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- [00:00]
A
This is adtech God and I command you to listen to this house ad. So if you're listening to this show, just know that you've really stumbled upon a giant network of content across advertising, marketing, media, publishing, and of course, the people that work in this great advertising industry. So go to market, check out all of our brands. We have multitude of shows from the Brand Forum, the Advertising Forum, the Monopoly Report, the Ad Tech God Pod, the Market and more. We are bringing more podcasts to our network. We are consistently and constantly bringing on new shows. So check it out, market or search for any of those brands in the app that you use to listen to this podcast. Enjoy the show and see you all soon. Welcome to the AdTech Godpod, your window into the world of advertising technology and the people behind it. I'm your host, Ad Tech God. Welcome to the EdTech Godpod. I am bringing back breaking news episodes. I announced it yesterday. Today, Vayant announced their acquisition. So before I get started, I just wanted to cover a few housekeeping items. We are available and active at possible and can. Coming up this year, if your companies are looking to activate with content events one to one podcast with Ari Papero, please reach out to us. You can go to market. Click on the event section to learn more. So today's news, basically everyone is familiar with Vayant. Everyone's familiar with Tim Vanderhook, Chris Vanderhoek, I'm familiar with him. I'm also familiar with T Vision. But for anyone that is not familiar with T Vision, they specialize in capturing second by second eye on screen, attention across both linear and streaming. This type of visibility is really important, especially with brands and advertisers looking to go beyond just an impression base. But really who saw their ad. So I've invited both Tim, the CEO of Vayant, as well as Yang Liu, the co founder and CEO of T Vision, to join me today. Just hoping to dig in a little bit more and understand what we're building here at Viant. So, gentlemen, thank you for joining me on the pod.
- [02:11]
B
Thanks for having us.
- [02:12]
C
Thank you for having us.
- [02:13]
A
Yeah, thank you, Tim. I think this is your second or third time, so thanks for joining me again. Yeah, you're like a staple.
- [02:19]
B
Absolutely. It's like going to church.
- [02:21]
A
It's like going to church. We're going to use that hashtag on this post. Jan, great to meet you and congratulations. That was huge news today. Love to hear it. I'd love to hear from your perspective. What is T Vision? Why'd you build it? And what are you doing that's different in the market?
- [02:35]
C
Great, thank you. Thank you for having us. So T vision, we really started 11 years ago. Before that, you know, early on I was a consultant at McKinsey. Pretty boring job. Then one day I thought, okay, I can actually do better than my client by starting women's fashion brand. That's my first kind of experience in the startup. That didn't go well at all actually. You know, like McKinsey, guys wearing suits try to design women's underwear. Not the best business idea in the world. So we pivot into ad agency because, you know, we spent a lot of money on marketing by selling those items, the fashion item online. So I thought maybe at least I can pretend I'm an agency person and help brands to basically manage their media and creative. So I did that for a couple more years and through that experience I started to understand, especially for tv at that point, the measurement had like a big, big issue. Everything's slow, it's so expensive and the legacy providers, they're just not like tricking the small agency like us in a fair way. So I thought, okay, the measurement is such a big space, it's so important for the entire ecosystem. Why then, right, if I created a better measurement company, there must be a market opportunity here. After that I came to states, I went to mit, I met some great engineers, told me, oh, actually there is a technology you can do much better job and we can do this all together. That that's really how we got started 11 years ago.
- [04:29]
A
Yeah, I'd love to hear what is it that you guys do? Because I know I'm familiar a little bit with T vision and I understand that the, the core high level messaging of the company. What do you do today with streamers and linear and what is the product itself that is so attractive to vayant to acqu?
- [04:47]
C
Fundamentally, what we try to understand is the true attention viewership of the true human. Because if you think about entire marketing industry, ultimately our job is to get human eyeballs, right? That's why we're spending money in this entire ecosystem. However, for a very long time, people been focusing too much. Understanding impression ratings, grp, that's the proxy of human attention. I mean it is important. But if you can actually measure attention, you should just measure attention, right? But understand, right, maybe long time ago the technology was not there to measure attention, but we developed the best passive attention measurement able to measure everything in real time, second by second, person by person. Then people can use that information to make much better Decision on media buying. Either you want to sell media, buy media, optimize media. This can be the best information. But we are still a measurement data company. So by joining team's team, right, this makes sense because team has the best media activation platform. So we can use our data to activate media. Then that'll bring quantum value to brands.
- [06:13]
A
Tim, I wanted to ask you, and sorry for having you sitting there silent for a couple of minutes. I wanted to get a better understanding of what T Vision does over the last maybe year or so. You've had iris, you've had identity, you have contextual. You're now getting into the measurement game and what that means for the overall company. What's the strategy here for Vayant? How is this unique to market and what are you building at Vayantha?
- [06:35]
B
Yeah, you know, what attracted us to yawn and T Vision is just the data signals that they provide. So starting at a high level, they're a US TV panel that tracks persons within the actual household. And just to give the viewers a sense of what it is, there's a camera on top of the television in every panel's house. On their primary tv. They fill out. It's all opt in. They fill out a whole profile of everyone in the house. You upload photos. And what is that camera doing? It's doing facial recognition to recognize Tim versus my wife Laura versus my four children as well. And there's a box where there's ACR running. So we know what's on the television screen and there's really three critical signals. We wanted to move past delivered impressions because we all know it's broken and can be rigged and marketers have been being taken advantage of. So there's three critical signals that T Vision provides advertisers and content owners today. So what are those? It's number one presence in room is anyone in the room when the TV's on and it's playing and you'll find 20 to 30% of the ads delivered, there's no one in the room. So if no one's in the room, it can provide no value and shouldn't be on the measurement side attributable for a sale. So presence in room is really critical. But not just that. How many people are in the room? Co viewing? Most people are familiar with Nielsen who does co viewing. You know, there might be 2.1 on average watching this, this television show. But Jan's technology also provides vyant co viewing not just how many people are in the room, but specifically who is it Is it mom, is it dad, is it the kids? Or is it that golden impression where it's family movie night and all four or five people in the family are actually watching that movie on Disney plus or Hulu or whatever it may be. So you have that. And then the final piece, which is really this critical that Jan touched on, which is attention. The camera that sits above the TV is tracking the eyeballs of everybody in the room. And I've tested this out tremendously. I have the box, I have the camera, my family room. I have a fireplace below my TV and I stare at the fireplace and it's able to detect that I'm not looking at the screen. But the biggest distraction for everybody when they're on the couch is the mobile phone. I'm. Sometimes my TV is on and I'm paying no attention to the show that's running, could be a game and it's a blowout and there's no point to watch anymore. So I have it on in the background, but I'm scrolling through, browsing products, doing searches, social media, whatever it may be. So these signals of presence in room co viewing, who's in front of the TV and are they paying attention, those are critical when it comes to media planning, buying and optimization. And that's really why it's a match made in heaven. And the final piece, I just want to say, like, if you ask a marketer today, they have investments in a couple of buckets, linear TV, programmatic, and then of course, walled gardens, YouTube, prime video, et cetera. The problem is the Walled Gardens measure themselves and they provide a report that says they reached everyone and they drove all the sales. And we all know it's not true, but they have such leverage in the marketplace, advertisers are kind of stuck believing that Programmatic probably does a better job at telling the truth, but we're up against walled gardens. And then there's poor linear TV, which is measured in GRPs and still on Nielsen. And what T Vision provides is all of those buckets of investment for advertisers, a unified measurement dashboard where we can see duplicated, reach, unduplicated reach attention across the way, co viewing across it all. And then now they're able to actually optimize the entirety of the television budget. So it's not just signals, it's also the measurement in a unified way that really just doesn't exist today. And that's why we, as soon as we recognize the value that T Vision had, we approached John first for partnership and then of course Quickly moved to we wanted this for ourselves to be able to go out for differentiation in the market.
- [10:57]
A
Love it. I want to ask you, Tim, it seems like you're kind of addressing three or four different things in all your recent acquisitions. So you're addressing the who with locker, you're addressing the content or the what with Iris. And now you're kind of hitting the truth. And the attention piece of this is more than just an impression being served. I know who's sitting in this room. I'm able to confirm it. Your dollars are actually being delivered to a human and they're seeing this ad. With that comes a little bit of positioning in your press release where you talked about being unbiased and a market wide view. How do you maintain that independence? That I think is the biggest piece of it to your advertisers that the measurement that's enabled in the buying platform is going to be the, the moment of truth or the dashboard of truth for all of their campaign delivery and measurement.
- [11:41]
B
Yeah, I mean it's a great question and one everybody should ask is where is the bias? We're only on the buy side. We only make money from advertisers and we want to tell them the way we get paid even in the DSP today is what's providing the best value. I don't care if the money goes to Fox or to Major League Baseball directly or to Hulu or to ESPN or to Param. We have no dog in that fight. We are simply buying efficiently, the the lowest possible price we can get for them. And we allocate budgets appropriately. And now with key vision, we're able to expand that out of the programmatic slice that is the budget and now expand into all the budgets where they're allocating money. So you have linear TV, you've got programmatic, you're going to have YouTube and Prime Video. Does YouTube deserve to be on the buy? Of course. They have huge reach. Does Prime Video deserve to be on the buy? Of course. They have Thursday Night Football, they have the NBA. These are critical tent pole content events. But now with key vision, we're able to advise advertisers at a much higher level on their total investment. But still we only make money from the advertisers. We negotiate a fee on the DSP and, and for the measurement and from there let the chips fall where they may and let the sell side, whoever has the highest reach, the highest engagement with the Advertisers content, the 32nd spot, let them get the money. It's not, it doesn't really have anything to do with Viant. And so when we say we're the independent, independent arbiter of truth, you know, it's a bit of a statement out there. But what we mean is we don't own content. And all the money that comes to Vyant is being pushed to the sell side. When you have to rely on a sell side provider's report, we all know what that looks like. They drove all the sales, they provided the most value. Give me all your budget. And we know all these, these providers are providing value in some way. Now we have a qualitative and quantitative way to calculate what that return is for advertisers. And that's what we mean by we're independent and we're objective.
- [13:54]
A
Thank you. Thank you for answering that. Jan. I wanted to ask you, and I'm digging in a little bit just because I want to get a good understanding because I do feel this was a big announcement this morning when we talk about this, would this be more of a panel based approach of how you're collecting this information? Are you able to disclose how many people are on this panel and what does that really mean for kind of like the granular attention and attention data that you collect and how you can apply that across scale and larger user bases?
- [14:23]
C
So today we have roughly 5,000 homes panel which translate into 14,000 people across the United States, 35 DMAs. It's nationally representative panel and within this panel we understand every single panelist, we understand the demo information and we track them 24,7 across all media. The way it works is it's fully opt in panel so there's no privacy risk. We only process image or video on the local device, so we're not uploading anything to the cloud. That's also very important. And everything is passive, which means there's no survey, there's no phone call, there's no pushing the button. We collect all the data in the background. That's how we get the most high quality, authentic and also panelist friendly data at scale. And we are by far the biggest attention data provider in the marketplace.
- [15:24]
A
Jan, Tim, either either one of you, but maybe, maybe Tim, you can, you can help me a little bit more on this one. When, when we talk about high attention, low attention, how, how does that translate into CPMs for your buyers? Will there be like adjusted pricing for them based off of very high attention impressions versus low attention impressions? Is that a pricing model that you're bringing to market or will it be more of a, a mixed batch of inventory that you can offer.
- [15:49]
B
Yeah. And it's, it also lends to the integration a little bit, which I'll talk about, but absolutely. We in the press attention adjusted CPMs. Right now you have bid shading, which is really just trying to get the lowest price possible while maintaining pacing and delivery of the budget. But now with all of these signals coming in, we can recognize higher value and lower value. If there's two or three people in the family room that are in the target audience, we know we can raise our bid if they're paying attention to the screen. And conversely, if we know it's the wrong audience watching this show, we're going to lower the bids or not bid. So attention adjusted CPMs, what are we moving from? It's a bit of a bridge. We pay on delivered impressions today. What the industry needs to move to is seconds of attention. That's what a brand needs to drive recall. 1% increase in attention leads to 1% increase in recall. It's pretty simple when you look at all of the research that's out there and what is a marketer looking for? Recall is that initial metric which then leads to more sales. So for us, how do we bridge T vision measurement in homes using a panel to live bidding in a dsp? Iris was the key to success there. When you think of Iris, it's a content id, it's a number coming across. It really represents a show. Jan's panel is measuring that show second by second and in real time. So prior to bidding, Vayant will now know there are three people in the room on average watching this show. Based on the panel data, we have 85% attention on the screen and we're going to know that data before we place a bid with that content owner. So it will come to us and that's what will help make the decisioning. But any other player in the space who didn't have Iris or a content identifier T vision, it would still be hard to to move it from just measurement to activation. So Vayant plus IRIS plus T Vision, that's the bridge that we were able to lay where we're able to take his high fidelity data and bring it into the bid stream.
- [18:01]
A
Tim, just to touch up on the comment you made, how does integration look for you? What. What's the timeline to do this? Is the integration already existing? Are you going to ingrain the solution more deeply into your platform? What does that look like in the, in the near future?
- [18:15]
B
Yeah. With this acquisition, we actually integrated for targeting purposes ahead of the announcement. So T Vision is already integrated with Iris IDs. We chose not to release that product until we closed the transaction. And so advertisers today can go in and bid similar to like pre bid segments that most are familiar with on high attention, medium attention put different CPMs for them and it's paid for on a CPM usage basis. So similar to all audience segments that are out there today, the tighter integration which will be done in four to six months I would, I would estimate is that closed loop system where we know directly after the ad aired, T Vision detects it. What was the attention that we actually got on the ad? So we can do our best to predict it up front, knowing the minute, the 30 seconds ahead of time using the panel based data. But when the advertisers ran, what was the actual yielded attention which drives further downstream workflows on do we buy again? If we had 100% attention and we had a frequency of 2, we, we got 60 seconds of attention in that household, we may choose not to bid and wait 3 days, 4 days, 5 days until you start to forget as a consumer. So the tighter integration in the next four to six months will be that closed loop feedback system where we will know in real time what was the attention of that actual ad creative that was detected by the panel. So it's live today for targeting. We do have delayed measurement, but we're looking to bring both of those to a real time data set in the dsp.
- [19:54]
C
Awesome.
- [19:55]
A
Jan, what are you most excited about? You're rolling into Vayant, which is a fantastic company, been very bullish on their growth and their strategy over the last 12 to 18 months. What are you most excited about? You know, when it comes to rolling under Vayant and just the resources and the growth that you can bring to the company.
- [20:14]
C
Of course I never doubt we have the best data set in terms of the signal about the quality of the media. However. Well, we're not media company, right? I mean to learn from team how to really optimize media, how to activate media, but without really knowing that our data is always not really fully integrated into a platform. And now as part of the vyant, we can really, truly unleash the potential of the data because we can do much, much deeper integration. As Tim just mentioned then I think we can truly, really optimize the media and drive efficiency to brands which agree that that's, I mean fundamentally that's paying our entire industry and we should all aim to drive the best performance for brands and that's really get me really excited because when we started the company, the goal here is really we try to optimize the entire the supply chain of the ad ecosystem. But you know, as the data measurement company, sometimes it's a bit difficult because because those media platform are not going to tell everything about how they activate the media. But finally now we can do all together which is super exciting.
- [21:29]
A
Awesome. Jan, Tim, thank you both for joining me. I know this is quick, but I appreciate you both taking time out on such a busy day to join me today.
- [21:37]
B
Thanks a lot atg and thanks for of course, breaking news.
- [21:40]
A
I'll be watching guys. So thank you very much and looking forward to it. Thanks for tuning in to another episode of the AdTech Godpod, a podcast for the people about the people. Stay connected with me for more insights, trends and interviews in the realm of ad tech. Don't miss out on the latest updates. So follow me on X Instagram and connect with me on LinkedIn. Don't forget ATG Slack community has insights, networking opportunities and jobs. Keep the conversation going and stay at the full forefront of adtech innovation.