Inuvo, Inc. (INUV) Earnings Call Transcript & Summary

Hello, and thank you for joining us for the iAccess Alpha Virtual Best Ideas Summer Investment Conference 2025. iAccess Alpha hosts virtual investor conferences featuring companies sourced from investors with a track record of generating alpha. Today, you will hear presentations from 14 selected companies. IAccess Alpha holds 4 virtual investor conferences annually, 1 per quarter. The next event will be the iAccess Alpha Virtual Best Ideas Fall Investment Conference 2025 scheduled for September 16 to 17, 2025. We'd also like to take a moment to thank the many investors who have pitched in with ideas or helped source companies. These conferences wouldn't be as valuable or high quality without your ongoing support. Now let's begin with our first presenting company, Inuvo Inc. I'd now like to turn the floor over to today's host, Richard Howe, CEO of Inuvo, Inc.. Richard, the floor is yours.

Thank you, Jenny, and thank you those who have attended this. As Jenny pointed out, my name is Rich Howe, and I'm the CEO of Inuvo, and we trade under the ticker symbol INUV. To the best of my knowledge, we are the only company in the world to have successfully developed, commercialized and patented large language generative artificial intelligence, specifically for the solution of audience discovery and targeting online. Like a lot of good technology, our AI actually started its journey in life in a machine learning lab at UCLA, and we were fortunate enough to acquire the underlying patents and the original technology from that and then commercialized it specifically for the use case of targeting audiences online. In the last 35 years, there's really only been 2 evolutions in ad targeting. And the first one actually started when the Internet itself began. And the second one has been in place probably now for the better part of 25 or 30 or so years. And this most recent evolution, the one that is universally used across digital targeting, depends entirely on the use of your and my and everyone else's private data, meaning without the ability to identify who a person is and use their data, the targeting technologies are, for the most part, useless. Consumer data privacy legislation and technology changes that are impacting the very plumbing of the Internet are making this current method of targeting people based on who they are and their data obsolete. In fact, as of today, most people with an iOS device using Safari browsers are, for the most part, invisible as it relates to targeting because of the privacy changes that Apple has made. And that represents some 50% or 55% of mobile traffic. So this is a significant problem for advertisers, and it presents an opportunity for a company like ours who has built what we believe is the third evolution. And we believe we're positioned well to be able to capitalize on a large market and take market share as a result of having a technology nobody else on the planet possesses. I may say some things during this presentation that are forward-looking, please do treat them as such. Our markets are large. It's one of the reasons why we commercialized this technology specifically for this market. The ad market has a significant amount of spend. There's really sort of 3 high-level categories to this market. One of them is the search marketing area. The other one is social marketing. And the third is customarily referred to either as the open web, just generally the Internet and/or programmatic marketing. We have technologies that allow us to play in 2 of those markets. And as you can see from this slide, these are significant size marketplaces, $100 billion for the search marketplace and over $200 billion for the programmatic marketplace. And so this gives us a lot of confidence that we can actually build a significant sized business here just given the sheer size of the markets we're playing in. The challenge of the Internet, quite simply stated, is for the last 30 years, we've been tracking consumers around the Internet. And all of the companies, be they analytic companies, data companies, ad tech companies, measurement companies, all of them depend on the ability to actually track a person throughout their journey. And that journey involves many different paths. You could be on Facebook, you could be on search, you could be just seeing a website, you could be watching a television show online. Unfortunately, that path is now broken. And with it, so are thousands of companies who have built all of their technologies on the back of actually being able to do this. This is the problem that we set out to solve with this large language generative AI that we have developed and now proven many times in the marketplace. And it gives us a competitive edge in the marketplace and allows us to target consumers in a way that doesn't violate their privacy while at the same time, is performing measurably better than the current methods in any and all head-to-head tests that we have done against competing providers. We actually have 2 different types of artificial intelligence, solving the 2 biggest problems. If you can't track people around the Internet, then you can't actually effectively measure the effectiveness of the money you're spending across channels, meaning if I can't tell when you write Facebook and then you went to Google and then you saw an ad on a website somewhere, then I have a really hard time attributing the spend that I have against the value created from those various ads. It's near impossible to do that anymore. So we developed a technology, a machine learning technology that does the following. It basically can take all of the spend for some historical period across any and all of the channels that our clients are using and then deploying some algorithms that we have developed and extended ourselves proprietarily. It has the ability confidently to predict which of the channels are producing the value and which are not. And of course, what this allows our CMO clients to do is to have a dashboard that they can use to basically dial spend up and down across the various channels they're using, hugely beneficial and has been proven to be successful now in many of our client implementations that has had material changes to their business. The second artificial intelligence technology is the one I spoke of at the beginning that nobody else on the planet possesses, and that's the implementation of large language generative AI. This is technology in many respects, comparable to the large language technologies we're all now accustomed to using ChatGPTs and the Gemini and the rocks and the clots and whatever are out there. Similar in the sense that to accomplish the goal of building this technology, we had to build a machine that has the ability to read and understand and build a language model for the collective wisdom of humanity represented by all of the content on the Internet, hundreds and hundreds and hundreds of billions of pages. And it's exactly what we did. And interestingly, we started doing this now maybe 7 years ago. So before anyone was even talking about a ChatGPT or a Gemini, we were actually on this as a solution, at least to our use case problem. And the technology is out there today, and it's still reading pages every day, millions of them every single night. Fundamentally, it has the ability to determine for any product service or brand, the reasons behind why someone is interested in that product service or brand. And it does that without having to know anything about consumers. So for example, if you look at the left side of the slide here, you see the Wall Street Journal in the middle. And the Wall Street Journal in this case would be a subscription. So the Wall Street Journal is looking to basically find subscribers for this. And what our technology would be able to do is find out all the reasons why people might be interested in the journal. And the reason it has the ability to do that is because it's read everything that's ever been written about the Wall Street Journal by everyone, anyone. And of course, one of the audiences well-known one that comes to the forefront for the journal is the Theranos fraud. The Journal was the company that broke that fraud. And so if you look at this, our AI would have immediately figured out that Theranos is a catalyst, if you will, probably to people wanting to subscribe, i.e., a reason behind why they would want to subscribe. And so it would lock that into its memory. On the right side of the screen, you see the other side, the media placement side. So here, you have all kinds of media choices. You have connected TV ads, you have online videos, you have web pages where you can put ads on. If we just look at the top one, you see a movie there called the dropout. Now because our technology has read everything about everything, it knows what this television program is about. And it would conclude immediately that, that television program is about Theranos. And consequently, when a media opportunity comes available to be able to place an ad there, it would associate the fact that this is an audience member who is probably interested in Theranos. And ultimately, that would make them a good candidate for a Wall Street Journal subscription and it would put the Wall Street Journal subscription there. So the evolution that we have designed and developed with this technology really takes ad targeting from being about people. The way this is done today is it is all around figuring out who people are based on their data to actually doing audience discovery and targeting based on the reasons behind why consumers are interested in the things they do. And we believe this second approach, a paradigm shift in many respects is a way more powerful way to do this. And the evidence speaks for itself in the performance that we've seen for clients. This technology comes to life when you see it in a demo. So I'm going to play a demo now. It's video. So I'll be quiet here probably for 5 minutes and the next slide is really just going to show you an example of this related to this Wall Street Journal case. [Presentation]

So what you've just seen has never existed before, and it is amazing. The ability to be able to prompt the system and have it generate an audience for you in minutes and maybe more importantly, to be able to generate an audience about anything is amazing. It's transformational. It's never been done before. Nobody else is capable of doing it. And it really is what I'd like to say, democratizing the challenges associated with marketing, the analytics and the data and the discovery, all done by an AI without violating any consumer privacy and being designed for the future, not the past insofar as the way the Internet is developed. We think it positions our company quite well over the next few years to capture market share. At this point in our journey with Inuvo, we're roughly $93.5 million in trailing 12-month revenues, and we've served hundreds of clients and so we've had plenty of opportunity to prove out the value proposition of the technology you've just seen directly in market with clients. But here's one out of many. It's a recent one that we've been working with. This company is called James & James, and they're a higher-end furniture manufacturer. Prior to Inuvo engaging with James & James, they were like a lot of companies using an agency to help them with their marketing activity. They were spending twice as much money as they're spending now, and they were losing a lot of money. And in fact, the company itself was getting close to being on the verge of going under. Inuvo came in. We deployed both our AI technologies, the one that allows the CMO to measure the success of the money they're spending and second, the technology to help them find the right audiences and then target those right audiences. And within 3 months, the entire picture was turned around for this retailer. They now had a return on ad spend that was an increase over the prior spend they had of near 100%. They were able to open up and understand which channels were working and which were not working, turn off the ones that weren't, turn on the ones that were. And now they're profitable and they're on a growth curve and leveraging our technology and the great products they have, there's going to be a bright future for this company. There are literally tens of thousands of these kinds of James & James companies in the United States alone. And so we think we're in a great position to steal market share. The growth profile for the company has been attractive. We've had a compounded growth rate over the last 5 years of about 6.5%. We grew 13.5% year-over-year in 2024, and we've had a growth rate in Q4 2024, which was 25%. We had a 57% growth rate in the first quarter of '25. And we've already guided the second quarter of '25 to be up 25% year-over-year. As a technology company, as you can tell from this presentation, a highly technologically oriented company. AI costs a lot of money to build the computer systems and whatnot. It takes about $100 million for our company to be generating cash at the operating level. And we've broken through that barrier a few times now. We did $26.7 million, I think, in revenue in the first quarter of 2025. And so we believe this year, we should be able to have at least an operating cash flow breakeven on the business. And we do expect to see continued growth in the company going forward. We've had the good fortune to be able to serve a lot of clients. Here's a sampling of them. As I've said and continue to say, every time we serve these clients, we see a measurable increase over what they were doing before we showed up. So performance is not the barrier to our technology. The real hard part of gaining market share is the aversion to change in the buyers and the sheer number of competitors whose business models are so dependent on the old methods that they create complications for us in sales cycles. But we are fast overcoming that as the legislation changes and the technology changes that are changing the Internet are having an impact on forcing effectively people to change. Just maybe to sum up and then I'll probably turn it over to Q&A. But as I said, we are really the only company on the planet to have created this next evolution in digital audience discovery and targeting. We have a catalyst, if you will, in that there are some large changes in privacy that are ongoing that are helping us. If you can't target people online, we become a good choice given we don't have the limitations of the existing technologies. We have disruptive technologies that are being applied in both the search and the programmatic markets, roughly a $300 billion market between the 2 of them. We have proven growth now for at least 5 years, steady proven growth with accelerating growth actually starting in Q4 of 2024. So we think that, that will help us scale. And as I said earlier, now having served hundreds of clients, we're not -- we don't worry about whether or not we're going to prove our value proposition when we go into a client. We spend most of the time in our sales cycle trying to convince them to change and take the risk associated with changing off of something else. And with that, I guess I will turn it over to any Q&A.

Okay. So I see some of the questions here, so I'll see what I can do to manage this. One question that's asked here is, is anyone interested in acquiring the company? I would say we've been approached a number of times over the years to be acquired. And the only thing I can say is I don't think we're -- right now, at least at the valuation that we have, which we believe is significantly less than the inherent value of the company we have in a position to be able to sell to somebody and reward our shareholders for all the hard work that we've put into this company. So the answer is yes, but we need, I think, some more growth in the company and perhaps get ourselves to this cash flow positive, which we will this year before maybe an acquisition becomes serious. And there's a second question there associated with this, which is why not merge or something with a larger company. We work with some larger companies. We're not really merging with companies, but we do work with a large company. I should point out that we have -- our 3 largest clients are 3 of the largest companies in the world, one of the largest retail companies, one of the largest tech companies, another one, largest auto company. So the question becomes what are the larger agencies doing? The answer is they're all doubling down on the existing identity mechanisms, the consumer data methods. And this is exactly what happens when an industry disrupts and you have thousands of companies who are dependent on the old ways instead of reinventing themselves and doing it the way they need to do it to win in the future, they basically try to figure out how to take their round peg and put it in a square hole. And that's the best way I can describe what's going on, and it's happening almost universally. So we can help those companies. But in many cases, we're competing with them, and we see actually an opportunity to steal market share. The third question I see here was how do you plan to scale IntentKey across verticals? We serve a number of verticals now. We have some dominance in the client base in retail and auto. The key to scaling this is boots on the ground. And we have a sales team that's out on the street and we have an account management team trying to grow within the accounts we have. The answer to the question is we just keep adding more qualified people to do that and get out in front of people and spend some money on marketing so that people know that we're out here. Despite the fact that we're now almost $100 million in revenue, we're still a small player relative to the $1 billion Goliath who are in our industry. And so that's what I have. So with that, I will thank you for attending today, and I'll turn it back over to Jenny.

Thank you very much, Rich. That does conclude Inuvo's presentation. You may now disconnect. Please consult the conference agenda for the next presenting company.