Viant Technology Inc. (DSP) August 2026 Conference Transcript

All right, good morning. We are going to get started. Thank you all for joining us today. I'm Maria Ripps, Internet Analyst here at Kinecord, and it's my pleasure to introduce Tim Benahook, Bion's co-founder and CEO. Tim, thank you so much for joining us today.

Thanks for having me.

So maybe to start, there's been a lot of discussion around competitive dynamics in the DSP space more broadly, and Bion appears to be taking share. What's driving this momentum, and sort of what's resonating with advertisers the most?

Yeah, Viant is taking share in the programmatic advertising space. We're really well positioned. We have an incredible amount of data. We call it our intelligence layer, and it's unique to us. So we come with an identity graph where advertisers can do sophisticated advertising campaigns. It's very unique to us. We made an acquisition of a company called Iris, which allows us to know which show within a streaming TV app your ad is going to show up in, and that's exclusive to Viant. And we made a recent acquisition of a company called T-Vision, as you know, which is the second largest U.S. television panel behind Nielsen. And what that company gives us is information about is anyone in the room when the content is being played on the screen, how many people, the co-viewers, And ultimately, are their eyes looking at the TV screen or are they looking at their mobile phone? We call this attention. And so when you combine all of this exclusive data, it's not available in any of our competitors. That's what's driving the ad spend into Vyant's platform.

Great. So turning to the broader sort of advertising backdrop, how would you characterize sort of advertiser health amid this current macro uncertainty? Advertisers sort of getting more constructive with budgets? or are they being still a little bit more selective in terms of where they spend?

I think overall the macro backdrop, even with the war in Iran, we see it pretty stable in general. Very small customers that I've seen have said anything about it. It usually doesn't really come up, and ad budgets continue to remain healthy.

So let's talk about your initiative with larger advertisers, which is gaining a lot of traction. How are some of the recent wins like Whoop ramping, and just talk about how the RFP pipeline look like.

Yeah. So recently we announced two large enterprise customer wins. If you were around three years ago, we served small to mid-size advertisers. We've continued to build the business up. We continue to add an enterprise sales force, and we get pulled into these RFP processes for the major US advertisers. Our big competitor, the Trade Desk, is reeling. They're losing share. We recently announced Molson Coors was a big win for us in that kind of enterprise customer category. Whoop is another one that we announced, and they've consolidated their ad spend onto our platform. The consolidation has gone perfectly. It started in late Q1, early Q2, and they continue to ramp their spend. And when big advertisers come on, they usually bring on display ads, online video ads, mobile ads, and some CTV. These are multi-year contracts the enterprise customer wins, so it gives us more visibility into the revenue. So it starts small. Year two, there's much more ad spend because they've got their entire budgets loaded in and all their campaigns running over the course of year one. And usually in year two, you get linear TV budgets transitioning into streaming. And then year three, even more linear consolidates into streaming. So we're really excited about the customer wins that we have. You mentioned the pipeline. We announced on our earnings call, we have the largest sales pipeline in the company's history. And we've been around for 28 years. So you've got just product differentiation. We have the data that advertisers want. and we've gotten the platform mature enough and we're executing in this enterprise category and the pipeline is as healthy as it's ever been. The way the pipeline works, it's usually an annual process, RFP process. So they issue an RFP in Q2 that they're going to leave the Trade Desk or Google. They're looking for new platforms. You got to get general counsel, the chief information officer, the head of their IT. They put data in and they test in Q3. They test again in Q4, and they usually make the decision for 2027. So we see a tremendous amount of tailwinds in our business with the current customers that have onboarded and a huge pipeline that we should win our fair share of, which would then provide further tailwinds for 27, 28, 29.

That's great. And we'll talk about all your sort of new products and initiatives. But in general, why are you taking so much share from some of your larger competitors?

This business is really simple. When we go talk to an advertiser, every advertiser for two decades has asked the same question. When they come in, they say, what exclusive content do you have where I have to work with you? Or what exclusive data do you have where I have to work with you? So if you start with the biggest competitor of Google, they obviously own YouTube, and that's their pitch. You can only buy YouTube through Google. And so Google is always on every single buy. Amazon created Prime Video to replicate that same strategy, and they've signed the NBA, NFL, all this content. So if you want to get your ad in those shows, you're there. But when it comes to a third-party independent DSP, the way we differentiate is we don't care where the money goes. We are independent. If the money goes to Disney, if it goes to Fox, if it goes to Roku, we don't care. We just work for the advertiser and charge them a fee. But we answer that critical question, which is what exclusive data do you have? And we bring data that no one else has. And if the data provides value, you use our DSP. That's that household ID, the identity spine. What does that allow you to do? Target ads effectively. In old TV, it was one ad shown to everybody. In streaming, every user is getting a different advertisement and the way that we do that is with the household ID. If you want to know which show your ad is being placed in, Molson Coors, they sell beer. They don't want their ad to show up in the Kardashians. They also get fined, because it's a regulated industry, if their ad shows up in kids content. And so because we have Iris ID, the content identifier, that acquisition we made, we're able to make sure that their ads don't show up in kids' content, and it provides their legal team with a lot of confidence that we solve that problem for them. But now with T-Vision, which is the acquisition we just made in April, we can now tell you where your advertising has so much waste. Certain shows, 50% of the time, no one's in the room. And it's really easy to understand the concept of, if an ad plays out on the TV screen on YouTube, and there's no one sitting on the couch, the ad has no effect. It's pure waste. And we're the only company that can answer that specific question. The way T-Vision works, it's 15,000 people. We have a camera in their family room. They register themselves. They sign up. It's all opt-in. We don't have a camera in everyone's living room. That's a common question I get. So we have a panel that has a camera in there where we can see what's happening in the family room. It's measuring the content and the ads when they play out on the screen. So not only are we helping them understand their media plan and where the waste is, we're also telling them which ad creative is better than the others. So you know a lot of times an advertiser might have 10 different ad spots like Starbucks and they choose based on gut instinct creative A and they run it 70% of the time because someone thinks that ad is the best. But when we're measuring eyes on screen engagement, that's ultimately what we're looking for, is when you see this eyes on screen engagement, that's your best ad. It's driving the attention of the consumers that it's being played to. Starbucks, great example. I was just looking at their data. They ran Creative A 70% of the time. they ran Creative B 20% of the time, but Creative B had 20% more attention than Creative A. Had they just swapped that, they would have got way more for their money. They didn't need to increase their budget. It's a mixed shift in what they're doing. This is the type of intelligence. We call it the intelligence layer and how we've evolved from just the DSP that helps you place your ad, a demand side platform into an advertising intelligence company where we bring exclusive data and we give a competitive advantage to the advertisers that choose to work with us.

Great, so let's talk about outcomes next which already accounts for about 5% of total spend just in six months after launch, right? And that's all from existing customers who are shifting performance budgets from search and social. How does this performance compare to your expectations and launch and just talk about this product.

Yeah, so we launched a product at CES called Outcomes. Our North Star on our product roadmap is to do everything we're talking about today with no people involved. Let AI take over every aspect of the advertising process. And so Viant AI Outcomes, which we launched in January at CES this year, the advertiser tells us the URL of the product or service, their budget, the goal, I want to achieve customers at $20 or $15, whatever it may be, and the time frame the campaign runs. And our AI instantly generates an ad campaign for them, where you're going to place your ad, how much budget you're going to put in CTV, online video, display ads. It allocates the budget for you. And line item by line item selects all the websites, mobile apps, and streaming shows that your ad is going to show up in. And then after the campaign launches, we have that same AI is reading the reporting and instantly making changes within minutes to that campaign based on the feedback that we're getting from consumers. Is it working well? Is it not working well? Are we above the goal, below the goal? We can change price. We can cut a publisher. And this, when you compare humans trading the ad campaigns or running ad campaigns versus an AI running ad campaigns, similar to the financial markets, it's hard to beat an algorithm. And so we see, on average, we beat humans by 65%. And so we launched this product in January. As you could imagine, with all AI products, there's a little bit of friction with humans that are, you know, can I trust it? What if it doesn't do it? But it now represents from zero to 5% of the ad spend. And that's only amongst existing customers. And these are incremental budgets that we're getting. When an advertiser goes to market, about a third of their money is spent in brand advertising. And about two thirds of their money is spent trying to direct response advertising. We call it performance. Historically, we didn't play in the performance game. That really is Google and Meta, and it's why their budgets and their revenue is so large. So Outcomes is meant to go after the Meta 10 million advertisers and enormous budgets there and compete in the same way. Google has a product called Performance Max, which is similar to this. Meta has one called Advantage Plus. And now Viant has Outcomes, and it's been very, very successful.

Great. So among advertisers that are committing budgets to outcomes. Is it still sort of test and learn approach or you're seeing sort of more material shifts in budgets?

Yeah, I would say it depends in the stage. So our earliest customers, and this is the way it goes. Someone comes up, they say, okay, I'm willing to test it. Here's $20,000 and I want customers for $15. Let me just speak to an exact name. McKenzie Childs, which sells home goods. They, you know, it's kind of like, it looks like an artist painted it. A lot, it's very whimsical. goal. It's a high-end home goods product. Let's say the average platter sells for between $500 and $700. So they told us they want customer acquisition costs of $60 was the goal. They come in, they did it with $20,000. We beat the $60. They do $40,000. We still beat the $60 goal. That is now up into the six-digit figure. What we don't know is can they spend $10 million and still achieve customers at that goal, that's where we don't know which is the upper bound of budgets per advertiser, and it's kind of you feed it more and more money, and then at a certain point, you've really exhausted all the people in market for McKenzie Childs at that time. So that's now up to, let's call it a quarter of a million dollars, and that's kind of how budgets scale, and we just continually do it. And I just want to talk about how well the product performs. Their goal is $60. we're producing sales transactions for $15 for them. So the AI is demolishing any human's ability to compete. It's just there's human friction in accepting all of our fates in the future that algorithms are coming.

Interesting. So given all the momentum with outcomes, where do you see sort of percent of spend flowing through outcomes, let's say 12 months from now?

Yeah, I think it's going to continue to scale the way we saw. and it's current customers, like we talked about, we've built out the enterprise sales channel and every enterprise advertiser, if you're Southwest Airlines, you've got a branding budget and a performance budget. So I see over the next 12 months, a lot of the same, us going to the current customers and using it to win new customers. We call this a full funnel approach. You're doing the top of the funnel, branding, and you're doing lower funnel as well. But our long-term goal over the course of three to five years is to go after Meta's advertisers. There's 10 million of them. They self-service sign-up flow, and that's what we're running through all the cycles, testing and learning. How do we acquire those customers really cost-effectively? What types of budgets do they have to scale? And so I look at the longer-term horizon of, say, three years, and how can we hit hundreds of thousands of advertisers? The closest company that's gotten to this area is AppLovin, And that's really what's fueled their growth is they have a self-service sign-up flow similar to Meta, and we see ourselves going down that same path.

Got it. Do you think that sort of over time as AI agents are essentially competing with other AI agents, not humans, that spread could compress, or how are you thinking about it?

Yeah. In an AI world, the difference of my AI versus, say, anyone else's AI is what data do you have that no one else has? So AI is really good at data analysis, reasoning, and making decisions fast, as we know. So when we talk about that exclusive data, this has been our M&A strategy, going out and acquiring data assets that are really valuable to the advertising process so we can keep them for ourselves and give our customers a unique advantage in the marketplace. So we have household ID. No other company in the world has it. We have Iris ID, the content ID. No other company in the world has it. There is one competitor out there to Iris. It's owned by Nielsen, the television company. It's called Grace Note, but they only work with LG. So they have, let's say, 6% market share. Iris today has 50% market share. We've announced HBO Max, Disney, Roku, there's Vizio. They're all coming online. We will be at 70% of all the streaming TV apps are moving to Iris. So we're leaving the competition in the dust there, and that's going to be exclusive to us. With T-Vision, Google doesn't have a television panel. Google doesn't know if anyone's in the room when YouTube is playing. So having all of that intelligence built into our AI gives us that long-term sustainable moat where we don't think competitors can chip away at it.

That makes sense. You just answered two of my questions. So on Iris, so you pretty much just addressed what I wanted to ask you, but talk about that asset a little bit more and just talk about what it essentially unlocks at scale.

Yeah. Well, we've mentioned Iris. It represents a number comes across when we get an ad request from a streaming TV app. There's a number one, two, three, four, five. What we know is that's Landman season one, episode three. And then we run computer vision against that episode. And we know where the ad breaks are. So we know exactly what's happening right before the ad pod loads. And so the whole goal of advertising is relevance. We want the ad to be relevant to the consumer in there. And what we've found is the performance of advertising explodes when it's relevant to the consumer, which we do with Household ID. We know you're in market for a car or whatever it may be. But we also see that the performance of advertising, when it's relevant to the content, has another leg up in performance. And so as an example, Cabela's, which sells outdoor gear, hunting, fishing, things like that. If you're in Landman, in that scene right before the ad pod, if they're fishing in a stream and we load Cabela's and there's 30% off fishing rods, we see the sales activity explodes. That's what I mean about driving consumer relevance, content relevance. This is what Iris gives us. We also run computer vision and AI models to understand the sentiment of that video that the consumer is watching. I'm a Dodgers fan. I live in Southern California. And so a great example that I did that just recently happened. Dodgers hit a home run. Next guy gets out. We take the lead. Everyone's elated that is a fan of the Dodgers. The first ad that loads is selling life insurance in case you die. it's just it's the exact emotional sentiment that doesn't match what you have in the room and so these are all the areas that we're exploring around new data sets that come in where you know about the content you know about the emotional sentiment and when you get all of that right that's when advertising is most effective and this that I'm describing to you this is what advertisers hear from us and this is exactly why the trade desk is structurally declining quarter after quarter, their product just simply isn't innovative anymore. And so we're stepping into that role. They were the bellwether for about a decade. And we are now stepping into that role amongst that enterprise customers because you can't replicate what we bring to the table.

Yeah, that's great. So let's talk about T-Vision and just talk about where you are in the integration process. And it seems like you're investing a little bit more Just talk about sort of key investment areas there to bring that product onto the platform.

So television or the T-Vision panel, as I described, it's the second largest U.S. television panel that's out there. Nielsen is number one. Nielsen claims 42,000 households, I believe is the number. It might be 44. 42,000 households out there. When we look at their business, they really, the people with a people meter, If you guys have ever heard of that technology, when you're in front of a show, every five minutes, you're supposed to push a button on your waist. You wear the people meter. You push a button every five minutes to indicate you're still in front of that show. This technology was invented in the 90s. It was, you know, breakthrough at the time. But this is now 2026. So their people meter is really only 12,000 people in the United States that are wearing that people meter. When you contrast that to T-Vision, we are in 5,000 households today in the largest 35 DMAs, so New York, LA, all the way down. We want to scale the number of DMAs that we're measuring. And so we're going to, in that 5,000 households, we are measuring 15,000 people. So the number of people that we're measuring is already higher than Nielsen PeopleMeter, but they have more households and they have more DMA coverage. So we are investing in more panelists. We're going to double the number of DMAs from 35 to 70, and we're going to triple the number of households from 5,000 to 15,000, giving us about 50,000 people, more than Nielsen has. Our goal is to be the largest U.S. television panel and replace Nielsen as we all know what they are in society today. Nielsen has also announced that they're pulling back. Their cost to acquire new panelists is very high because their people meter is very complex. Our costs are very cheap. It's a basic computer, so a very, very cheap, tiny little computer. Think like Raspberry Pi costs and a basic webcam. And it's the software that was developed at MIT of these three really brilliant founders that did it, that we acquired it. And so we're able to scale for less than $600 per panelist. So we're going to triple the number of households. We're going to triple the number of persons. We're doubling the number of DMAs. Now, why are we doing that? The TV panel is statistically significant if you are a national advertiser like Molson Coors. But we also serve customers like Whataburger, which only operate burger chains in Texas. So we work in Dallas and Austin, but in the other DMAs within Texas, we don't have statistical significance. And that's really the goal is we want to go from national TV advertising, which is a big market, also to support local TV advertising, which is an even bigger market and better margins.

Speaking of Nielsen, do you have a view on how the proposed acquisition of Double Verify sort of reshapes or impacts their offering?

Yeah, it's an excellent strategy when you're Nielsen and you are the most hated company in the world. If you talk to anyone who's a customer of Nielsen, no one likes them. Double Verify is the second most hated company in the world. So it made a lot of sense to put those businesses together where both companies hate their customers. And so to me, Double Verify, it makes no sense logically or strategically. I think what that is is trying to move from television into something else, brand verification. I would expect, you know, DoubleVerify has been being pulled off of campaigns. Their business hasn't been doing great in that verification space. And it's the same thing. It's old, not innovated group of technologies that had its place at once but has been pulling back. So, to me, it's a private equity play, harvest a zombie business, try and suck up all the cash flow, and we'll see how long it lasts.

Got it. So, we have a minute or so left. I want to touch on financials before we wrap up. So, you got it to Q3 contribution X stack growing roughly 25% at the midpoint. You gave us range. What are key assumptions sort of within this outlook and sort of what would drive lower or upper end of the guidance?

Yeah, the key assumption is we have pretty good revenue visibility. We give quarterly guidance. We don't have multi-year. As we've won more of the enterprise customers, we have more visibility. But that's really par for the course. I just want everyone in the room, we have grown our net revenue, what we call Contribution XTAC, we have grown at over 20% for three years. And so my big competitor, Jeff Green from the Trade Desk, everyone listens to his words, but the numbers don't lie. We continue to gain market share. We continue to grow at greater than 20% for the last three years. We guided to 25% in Q3. That just means we just keep executing. We don't expect any black swan events to be derailing that number. What are the positive surprises to the upside? We have very little in political in there. We're not a huge historical political advertising beneficiary. But I do believe that there's possible upside if our teams can execute in that political category. You know, it's every two years, it's a once in a, it's like a land grab. We're not known for political, but more and more the data that we offer, political advertising agencies, candidates, it has huge benefit for them. So political could be a big upside. New customer wins can be an upside there. faster adoption of outcomes could be further upside there as well too so again i've talked about like all the risks and very pragmatically how we execute but i would expect just continued execution out of our team like i said north of 20 for three years we just do what we say we do pretty much quarter in and quarter out and the goal is brick by brick just to become the number one advertising platform in the business and we've continued to do that for three years and we see a fantastic future outlook over the next three years.

Great, clearly a lot of momentum in the business. We'll leave it there. Tim, thank you so much for joining us today.

Thanks, Maria.