Artificial intelligence adoption into digital advertising may shift the focus from profiling who a consumer is to "why they are interested in your product, service, or brand." Inuvo Chairman and CEO Richard Howe details the implementation of language models to advertise to larger, interconnected demographics without harvesting user data or third-party information.
Video Transcript
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JARED BLIKRE: Investors have been keeping an eye on the different areas of the AI boom. Artificial intelligence's ability to assist with search functions and how it might impact advertising spending revenue is just one of them, particularly in the case of Google, which dominates the world with its search engine. And according to gs.statcounter, in 2022, Google made up 91.9% of the search-engine market.
Inuvo focuses on being a market leader and using AI for advertising, and its Chairman and CEO Richard Howe joins us now to discuss. Richard, thank you for joining us. I was reading about your company, really interesting how you go about your business, basically in the ad market. The ad market for online advertising, structurally changing. How are you using AI to take advantage of it?
RICHARD HOWE: Yeah. The big problem in advertising is, for 30 years it's been using identity as the fundamental basis for targeting, for creative, for figuring out which devices are attached to a person. There's just no aspect of advertising that hasn't been based on identity, and that's going away quickly. Most people would know that as the cookie challenge.
And what that does is it actually offers an opportunity, an opportunity to free yourself, if you're a marketer, from marketing that's been based on who someone is to based on why someone's interested in your product, service, or brand. And that's where AI comes in. The technology that exists within AI now allows us to not just solve the privacy problem, but really change the paradigm to a more powerful answer to the way you find audiences. Why are people interested in my product, service, or brand?
JARED BLIKRE: Well, you have a really interesting example online I found on YouTube that has to do with the Carhartt jackets and the coats. And could you just break down step by step how your company goes about using a product, such as this in gaining insights through artificial intelligence without having to glean that information from the users themselves?
RICHARD HOWE: Yeah. You bet. The Carhartt example is a good one. There's a lot of them, but I'll hit that one since you've asked for that one. Fundamentally, this kind of AI is based on a language model. There's a lot of different categories of artificial intelligence, a calculator is AI, but this kind is based on a language. And it's based on the language because we humans, we experience the world through the language.
So it's read the entire internet. It's being able to associate all the concepts that exist in our language one to the other, and all the pages that are on the internet one to another. And what that allows this AI to do is to associate things. So Carhartt, take a look at them. As a company, and as a brand, they really have owned the worker space, like jackets and outdoor wear, specifically, for people working hard in the fields.
And one of the things that our AI is able to do is associate things that you normally wouldn't think are associated. In this case, with Carhartt, it was the movie "Interstellar." So because our AI has read everything about Carhartt, and because our AI has read everything about everything, it knows there's a relationship between that movie and Carhartt.
Now, it knows even more than that. It's not just the movie "Interstellar," it knows that Matt McConaughey and Jessica Chastain are actually wearing Carhartt gear in that movie. And as a result, there's an audience there that you could target that you would never have been able to identify simply because the technology doesn't work that way.
JARED BLIKRE: So if you're able to read the entire internet, you're going to come across, stumble across some things, maybe some connections that you don't want. There's going to be a lot of hidden biases in there, and how do you tune your AI software? And maybe it's not just a concept of tuning, maybe it's more structural. How do you build in safeguards into the AI software to make sure it's coming up with relevant and appropriate terms and linkages?
RICHARD HOWE: Yeah. So when we have our clients, some of the things, obviously, that they care about is they don't want their ads associated with, let's just say, content that may be not associated with what they're looking for. I mean, probably a good example of that is an airline, certainly doesn't want any of their marketing materials on sites talking about plane crashes. There's ways to filter that out. So that's one example, but there are many ways to do that.
The good news about using this kind of a Y-based approach and not having any relationship or the use of third-party data, consumer data in any way is these, sort of, inherent biases in the way that we think about biases don't exist because again, it's not about the people. It's about the reasons why groups of people are interested in something.
JARED BLIKRE: Have you done a direct comparison between the old method of using cookies and tracking user behavior across sites and your current method? Is it better or worse? I would imagine just blatantly scooping up everybody's data, it's going to give you much better results, but maybe I'm wrong.
RICHARD HOWE: Absolutely. So it has the benefit of clearly solving the privacy challenge, which is the fundamental problem facing the ad industry right now, and the added benefit because the technology is so much better than the technology we actually invented when we invented the current ways of improving. So you get a better product, and you get to solve all the challenges associated with using consumer identity.
And consumers are basically not getting unhappier all the time with people using their data. And of course, all the manufacturers like browsers, like Apple are starting to prevent using those methods. So yeah, it's a double benefit.
JARED BLIKRE: Any numbers you can throw out here, or have you not done any back-to-back study like that?
RICHARD HOWE: Yeah. We track it all the time. So if you think about it this way, in any implementation where we implement the AI, we go up against, probably, somebody using identity-based tech. And on average, we beat it by 50%.
JARED BLIKRE: Impressive. We got time for one more, just under a minute. Anything you'd like to add to the conversation?
RICHARD HOWE: I think, it's important for marketers to understand that a future devoid of identity is upon us. And the sooner they start thinking about providers and technologies that can help them move away from that, actually, I think the sooner they'll be unshackled from the structured nature of that approach to marketing and open themselves up to new possibilities.
It's like any change in any market. You know, you've got to make the leap. And then once you do, you're like, oh, wow. Am I ever glad I made the leap.
JARED BLIKRE: And change is coming ultra fast now thanks to the technology. Really appreciate your insights. Thank you, Inuvo Chairman and CEO Richard Howe.
RICHARD HOWE: My pleasure.
