly, you know, just to fortunate to have the opportunity to grow with a lot of me that moved me from from Singapore into New York to oversee global business for them. And in fact, you know, humbly, I do take some credit for, for that asset because the team under my leadership with obviously with Andy and everyone else, that's the data signal which publishers needed.

00:18:49:10 - 00:19:10:12

They acquired a lot of me for international traffic and can't take credit for it. But the team would have built together starting in Asia and and moving into Latin America. And Emir, that's the signal which was complementary to epsilon PII data, which they have at scale. So that's, you know, to your podcast signal. That's what they bought it for.

00:19:10:14 - 00:19:27:05

Yeah, it was the international signal. That was it. And that's very, very hard to get. I mean we saw that with excellent I mean, you know I was at TransUnion where they have credit data. But you know, which is certainly multinational. But it's very hard to get once you get outside of. Yes, because of governance and privacy constraints.

00:19:27:05 - 00:19:49:05

And it requires partnerships. Tons of tons of it was tons of work. Yes. You're right. Like, you know, and there's a lot of benefits from many things. They had a deep business. So a lot of broadcasters, publishers, they had that DMP technology to understand their consumers and to profile them, to cluster them, you know, to activate them. So you had that technology already deployed, and a lot of networks had pubs.

00:19:49:07 - 00:20:09:05

So we used that footprint to monetize some of that data anonymously for the marketplace. So you had that leverage of SAS integration across different geographies as a backbone to actually build upon, to build a marketplace on it. So yeah, so that's why I put that exit just a little tick and you probably will shout at me. But you know what?

00:20:09:05 - 00:20:27:11

I'm proud of that work and I'm going to stand by it. So yeah. Yeah. You're a fundamental part of the team that that that's worth counting. Right. And he's one of the most like people in the industry. Like he's almost universally liked. I mean, I had Solomon who is there for a little bit. He's, he's I'm pretty tight with him and only good things to say about him.

00:20:27:11 - 00:20:46:05

So I so many good experience working together. Sounds like it had a good outcome. So congrats on that. Yes. And Adam as well I worked with that while he was there. And so yeah, that was it was great team. Great team. So then, so then you move to dinner at Verve is Verve follow letting me I'm I'm getting the the chronology wrong here.

00:20:46:08 - 00:21:06:14

Yeah I'm so my now like I remember Verve back in the day in New York City. They were, like a location data company, correct. You know, all the all the all the, you know, mobile, mobile data kind of Foursquare in some ways, right? Yeah. Like and all the people are, you know, complaining that it was, oh, it's crap data.

00:21:06:15 - 00:21:26:07

You know, we had cookies, so I'm not sure how much. Yeah. How much worse or better off they were or worse off they were, but yeah. To it. Yeah. I'll tell you about the first. There was a story. So, parent company versus MGI meta game invest. So what they really focus on is gaming on an upgraded on console, on your phone, on laptops.

00:21:26:07 - 00:21:48:00

Right. So you have the gaming, mogul with with a lot of games. And they said, well, let's just start the ad business because we have a ton of PII data for, for gaming. And we're going in for behavior for gaming, you know, for purchase, etc.. So let's just buy businesses on bulk, buy sell side and build a business out of this.

00:21:48:00 - 00:22:10:00

And they Ceramica was behind orchestrating all of that. And it's very knowledgeable and knows how to acquire businesses at the right moment that for the right price. That's his you know, that's a superpower. That is. Yeah. He's just he's just he's just good at that. So. Yeah, that's that's an important CEO superpower. It's like if you don't have all of the organic growth you need, you need inorganic growth, which is true.

00:22:10:05 - 00:22:29:18

Yeah. Right. Can help bring some cash in the door. Ability to bring in money and ability to identify acquisition targets and pull the trigger. Yeah yeah yeah. And you know and and they did this like this and I still doing this you know with capture acquisition and junior group etc.. So like you have a pull for of businesses and buy and sell side which they, you know trying to orchestrate it and make sense of it.

00:22:29:20 - 00:22:48:17

And at the time in like that it was need of transformation and consolidation across both sell buy and sell side. They had three BS. You probably know them Brad pub native and smart. So and I think yeah yeah yeah yeah yeah. So like they bought a lot of a lot of good media and mobile for it first.

00:22:48:19 - 00:23:10:03

SSP then they had, they have acquired like three DSPs and contextual player and now they have an ecosystem play. And more importantly, how do they do that? Propagate the gaming data through it as your unique source and differentiation. So back to like FC. Every conversation we have we've go back to the signal like that's yeah yeah it was it still was it.

00:23:10:03 - 00:23:32:06

Did it continue to be mobile centric despite the you know did the gaming acquisition. Did they buy it. Did they buy the games themselves or did it by the publishers or just the games. Like how did that work? Yeah, they bought the publisher. And it produced a lot of like, I think 5000 games or something, you know, like car racing games, you know, like little utilities.

00:23:32:08 - 00:23:46:15

I understand. Look, I'm not a big gamer, but they delivered on on. My dad is 82 and he plays games. Anyway, so so their business, I mean, that's okay. Everyone talks on up on Apple heaven all the time and you know. But you know, what do you think about the whole business? It's just mostly just mobile mostly games.

00:23:46:15 - 00:24:03:19

So yeah keep going. Yeah. Yeah. It certainly thematically reminds me of Apple up and and what they did to build their ecosystem. But yeah they became mediation for that. Right. So that has supplied had the had large demand and you know the consolidation that was and you know that came in as a head of international and kind of mapped that together.

00:24:03:21 - 00:24:31:16

Yeah. And I was interesting. I never managed CEOs. Right. Although there were small businesses, 50 people, companies which been acquired. I never managed people, you know, who had exit strategy, who had the owner strategies, like actual and a bunch on how to have, you know, full of incentive on how to imagined. Right, trying to consolidate businesses with potentially, you know, conflicting interests and or self-serving interests, you know, which rightly so.

00:24:31:16 - 00:24:52:07

If I was a co-founder, the tech becomes the the tech in the data part. It's actually these differences, the incentive structures. Right. The alignment across organizations that that becomes the hardest part. You get fiefdoms, right. But that's the hardest part. You know what that that's that's challenging. You know, you can look at it. How do you learn from that?

00:24:52:07 - 00:25:19:08

How do you you know, you know, for me that was a great learning curve. And and versus was great for that. And then in between that had a bit of agency and experience and you know, and now I'm now I'm at bar, so kind of I think I work for everybody except, to the brand. So Brad to, you know, if, you know, to swing over from the donor side in three years time, you know, if this this next step is probably not working with a CMO now.

00:25:19:08 - 00:25:38:20

So that would be the end of it. Yeah. Yeah. For those fellows. Brett, have you worked or have you worked for brand? I don't think you have. I've not. I've been on the vendor tech side for ever. Yeah. Yes or no? But samba TV, I mean, everybody knows it is Ktvb. Maybe that's where their knowledge ends.

00:25:38:20 - 00:26:03:19

Obviously, it's data. There's some measurement. You have ACR technology, which kind of, brings me back to Nielsen because ACR was talked about all the time. That's automatic contact. Automatic content recognition. Yep. That's right. Right. Which is, which is basically the ability to track on the television glass, what's being watched and all of the content metadata like Gracenote did that, which was acquired by Nielsen.

00:26:03:21 - 00:26:27:10

But tell us because because I think we kind of walked this trajectory for a reason. There's a purpose. We those are purpose. We went through your this meandering path of of yes. Background. Because because it's a really interesting perspective to bring to the television and connected TV world. I mean, how do you see all that connecting and tell people a little bit about samba TV as well, and what you what your vision and mission is?

00:26:27:12 - 00:26:45:22

So for me, it was I think, a natural progression. I was like, you know, what is next? What what areas of unfamiliarity I can enter to like to get better at. And you know, I never, you know, I this data for a lot of me like we had that we had this data back in the days, you know in cable before the could for the for the problem.

00:26:46:00 - 00:27:06:04

So who doesn't have Visio data. Right. That was like well, but prior. But you know, I really want to get into, you know, the measurement side of things. And you know, I'm sure you want to talk about that, but also, understanding the technology behind it because it's it's fairly complex, but might be a bit controversial because samba TV has rebranded.

00:27:06:04 - 00:27:22:23

I'm not sure if you know that. Brian Rio, we dropped the TV at CES. So we have something where samba and you know, and this is that. And. Yeah, and I'll tell you why. So it's samba like had a like edit that out in post-production because you might you might see some scrutiny from the PR and comms team.

00:27:23:01 - 00:27:46:07

We'll see that. Yeah. Yeah. No, I think it's perfect. It's a public knowledge. But. Yeah, but but but you know, I've been wrong before, so, so I find that so historically you're right. Right. So, you know, samba basically is, used to be television data and measurement company specifically, you know, working on content. Automated content recognition technology.

00:27:46:09 - 00:28:14:05

But since then, we have acquired, a company called DiMarzio, which is you probably familiar with it. Right. So Casper's business, which was based pure conceptual. So what we have done is mapped, TV, let's say, attention and the viewership signal and then intentionality of the web. So, you know, 2.5 billion URLs, you crawl that you understand context content, but semantic meaning, classification, pure NLP.

00:28:14:11 - 00:28:35:06

And for the sprinkle of NLU, of understanding how you derive that metadata. And then you map it together for our ontology graph, which is a knowledge graph. So you can connect down to show level, content level, time spent. And are you licensing. So are you licensing this to the manufacturers UMG licensing this to the CTV companies. Because there's so you.

00:28:35:06 - 00:28:57:19

So my understanding is like reviewing the content taking snapshots and trying to like providing a signals right. Which you turn into that ontological graph. So like how does the business model work. Yes. That's a so the data is coming from 25 OEMs okay. And that's a global data. This is one of our major major USBs. So for example in Germany Philips is still very predominant TV player okay.

00:28:57:22 - 00:29:27:09

And we have Sony's TCL's handsets of the world where, you know, it's fairly, representative long tail of OEMs. And we love that love that for a reason. Because geographically, it's like graphically income level distribution of who buys their TVs gives us representativeness, across geographies. So that's very important diversification aspect on, who which households and with properties of this household own those TVs and network what price point.

00:29:27:10 - 00:29:46:04

Right. So you have the represented list. So we collect that data on the chipset level. Right. So that's how technology works. You have your, you know, visual and audio fingerprint. You know, couple couple sync bits per second. In fact, you collect the data, and then more importantly, you map it against a large content library, which you have.

00:29:46:08 - 00:30:09:23

Right? So you can you can get what program or ad was on the screen when it aired, which household saw it, for example. And then it gives you that level of, you know, a she has very powerful because it gives you that neutrality. Right. And, also gives you a holistic gallery, linear cable streaming gaming. And you're capturing at a device ID level, right?

00:30:09:23 - 00:30:34:13

You're capturing these signals. And then I'm assuming you, you, you probably anonymize it to a certain extent. Right. Put it into these models. But then you can drill down to see which content was viewed at a, at a household level. Exactly. Yes. And then you have, you know, we have identity graph, which we have acquired, the Dutch businesses, forensics, which gives us kind of identity resolution, gives us map and crosswalks between, you know, any identifier you can think of and that becomes.

00:30:34:13 - 00:30:54:04

Yeah. And that's where you would map across channels once people go off the television glass to mobile to desktop to laptop, etc.. That's right. And gives you like household, you know, graph understanding of who is viewing what at what time, and also ability to then do attribution against that. So, so so I got a question. You just had a curiosity ACR.

00:30:54:04 - 00:31:16:17

Is that actually what is the actual hardware behind ECR? So do you think of it as a as a little program running on the chipset level. Yeah. Within, you know, which is deployed and then firmware into your TV set. So you basically when you every first time you start a TV, you have to consent to it saying, you know, I consent on Sony, for example.

00:31:16:17 - 00:31:37:16

One, no TVs, you consent to be, you know, to send this data for HDR purposes. And it's installed on the hardware itself. It's sort of hardware itself. It can be rewired with the updates because, you know, you have like, I can think of it as an OS for TV, right? What you do and, and and you can kind of reload it and understand how you capture what you capture.

00:31:37:18 - 00:32:06:05

But that requires that relationship with the OEMs where you're actually at the manufacturing plant when they're putting shift 138 into, you know, that like that's actually where it's happening at that. Right? That's why CSE is like, we've done CSE is our not just tentpole event. This is where we've started the that's the event for you. Yeah. This is where the TV's manufacturers were coming in before there was smart TVs with some tickers at the bottom saying that, you know, like, this is the first generation of apps we know.

00:32:06:07 - 00:32:30:22

And that was that when Ashwin and and executive two, you actually start doing those deals and start collecting, you know, OEM relationships, which became fairly large, you know, footprint for, for samba globally. So yeah, 50 million is is there a modernization for him and how are you paying what's the compensation for for the TV manufacturers, the OEMs.

00:32:30:22 - 00:32:54:16

So there's different different deals with different manufacturers. The idea is to and all those different restrictions, Brad, like for example, Netflix blocks, you know, not just ads, but so yeah, every, every. Yeah, everybody. So that there's like there's this forward restrictions on what content can they recognize what's copyrighted what's not. So there's like you know as you can only imagine the fragmentation of that relationship is is a nightmare.

00:32:54:16 - 00:33:17:22

So you have you know you have. But there's also little workarounds. For example, if you Brad, I do sometimes a plug in to my is Yamaha to my TV and use it as a screen. Well now it's not a TV anymore. So if I watch Netflix on my laptop and screen it. Yep. Seems be the source of of the canonical device.

00:33:17:22 - 00:33:37:14

Is your laptop now? Correct. So like, you know, you know, the actual fingerprinting of the TV app itself, you just stream it as a source is a projector, etc.. Right? So you have all different scenarios, fire sticks, etc. on how content is, you know, can be consumed on the, on the screen and then all the, you know, legalities around that.

00:33:37:16 - 00:33:54:00

And you have, you know, you should have you pay the OEM, send it to for to be installed. Right. And, you know, and, our viewers may not know this, but like, you know, the prices of hardware just gone down so much the last ten, 15 years. A big reason for that is that the OEMs are able to make the to make money because of these types of deals, right, where they're actually sharing.

00:33:54:00 - 00:34:17:19

Yeah. I'm assuming this is, that's that's a good description of it. In fact, I believe in some instances hard ways. Negative margin negative you lose. Yeah. You lose money on TVs. So they obviously supplement for income is to have this type of relationships. So that's how you can buy like a 72 inch flat screen for like 500 bucks at Sam's Club and see why you can do that because of this.

00:34:17:19 - 00:34:39:00

Right. And the reason you remember like this business is, is it telling you I think maybe I'm. I'm misquoting. Yeah. Who giving a hardware for free. Yeah. But then there's, there's monetization, like, so that's not far from reality because TV, you know, is there, is there anything thin margin, single margin, single digit business. So so they the so this is a symbiotic and very healthy relationship.

00:34:39:00 - 00:34:56:10

And then brought to your question like what do you do with the data after that. You know, obviously there's a plethora of use cases on how that data can be used depending on who you talking to. Obviously, as you understand, like any of every ad which that aired, you know, we have we have we have viewership of that data.

00:34:56:12 - 00:35:27:11

And so it can be used, be used for the, for conquest. It can be used for business intelligence, for market channel. So there like this utility even outside of targeting. So planning discovery, you know, is just the beginning of the game. We have companies work with us purely for analytical use cases. So for example, companies who look at this data, what was the last show you watched on Netflix before you moved to Amazon Prime to start watching X, Y, and Z and then so churn analysis?

00:35:27:13 - 00:35:48:06

Yeah. For example, you know, and that becomes a very large business to go back to sports to basically to build more sophisticated models on what people are watching. Why this changing? Why the shifting, fascinating, really fascinating utility of what you can't think of that. It's it's not some people say ICR just, you know, targeting Desperate Housewives on, you know, on that stuff.

00:35:48:06 - 00:36:07:22

Yeah. Yeah. Maybe this is for customer growth. Customer retention. Right. New a new customer comes in to a new platform like like Prime. And you want to show them content recommendations that are relevant to them. And you're pulling that from their past behavior on a different platform, possibly on a different device, which is pretty powerful. That's right, that's right.

00:36:07:23 - 00:36:25:07

Yeah. And so do you think you mentioned tele, which their tagline is great. It's the biggest thing to happen since color TV. That's a pretty bold statement. Do you think tele has that? I've talked to a few of the folks over there. Well, they have a waiting list for their devices, apparently. Like, people really want them, so.

00:36:25:08 - 00:36:48:08

Yeah. Yeah. Brett. Yeah. Do you think, do you think that there's a future in that? And it's in like the vision that I see it is, is it's basically like your your iPhone. They want to make it this sort of, device that's central to your life that's a lot smarter than what televisions have really ever been, you know, so you can do it's kind of like your mobile phone is turned into really a handheld computer, right?

00:36:48:10 - 00:37:04:05

I'm torn, but I'm to. I'm not sure. Bread like, you know, I think it's a consumer choice, right? You know, some, you know, low income families might find it more attractive because it's a free hardware. And, you know, it gives you the basics of what you want to watch. But then it comes with, you know, comes with that.

00:37:04:05 - 00:37:23:14

It comes with. Yeah. And the ad model I found a little weird because it sounds like there's some almost like some built in ad redundancy where it's like you get ads on the, the actual physical device and ads within the, you know, the streaming services that you subscribe to. If you, if you or if you, if you're doing fast type of channels.

00:37:23:17 - 00:37:41:18

So I'm like I'm like so you're actually kind of are you doubling your ad load? I mean, as a consumer it doesn't seem that attractive, if that for me personally, as a consumer, I think that's not you know, it's not experience I would like to have in my in my living room. Right. There's also, maybe a speaking completely, wrongly here.

00:37:41:20 - 00:37:57:07

Like, you can't cover the panel, I think because there's a camera detection or something. There's some sensor. Right. You know, so, like, you know, there's this, that. I don't know how privacy is private. You know, there's just apparently if you if you, well, can see if you're sitting down to watch. I mean, apparently there are some sensors.

00:37:57:07 - 00:38:16:19

I don't know how privacy say. Oh, boy, oh, boy. Apparently it's. Yeah. It's been intrusive. I I'd probable enough with the ring. You know, I was about to say I have enough problems with my Roomba by vacuuming my, my my floor, you know, like, I want a good television is watching. Yeah, yeah. We're already have problem with that with with the devices.

00:38:16:21 - 00:38:34:21

But but that's one thing that samba TV can't do because it's speaking of watching, unlike the sort of Nielsen viewer. And if people don't know, you know, Nielsen, television, you know, it's kind of the old Simpsons episode, right? You get sent, controller that literally has buttons on it. At least this is how it was when I was there.

00:38:35:02 - 00:38:52:10

And the buttons are like person A, person B, person C, person D, c identify yourself as you start to flip through content. So the I don't think it's changed very much. I mean they're building a panel. It's not a big panel. They you know, they just so they can tell who's watching you. You would have to probably back into that data I'm assuming.

00:38:52:12 - 00:39:27:06

So we don't use panel for that. So, you know, we don't need to have a kind of a human input. So that's just different. Different business model. Our strategy was, Brad, is to have, you know, representativeness, by just having a 25 type of global deals with OEMs, you have to just have enough density for, for, for, let's say, local affiliate network to say in that particular town, we have this much television hybrid 50 TVs, which are not noise, which something that pubs are not the gyms which are actually in the households.

00:39:27:06 - 00:39:53:11

So removing the noise, right. To be sure. Okay, we have enough representativeness to say that we have enough viewership signal to support zines. A use case that always the case that was always this support investment because you know that you're going to get. That's right. The audience if someone is buying on that, you're on that DMA on that zip code like that local specifically like you have representative data to do both measurement and and and to derive inside of that.

00:39:53:11 - 00:40:17:16

So that was really, kind of just the model number has, has built and it kind of played in our favor versus where you have maybe more high end TVs from Samsung or LG, which are more media businesses, versus samba, where we don't touch media. We we are agnostic in that sense, in representative. So I like that angle.

00:40:17:18 - 00:40:40:15

You know, you know, as I was thinking, to really think about that in person, like there's just so many smoke and mirrors and I understand you guys know where I've been. This is not your first rodeo. So I'm like, give me a substance. Give me consented data, which is unique and which has utility and has, you know, in somewhat future proofed, you know, there's obviously legislation and all the Vinales which is flying around.

00:40:40:15 - 00:40:56:12

But, you know, that was kind of how can I make the best bet possible? And I was like, that's sound like a good bet and a good team. So, you know, and and futureproof just you know, because it's in the hardware. It's not an IP address which is not future proofed regardless of what people want to tell you.

00:40:56:14 - 00:41:15:16

It's not you know, even email is technically not, future proofed, but and you have the relationships, you're in the hardware and you have the relationships with the OEM. So I think that that's very important. And also, you know, like talk of future proof, like TV, like, you know, I, I was thinking read the other day, it's projected overall projected to grow 16, 17% over the next couple of years, which is pretty significant.

00:41:15:16 - 00:41:35:06

Right. See TV right. All TV oh, obviously linear is declining, but CTV, the growth in CTV is making up for it. So it's a good industry to be in. And you know, like Amazon slogan is, you know, your margins. My opportunity for sambar. If I to rephrase that, I'm just thinking on the fly fragmentation is an opportunity.

00:41:35:08 - 00:41:57:06

Like really it's if you look in in how how the content is consumed in the, in the, in the living room. That's what's, that's what sambar solves for. Right. So cross-platform measurement, you know how many unique people did I reach across all TVs. And I think this is what we solve for, you know, at least like two breaths point.

00:41:57:06 - 00:42:23:03

You know, measurement is fragmented. You have live TV panels, which we spoke about in a platform specific streaming data. Digital ad measurement is different. So industry still needs a unified currency layer, right? Oh. You brought up that word, the currency. Let's see. I love the dangerous one. Yeah. Okay. And by the before we go on I say correct is that CTV is growing at around 16, 17%.

00:42:23:03 - 00:42:46:16

And then like linear is declining by around 7%. But overall streaming is about 45% of total television consumption with linear TV about 44%. Yeah, yeah. Linear is declining. Yeah. It's grown at a much larger rate than any media channel. Right. Which is that 1,718% level. So let me ask you this. When it comes to viewership and measurement, right.

00:42:46:16 - 00:43:22:03

Because you guys have this deterministic sort of hardware specific user data that's built into huge, a huge volume of televisions globally. Are you able to, then definitively break apart, the stuff that people are claiming is CTV, right. Really bifurcate, other media that might be called CTV or streaming, streaming being, you know, content that's being consumed on other devices that's not actually being consumed on the on the television screen because there's a lot of actors out there faking CTV audiences, which are actually not being consumed on the television class.

00:43:22:03 - 00:43:49:23

They're being consumed on, on, on, you know, laptops and mobile devices. Right. So you guys, I'm assuming, have have the ability to sort of help, you know, separate the wheat from the chaff in that respect. You're right. And like by definition, this is what occurs. Right? We observe everything on the screen. Linear broadcast, cable streaming apps, even gaming, fast channels or RTE advertising.

00:43:50:01 - 00:44:16:10

So you have all that signal consumed in real time. So you really have that true cross-platform, visibility, which is important. So if you're talking about breadth, measurement, can we one of our biggest products obviously on the measurement is through rich and frequency cross-platform. Right. So also can you solve for incrementality across linear versus, you know, digital problematic.

00:44:16:10 - 00:44:35:13

So we have partners who use that just for that. So that's why when I started with definition of soundbar, although we drop the TV and we have all the different data sets and all map together, it, you know, in our heart we still measurement and data company and always has been. And I like the neutrality aspect of that.

00:44:35:15 - 00:44:56:10

So we don't claim, you know, we we remain agnostic. And that's was always our thesis and how we can, you know, how can we evolve. And by position of CMOs, you're kind of fuzing like what other signal can refuse in into this ontology graph? You know, you're watching Desperate Housewives and then you're doing research on, I don't know, on you become travel content.

00:44:56:10 - 00:45:20:07

At the same time, you have very interesting mix of your intentionality. This is, by the way, what verve what kept you fi in exactly for that, for that data. So we have that contextual understanding and meaning of what you are reading, you know, what websites are you visiting? What is what the sequential in storytelling there is, and then what are you watching at the same time within that household.

00:45:20:07 - 00:45:38:06

And the graph to map to an identity level. So you have that level of understanding. And then from there you can, you know, start built into outcomes. You can start doing measurement, you know, and does that identity graph does that, what's the scale and the scale and scope of that. And and is that multinational like you're like your television on a m footprint.

00:45:38:08 - 00:46:01:17

So yeah. Just how extrapolated is it or is it a data set. That's pretty pretty gigantic. It's, I believe it's 50 million TVs in that us. Okay. I probably should have come prepared. Yeah, but big shot, was it that graph that gives you a seed audience to be able to, you know, so this is, you know, this is this is a TV.

00:46:01:17 - 00:46:19:09

This is the households we have. So like, this is not extrapolated number. Right. So yeah. And then you have 2.5 billion URLs which was gap. Right. Oh yeah. There's lot that and there's like a 1 million, a billion of maids and like you know all I do you think and that's the 50 million is the actual.

00:46:19:09 - 00:46:43:14

Oh yeah. Yeah, yeah. Poems which are filtered out from, you know and there's a. Yeah. Or you compare that to Nielsen. Right. Those numbers. Right. You figure like what's Nielsen 42,000 in the U.S.. Which sources are on 100,000 for 40,000 households or 100,000 people overall. Right. So I think you compare it, that's a that's a sizable that's a sizable identity graph.

00:46:43:16 - 00:47:00:22

So. So, yeah, it's been, you know, fascinating, talking to you and seeing this sort of trajectory all the way through Saba TV and talking about some of the kind of hard problems, you know, that you guys are solving for, in a pretty complex space that's got a lot of, you know, detail on, like, how this whole thing works.

00:47:00:22 - 00:47:24:08

Right? I think a lot of people don't really understand that. So it was good to know. Yeah. I mean, you know, ECR, I wanted to know exactly how that was implemented into the, the, the machines themselves, the hardware. Yeah. And that was fascinating. So yes, it's awesome. And as you've walked us through your career, and what do you think is the hardest part about building a career in ad tech today?

00:47:24:10 - 00:47:47:23

I think you've been out with a change. The Law Society is the technology, you know, just going way too fast, and consumer behavior specifically pushing that change. So if you're a learner and if you perseverance your butcher and you really, you know, for a challenge, I think you should have a breeze. But if you are not, then that's so that's the sentence Spurs could say, yeah, yeah.

00:47:48:04 - 00:48:08:20

The days of hiding in a cubicle and pretending that you're working for a large company are kind of, those are over, but you sort of have to. I think your point earlier about being a builder is pretty important, because you just don't you can't just be safe in a, in a structured sort of environment system like you could in the past because it's so rapidly being disrupted.

00:48:08:20 - 00:48:27:02

And yeah, you better get comfortable tech. I mean, I think that's for sure, regardless what industry. But I think especially in ours, it's so tech driven. Yeah. What's one company or technology in media that you think's massively underrated? Maybe flying a little bit under the radar that you want to call out?

00:48:27:04 - 00:48:50:08

Well, then I would bet against Jeff Graham. So there's a lot of shift and Jeff now. But I have deep respect for what he has been building. So I would bet on trades as I'm going to short it for now. But that's my answer is short it for now with the publicist battles. Yeah. The the and I've heard that before that that just as a, as a leader in a and somebody that's able to pivot and adapt and change and adjust.

00:48:50:09 - 00:49:05:21

Yeah. That's a I think that's a lot of battles with a coach. I'm scratching my head over that. They built their entire business like really bring out the it's easy to work with hard codes. When you look at the, you know the the UI they pushed out. No one liked it. So I don't really understand it, but I think you're right.

00:49:05:21 - 00:49:28:08

He's he's a good leader, so I wouldn't I probably would be foolish to bet against him too. Yeah. And there is this whole sort of, it's a battle of transparency, you know, with the, the because not having the level of transparency, but you could argue that that from a principle or principle based media, Brett. I mean, it's like I mean, I don't think anyone thinks it's great, but like it when clients buy just based on CPM rates at pubs and it's just race to the bottom.

00:49:28:08 - 00:49:58:20

I mean, I think you could argue from the whole perspective is increasingly hard to hard to make money without it. So I, it's I don't yeah. I think again there like really some big, big, big exposé next week about that. So I'm curious to see how that goes. Yeah. Yeah. It's just once you start to dig beneath the surface of programmatic media, as we've, as we've explored a ton in this podcast with Doctor Fu and folks like that, you start to realize that transparency may not be the leg you want to stand on, considering how much dirty, bad data there is.

00:49:58:20 - 00:50:20:18

Speaking of what we talked about with, but you call it the dark underbelly of the dark underbelly of of the of the data targeting ecosystem. My father, we were just making fun of, of sort of, sort of, older parents and their technology challenges. But he, he said for years that I'm in the surveillance marketing business, he has marathons like, he has merit, you know.

00:50:20:20 - 00:50:45:01

Absolutely. And brought to your point, like, you know, the even basic transparent to an auction level like that, the premise of programmatic, like, you know, it would stuff there, you know. So, yeah, let's talk about rebates later. Let's talk about the digital launch of the supply path rollout. Yeah, yeah. Let's just start with the auction. Yeah. What do you think is being, sort of overhyped?

00:50:45:03 - 00:50:59:07

You know, we can all say I, but I'm not sure that's overhyped. Right. If you had, like, an over under bet here, I would be like, I think that's actually probably not being sufficiently hyped even though it is being hyped. What do you think the most overhyped thing in the industry that you're seeing right now?

00:50:59:07 - 00:51:23:10

MarTech ad tech. It's a good one. You know, I wouldn't say I, but I think I agents doing everything is overhyped. I think it will happen. And the timeline for that, you know, based on some estimation, is that 18 months from now, but, you know, that's I guess, high versus reality. It has a timeline. And also the other thing is automation is better via UX, right?

00:51:23:10 - 00:51:49:13

So what is true Atlantic versus what is true, as a UI user experience in the, in the UI itself, because a lot of AI workflows, automations we have seen, which I think is overhyped for sure is Eric created similar experiences, but just with agents. But what's the difference in going to Booking.com, for example, in those fields versus telling the same fields to your agent to book that via the Booking.com?

00:51:49:13 - 00:51:55:08

So I think that dichotomy is definitely overhyped.

00:51:55:10 - 00:52:13:19

Yeah, that's that's interesting. Like what would be your vice to someone who's just like getting out of B-School or just starting a career who wants a career in in advertising and, you know, what would you like? Where like what were your vices like where like what they should focus on, where they should start? Is there type of company, a type of technology, like where would be a good place for them to dig in?

00:52:13:21 - 00:52:33:17

You know, I also if I would dig myself and vice on the same thing, where would I start my career? I think the answer would be the same. I would start it off with data infrastructure and measurement somehow. Still has to measure your homework. And if you have independent measurement or you understand data infrastructure and let's call it cloud infrastructure, I think you have.

00:52:33:17 - 00:52:53:05

So okay, go back to your not name the first word in your forecast. That's where I would go sigma and maybe add trust to it. So yeah so so like if you're in college of it I've got a I've got a son at Syracuse right now and he's, he's in the media space and you know, should I push him towards things like econometrics.

00:52:53:07 - 00:53:16:13

Right. Understand the fundamentals of data and data statistics and data analysis and, and how this stuff is, is sort of integrated into decisioning, right. Which whether it's happening in AI or in a data warehouse or, or in a, professor's, spreadsheet. Right. Do you think those types of areas are kind of important for understanding how data works?

00:53:16:13 - 00:53:40:17

And I would say, Brett, you know, maybe I'm biased because this is kind of my upbringing, my background, my father, but said, you have to know mathematics and do applied mathematics, applied meaning you can apply to anything biochemistry, to epigenetics, to advertising and future marketing. Yeah. Like it's universal language. Look what we see about embeddings, about future, about LMS, how they work.

00:53:40:21 - 00:54:08:05

It's all math. So if you understand that, you might have merit. You know we talked about automation part. Do you need to understand in the future to move away from AGI to as guys superintelligence. And do you have merit in that or will it be 1% of population who needs to really control that narrative? I don't know, but I think you have a good chance and better bet if you do know versus not knowing that, help me.

00:54:08:05 - 00:54:33:08

You know, all my career was kind of based on that from, you know, doing sales, doing analytics, doing whatever, you know, anything in the day to end. That's enough with innovative spreadsheet. You know, I've got people that excel at if you understand that you have a problem. Yeah. Yeah. I think in order to disrupt or to deconstruct you really and you really need to understand how things are built from the ground up.

00:54:33:09 - 00:54:59:12

And if they're built on mathematical principles or technical principles. A lot of the people that have succeeded in our industry, have had have been technical people, that then build out some of the commercial knowledge and experience. It's a classic CEO role. I was on product and now I'm in sales. If you can play both of those worlds and bridge those worlds, I think you're you're advantaged by definition, and you've certainly done that in your career.

00:54:59:16 - 00:55:20:09

It helped me tremendously. It helped me tremendously moving from product to operations and then just finishing. Now with the commercial, you know, when you when you understand things, when you can talk to it in simple language, you just call a fancy Excel and you don't need to read slides. You just explain how it works. And you know, you, you know, you become natural, authentic, Excel.

00:55:20:09 - 00:55:57:04

And I think that's was my journey. It helped me tremendously to point out on the Senate technology and kind of using that as a spy and and then dress it up nicely with, with cool slides, which can be objective generated. The your differentiation is not the presentation layer but but understand but also I was thinking about that something I would love to learn morph and kind of you know practice is one thing which I think will truly differentiate great from good in the future is ability to articulate succinctly anything.

00:55:57:06 - 00:56:16:04

And I think that that's a human element. Right. So McCann's Kansas style speech, when you come in and you really can capture the audience with your narrative or your storytelling, and you can group them with that attention, that skill will be universal and I think will be more prominent than anything else. So this is something I'm working on now.

00:56:16:04 - 00:56:35:13

And, and this is not the ad for McKinsey training by now. It's funny you say that because that's come up a few of these other podcasts of the leaders who said that, like gets if anything may be more important now. Right. Because, you know, you can use AI to crank out code and it just turn it. A lot of you may be content.

00:56:35:13 - 00:56:54:01

That's okay. Right. But being able to understand what it means to be able to write could be able to take what the AI gives you and and communicate that in a great way. And also to your point, be able to talk to technical people as well as business people, be able to bridge that gap. I mean, I think that that's incredibly important skill that not many people have agreed.

00:56:54:05 - 00:57:15:16

Definitely super power. Well, yeah. But it's been phenomenal talking to you. I wish we could go all day on this, on these topics. Yeah. So so we always ask, how can people reach you? Yeah. They want to get Ahold of you. Like, what's the best way I as a yeah, the best way. Social media I think link to like I'm not omnichannel.

00:57:15:16 - 00:57:40:17

You know, it's probably by like you is he'll link to this by is by poison. And, you know, I'm always, always open to ideas to, you know, to collaborate with people. So please do reach out. Always reply so. And thank you, Brad and Rio. I was absolutely amazing talking to you. A very engaging conversation. Both of us on Friday when we when we're all running on fumes after a busy week.

00:57:40:17 - 00:57:59:04

But but everybody, thanks for making it this far in the in the podcast. If you've made it this far, signal and noise, you can find us on YouTube. Amazon, not Amazon. We're going to be on Amazon soon though. Rio and I've talked about that. But Apple YouTube Spotify, Apple. Yeah. Subscribe if you haven't. Yeah. And subscribe.

00:57:59:04 - 00:58:19:23

So they download the app. Yeah. And we will see you next time. And thanks again. Yeah. Thanks. You have been a pleasure. Be here