Day 15 in the past, I guess they might be familiar. I've done this poll in each of these prior webinars. You'll see a poll pop up. It's a simple five-question survey. We have received a bunch of responses already, at the end of this session, what I'll do is I'll collate all the responses and share the collective wisdom of what we have learned so far. Equally important is sharing my disclosures. This is important for me to, and according to our compliance team. I'm just going to scroll to the next page, these are important disclosures. I'll stop share. I know, I just heard from our speaker, Mark, Chief Executive Officer, founder of MNTN, he's running a couple of minutes late. I just want to get this started, hopefully people have an extra 60 seconds to take the poll. We'll get started as soon as Mark jumps on. Until then, I'll just go on mute, and in case anybody has any SpaceX questions, let me know. We've been quite active on the pre-IPO front. Shameless plug here, did a couple of CNBC, Bloomberg appearances on that as well. No matter what you think of Elon Musk or his ability to take people to Mars or anything else. I think, objectively speaking, it's a very historic and a positive step in the world of capital markets, having completed the largest IPO to date. Oh, there is Mark. Hey, we're just getting started with the boring stuff here, we're just getting done with all the compliance and other disclosure stuff. We'll jump right in here, as in I'm done with my kind of initial things. Without further ado, thank you for joining us, Mark. Thank you. This is day four of a five-day AdTech Summit. I guess just to get things started, maybe for people who are new to the story of MNTN, how would you describe the company today? What has changed since you went public with the company? How I would describe the company is MNTN, we enable small, mid-size businesses, the SMB market, to access television as a way to drive revenue for them for the first time. TV, and specifically that means streaming TV. Television's traditionally been kind of a branding play for very large global brands. Even though it's the number one consumed channel, meaning more than 5.1 billion people a day watch television for an average three hours versus 4 billion a day use social media. It's this massive entertainment channel with all these consumers, it wasn't really available to the SMB market. What we did is we innovated there and introduced the concept and the technology that we call Performance TV, and kind of opened up this channel for any size business now to drive revenue using streaming television. Okay, fantastic. I know you have helped coin the word as well as popularize this idea of Performance TV. Now people talk about performance connected TV. Are these kind of the same things? In practical terms, how does your definition of Performance TV, does that subsume what we today understand as connected TV? MNTN literally introduced the term Performance TV to the world. It didn't exist on the internet before we introduced that term, and now it's becoming widely used. When used in the SMB market, you're thinking like an advertising platform that drives measurable visits and measurable revenue. It's analogous to paid search, paid social, and now Performance TV. As you look at it, some parts of the rest of the industry that, again, have been more centered in brand advertising, when they say Performance TV, they more mean targeted, not necessarily measurable. There is a difference, but the entire concept of television's now a digital channel that should have digital software that drive outcomes, that is the broadest meaning and the meaning that we essentially introduced at MNTN. Okay. Perfect. I guess, as we discussed in our prep call, I've raised three or four topics with all the execs that I've talked so far, just to give investors kind of an overarching thematic view of those three or four topics and how that is affecting your end markets, your customers, your company. First is obviously, no investor webinar can be done without talking about AI. At a very basic level, kind of when you think about AI at MNTN, where is it clearly showing up in your P&L today? How has it manifested in your P&L in the last 12 months? Talk about both revenue and cost, but maybe more first revenues. Yes, I think ultimately AI is like any significant new technology. It's going to be taken advantage across everywhere. We were pretty early in recognizing opportunities because we were so focused on performance. The first thing we introduced is two years ago, what we call MNTN Matched, which was AI targeting. We call it MNTN Matched because we think it's so precise, so essentially matching consumers with brands, so that they're potentially going to love. That was the first era we introduced it, and since then, we use AI technology, so LLMs, machine learning technology across our entire product line. Essentially all the decisioning, who to stream an ad to, what time of day with what frequency, what geographies, what content, meaning what streaming networks or even specific content, all of that is now AI-based. In terms of our team, one thing of note, more than half of MNTN's team is engineering. One out of every two people that work at MNTN work on our engineering team, there's prolific amounts of technology being created, that's a lot of what I just talked to. We also, I think we were one of the first to introduce AI creative tools, more than 95% of our customers have never advertised on TV before. The same percentage don't have television ads when we meet them. 30-second quality TV commercials that they can run across every streaming network in America. We introduced QuickFrame AI, which continues to gain traction and is now being used approximately 60% of our customer base, especially our new customers. It shortened the amount of time it takes for them to get live because it used to take about 42 days to go from, I want to do this, to having a TV commercial, now that's essentially less than a day for most of our customers. All of this tech is AI-based, we partner with all of the leading models like Google and OpenAI and ByteDance with the Seedance model and others in turn, we use different models throughout our business where it makes sense. Within our creative AI tool, we use multiple models even within a single ad, we're using multiple AI models. In terms of business itself, it's obviously a lot of our operations have gotten more efficient as a result of using AI technology. Our people team, what people traditionally think as HR team. That's just ingrained. I think at this point it's becoming pretty hard to consume technology, there's not elements of AI in that technology. For us, we've been producing technology with AI, we have some stuff coming very soon that we think is pretty groundbreaking in the Performance TV arena that again is all AI or models we've created for ourselves. Okay. Fantastic. A couple things to unpack there. I guess when it comes to all the AI tools that you're providing to small and medium-sized businesses that probably are getting a handle of what technology and what AI is actually enabling them, what are the biggest opportunities here as you think through next 12-24 months, if you can deliver those kind of tools or new AI capabilities to your customers, what do you feel is the most compelling kind of new use case that AI can unlock at MNTN? Like I said, I think the creative is almost its own revenue stream at this point. It's still small, but growing very quickly. The thing about the SMB market is that the budgets are relatively small compared to. Every dollar spent, it's really important that it goes to the right user. Let's think of two use cases. Your big national advertiser like AT&T. Half the country, actually the entire country can potentially become a customer of yours because everyone has cell phones. You're not really doing targeted advertising. You're really kind of placing your brand in front of literally every adult and teenager and so forth in America. You look at another use case, one that's a favorite of mine, which is Onewheel. They sell a single-wheel skateboard, really cool, but very targeted product. It's like snowboarding on the streets, you could think of it that way. It looks like a lot of fun, but it's going to appeal to very specific people. For that one, we use multiple layers of AI in order to understand, using the generative AI. Essentially models like who is that target consumer, what else are they consuming, what else are they buying in order to really pinpoint those consumers and then deliver very targeted ads to them. Before we were using AI tech, or the better way to say it is since we introduced MNTN Matched, the AI tech around that, for that customer, which is I think one of the hardest to pinpoint, that customer is getting 800% lift in terms of the number of visits and the number of conversions, like purchases because we were now able to really pinpoint their target buyer. Who likely owns a surfboard or is shopping for heli-skiing or is adventure-seeking. You really can pinpoint. That's why AI tech is so important to our business because it doesn't work unless there's all this technology we've created that really pinpoints that consumer to target them, measure them, deliver the right creative, and we're providing technology across all those layers for customers to get live and run on our platform. Interesting. Okay. I guess looking internally, with 2025 every investor was asking every CFO as to what AI can do to improve your margins. I think that was the most common flavor of the month throughout 2025. Where are we in that cycle, according to you? You have been an engineer and you know what AI can do to engineering productivity. Are you guys token maxing already? Where are you with just using AI to improve your 50% of your workforce? Yeah. No, we're not. We have relationships with OpenAI, Anthropic, Google, all of them. We host with Google, with GCP. My opinion is we have a really incredible engineering team. We run inside the company, we're very thoughtful as to how we use vibe coding tools, how we use various AI technology to use them. We don't use AI tool to do searches that are free on Google, w hich I think a lot of people are doing and wondering why they're token maxing. It's like you literally shifted a ton of free content consumption to paid content consumption and are wondering why you're maxing out on how much you want to spend. I think there's a layer of AI technology that's coming that's far cheaper, which is actually routing the right requests to the right layer of AI, and we essentially introduce that in our processes early on to be like, look, whenever you're doing something leveraging these technologies, you should not do it just out of convenience. You should incorporate, are you now just substituting something that was free a minute ago for something that's now paid? We definitely, like our whole engineering team has AI coding tools. Our whole marketing team has various technology using, especially for creative generation, including our own technology, QuickFrame AI. I think we're pretty thoughtful about it, but it's not fundamentally changing our margin structure. The other thing is that already we have 80% gross margins. I think it roughly in Q4, Q1, and we expect that to continue. We already had a very healthy discipline in the company around both our cost-related gross margins as well as our expenses that ultimately affect our adjusted EBITDA. Okay, fantastic. All righty. Just switching topics. In terms of last four months, one of the bigger debates has been around agentic AI or headless software or anybody who doesn't need a user interface but can actually manage a workflow using agents. Big picture, where do you see that? How do you think that in the context of MNTN and fast forward 12- 24 months, could actually agentic AI software manage a lot of what MNTN does and MNTN actually enables those agents? How do you see that evolution happen? Well, I think there's two aspects to that. One is, a lot of ad tech in general, and in particular, what MNTN does for our customers was already highly automated. In other words, you're a small business owner, we weren't presenting to you like a complex platform. It was already essentially very automated. There were no media buyers involved, so it's either a smaller business or in a mid-size business, a marketing manager, marketing team. If you look at platforms like The Trade Desk or Viant or other companies, they were built for the media buyer in an agency whose job it is to essentially buy media. You could think of them as analogous to a professional trading workstation with everything's manual, everything involves human intervention. There's a lot of manual communication going on, things like that. Where MNTN is, what's your budget? What's your goal? We'll figure out who your audience is. We'll give you AI tools to create the ads. We were already highly automated. Now you bring in an agentic layer, and I think that sounds great. We have MCP support, which helps enable that, and other things. I don't also at the same time think that most brands want to delegate brand management. Meaning like they're just like, I'm running a business and you tell me who my customer is. I'm just going to hand the business to you and send me a check every month. I like to use a term called Augmented Intelligence because I think this is where it's like at the center of these things, I think you're still going to have highly informed, very intelligent people who are leveraging, augmenting that to do these things for them. Within that, yes, absolutely, Agentic AI plays a big role, but that's a little bit different than you just turn the lights off, go home, and hope that your business continues to earn, generate revenue. I think that technology is very important. We're already a very big part of that. It's not quite going to play out at with the pendulum swung far as people think, where it's essentially marketing becomes just a lights-out operation there's nobody involved at all. There's a little bit of a solution searching for a problem there. Yep. I got you. I think there are certain steps that a marketer might want to automate without any human in the loop, but there has to be a series of checkpoints and iterative ways that you can keep on improving. I agree with that. Okay. Yeah, in our user interface, because in plot, you kind of mentioned are we going to be headless, no user interface at all? In our user interface, increasingly, it's an agent is making a decision, and it surfaces it as, this is what I'm going to do. Let me know if you disagree. At a certain point, you can just turn it off. I actually used to have quite a while ago, a boss, who if I went to him for approval, he would take three weeks. I started going to him saying, tomorrow at noon, I'm going to spend $200,000 on network switches. Let me know if you disagree by noon. I think that's how I see it more playing out, where things are surfaced, and if you don't stop it's going to happen. It's not like you are totally out of the loop and have no say in it whatsoever, and you've just, like I said, have moved to lights-out marketing. I'm not sure. Yeah. I like that. I like the way the metaphor there. A couple of questions in the chat and also just a PSA from my standpoint, please don't send anonymous questions. Our compliance people don't like anonymous questions. I'll read this out. Okay, can you talk about how you differentiate versus companies like Meta or Grok or Adobe that have AI video creators for SMBs, those tools? Would your customers use what they offer and integrate it like that? How do you see that AI video creative tools offered by other guys? Yeah, as a user of our platform, you can use any creative tools. Plus, one thing to remember is most of our brands, if not all of them, are doing social marketing activities. It's not like they don't have any ability to create video. I don't think you can really be a brand these days unless it's literally cost is your only. Value proposition, low cost is your only value proposition. Even then, you have to deliver that message. Our customers can use any tools they want. What we found is that, in particular for television, the ads are going to be multi-scene. There's a bit more complexity. They have to be 30 seconds to the frame. On social, there's no real exact hard limit on the length of the commercial. There's different AI models that are good. If you're using something like a tool from Meta, you're kind of limited to Meta's models. If you're using a tool from MNTN, we're partnered with Kling, ElevenLabs, Seedance. We're using all these models. You can go in, and you can say, I want to create a product ad, or, I want to create a spokesperson ad. We just have kind of really centered around specifically the use cases and really made it a lot simpler, either for the independent creator or the marketer or business owner themselves. You're welcome to use whatever works for you, as the end goal is to get your brand on the best shows on television and drive revenue for your business. We're seeing also, I think in the creative AI world, is a lot of people using different tools. It's not a zero-sum. Just in the same way, it's not like I'm only going to use Google for marketing. I'm only going to market on Instagram. I'm only going to market on Performance TV with MNTN. You're going to tend to do all these things. I'm actually seeing it play out that on the creative side, there's a tendency for people to be using different tools depending on the type of content that they want to create. It's not really turning out to become a zero-sum game. Okay. I got you. I guess switching over, like AI and all those things need data, and you're doing Performance TV, you need a lot of data to ensure measurement and attribution. Maybe talk about in your world, in Connected TV, Performance TV, how is the data ecosystem and what is the sustainable data advantage inside MNTN? Right. I'll start with the last part of that question. The sustainable data advantage is with the models you apply for the data. In other words, when you use Instagram, you're not really telling Meta that much that they don't know. A lot of the data that they use comes from things like their own tracking pixel. It comes from all the signals you're leaving around. Those signals are fairly democratized. There's not really a big competitive advantage in the data. You can get a lot of unique data, but if you don't have incredible models to use it. it's not valuable. All the real advantage comes in your use of the data, the technology, the team You have focused on it, all of the various testing, and ideas that you're testing applied to it. We have a broad set of data. We receive approximately 4 million- 5 million data points per second. It's just incredible volume. I think that's over 100 billion a day. I think over the course of a month it approaches many hundreds of trillions of bytes of data. The volume of data is there. We also have partnerships. Third-party data partnerships, first-party data partnerships. It all comes down to the processing capacity we have to apply our own models to that data. I gave you an example of that earlier when we were talking about Onewheel, and how in order to find a Onewheel customer, we essentially figure out who the customer is, and then figure out what other things that they would likely buy, consume, visit, how often, and that plus other things are a lot of the ways in which we apply that. The other thing to also remember is the media outlet for that data, and ultimately the ads, is a 30-second uninterruptable TV commercial on the largest screen in a home. That does play a role also. Content is important. If we're enabling you to create and test content at high speed, combining that with doing that with audiences, with all the data and models we have applied to that data, the combination becomes a sustainable advantage, especially in the area we're focused on, which is television, which is streaming TV. I got you. I guess, where do you see the biggest kind of potential for unlock as in what remains to be solved a lot with regards to data? It feels to me that the front end of the advertising Performance TV value chain seems to have been solved to a large extent, like the Gen AI creatives, perhaps the targeting. What about measurement attribution, like the back end? Where are you with that, and is that something that you have enough data to be a very good, close to deterministic measurement as such? Yeah. From day one, we've always had both our own measurement as well as we were initially integrated in Google Analytics. Integrated, now there's about at least 11, what's referred to as media mix modeling companies or multi-touch attribution companies. We have broad partnerships there. We've had them for a while. Our customers, not just for MNTN, but for every aspect of their marketing, they're always marketing in multiple channels. They're doing search, social, Performance TV, email. They might be on Reddit. They're market across multiple things. Each of these platforms is reporting, including ours, reporting what the behavior we're seeing within our ecosystem. Our customers, essentially the vast majority of them, then use third-party tools to get an overall view. Google Analytics traditionally was that main tool. Over the course of the last two years, that's broadened quite a bit, and now a great many of our customers use tools like Northbeam, Rockerbox, and others, which are third-party attribution tools. We love it. It gives an independent view that validates the performance not only of our platform relative to search and social, but also I think something like when we sometimes go in head-to-head tests. Like where people want to compare us to other things they might be thinking about, I think in the television ecosystem, we're winning those more than 90% of the time. That's using third-party data to validate that. That's awesome also. Nice. Is the last view, last click attribution, is that still a big problem where the larger platforms take a bigger share of what they actually do? That's changed quite a bit. I think the customers increasingly look at these things, not so much from last touch attribution, more from an incrementality. How incremental is this to my business? What we refer to as new to file. Is this a consumer that I haven't had visit my brand before, haven't visited within, let's say, the last 90 days? I think our customers, and across the industry, not just MNTN, across the entire industry, every company, including Meta and Google, they've developed much more sophisticated views as to how to look at that. You really honestly don't hear last touch. For our platform, the key metric is actually first touch. Television, think of it this way, is like Something like, this is a bit of confusion also, if you do search is an intent channel. You go to search and you kind of know what you want to ask about. You're leaving a signal. If you say, use our example before, skateboard, you're clearly interested in skateboards. If you go to an AI platform, that's really, in that context, another form of search. The result you get is different, but it's another form of search. On something like TV, something like social, you are getting content for products you didn't know you necessarily wanted, right? That's that Onewheel example, where you were like, you didn't even know about Onewheel, and all of a sudden it shows up in your Instagram feed, or it shows up in your TV via MNTN. You're like, Oh, that's really cool. They're very different. Increasingly the point of all that is we view ourselves as a first touch channel. Our goal is to be the first introduction to a specific product and category for that consumer via streaming television, as opposed to search and AI, which is more of the consumer already has this in their head and they tend to go there after they discovered it, or they've already bought in that category and maybe want to make another purchase. Okay. I got you. I have a question specific about QuickFrame AI product that you have. In there, you have given advertisers ability to export into YouTube, Google, kind of Meta, TikTok, whatnot. Are you offering QuickFrame as a standalone product for people to just do the creative part, or is that still fully integrated in your advertising platform? It's both. It's offered as a standalone platform. If you go to quickframe.com, there's pricing and so forth. We're very happy with the number of sign-ups we're getting per day on it and subscriptions, it's also offered completely integrated into our product. If you go do a sign-up on mntn.com, you can be live on television literally in an hour, and if you already had creative, in four minutes. If you need creative, it's going to take a little bit. You have to go through that step, and QuickFrame is integrated directly into that process. Okay. Very cool. I like that. Specifically for the very long tail that needs the basic automation help, I think that's a good way to get them onboarded, in my opinion. Yeah. Also, the one other big reason is that covers not just the long tail, but also our midsize customers. Is generally speaking, the more creative you have, the better performance you're going to get because creative can get stale, you're actively testing new ideas, we see QuickFrame as just lowering the cost of creative. Not that the customer necessarily even wants to spend less on it, but they get a lot more creative for their budget. We think that's really important as part of driving performance and why we chose, as a company, to take on that challenge of providing tools to help build creative. Okay, cool. We have about five to six minutes here with Mark. People who are online, quick reminder to take the survey poll. I'll share the responses in the next five to six minutes. Two topics, Mark. One is just competitive landscape. In Performance TV, you have larger players like Amazon and perhaps I would throw in Meta, YouTube, and then you have The Trade Desk, Roku, and other CTV players. Who are you directly head-to-head competing with? As you talk to your customers, if they don't use MNTN, where do they go to? Yeah. Generally, our competition's not with any of those companies. Think of the industry as split into servicing the needs of large global brands and then servicing the needs of SMB. The SMB is newer. It's also a lot harder. The large global brands, that's been The Trade Desk, and Amazon jumped into that with Amazon DSP, and you look at Roku, I think they make mention of seeing a lot of growth potential in the SMB market. I think that plus many other things have validated the TAM and the scale of opportunity we essentially ignited. The vast majority of that segment of the market is essentially entirely focused on kind of large global enterprise brands, the migration of linear television to streaming television. Our customers, more than 95% of them, have never advertised on TV before. They are coming essentially from social and saying, I already am spending on search, social, and now wanting to extend Excuse me, extend their reach, and essentially elevate their brand. At the end of the day, if you think of social, no one's going to call Google or Meta and says, I want to buy ads from you. What they say is, I want you to help drive traffic to my brand that converts and buys from me. When they come to MNTN, they're not coming to MNTN to buy ads, they're coming to MNTN as another path to driving high-intent consumers to their brand, and it just creates a different segment of the market, a different solution with different technology that we pioneered, have succeeded, and took the company public, and are pioneering. Our competitors, back to your original question, are more like one or two other startups. They're not like Trade Desk or any. We have a great partnership with Roku. We're not competing with Roku. You have to think of it in that way, that these are two different segments of the market. Another analogy to think about is there's one car industry. Porsche doesn't really compete with Toyota, right? Certainly Ferrari doesn't compete with Toyota. They're just in two different segments of the market. There's an overall Connected TV market. The fastest growing portion of that overall Connected TV market is Performance TV, and that's what MNTN created, and that's the segment we're growing in. Nice. Well put. Last question is just incremental growth, as in it could just be that you're in a market that is growing and you can keep doing more of the same. That's a perfectly valid strategy. Is there some new unlock in the next 12-24 months that could add a completely new layer of growth and new layer of revenues to MNTN? How should investors think about that? Yeah, absolutely. I've said on many calls with analyst calls and earnings calls, I've said half of MNTN is engineering, and not one time has anyone asked me, well, what are they building? That question has never occurred. There's a lot being built and there are definitely incremental revenue streams that we see coming in the future and that I'm very focused on and very excited about. I'm not ready to talk about them here. I don't want to pre-announce things. I do have a tendency to talk about what's coming soon. The answer to that question is absolutely. There's a lot of opportunity here, and I myself am a coding engineer. I'm an engineer first, CEO of MNTN second in some sense. I talk to my head of engineering, like already today, I've talked to him three times. Like five times a day, at least. We have a lot of plans, and I think we have a lot more coming. Okay. Actually, there's one last question from an investor. tvScientific was acquired by Pinterest. Under Pinterest, are they a more formidable competitor or are they even a competitor? How do you frame that? Yeah. I have a lot of respect for the tvScientific team. Some of the key people there were early at Overture. Which invented paid search, essentially. Doesn't get enough credit for that, by the way. First to market advantage is just a big advantage, and we had it. We felt very successful in competing against them. As part of Pinterest, my understanding and what I see in the market as to what they're doing is Pinterest has a lot of data and they want to extend their ability to monetize that data by extending the ads beyond just the Pinterest app and website. They're extending them. With tvScientific, it's a way to take the dollars you're spending on Pinterest and expand the number of dollars you spend because it can now go beyond the Pinterest app. Makes perfect sense for them. I don't think since that acquisition you're seeing people think, Oh, I'm going to go to Pinterest to be my Performance TV solution. We're not seeing that literally at all. I think that like many acquisitions, once a company goes in a company, it becomes part of their vision and takes them off in a different path, and that's what's happening here with Pinterest and tvScientific. Okay. Cool. Thank you for the perspective, Mark. We are almost at the end. I wanted to quickly share some survey results. People might find it relevant, useful, helpful. There were five questions in the survey. First was about recession. People don't think there is softness in online ads due to macro. Mostly neutral to positive. We asked about incremental growth in online advertising. I think connected TV is the one that people like a lot. ChatGPT ads comes up as a second one. Which AI applications to advertising and marketing are you most excited about? I think ad targeting followed by ad attribution and measurement. These two seem to be the top of people's minds. Which area of ad tech do you think is most likely to see M&A? Identity data collaboration, clean rooms, followed by AI workflow or creative automation. Maybe there might be some M&A there. Kind of similar choices, but a different question, which company do you think is best positioned in the AI-driven future of advertising in their CTV? You guys are in the right spot there, Mark. Followed by identity. Those two seem to be the most common things. We have a couple more sessions left, more importantly, I wanted to thank Mark, really pioneering a new category of ad spend and a new cohort of underserved customers. That's important. I think that TAM keeps on growing with more and more automation is what I would feel. Thank you for spending the time with us, Mark, and thank you everyone for joining. In 15 minutes, I'll interview CEO of Digital Turbine. They are in a turnaround mode right now, or so they claim. We'll see how quick of a turnaround they can do. Thank you, Mark. Everybody have a great night. Thank you. Thanks. Thanks. Thank you. Thank you.