Chapter 1: What challenges do AI search engines face in integrating ads?
The whole internet runs on ads, so why not AI? From American Public Media, this is Marketplace Tech. I'm Megan McCurdy Carino. Search engines, social media, e-commerce, mobile games, they all make money by selling advertising. But making ads work in AI search might not be so straightforward.
Perplexity, for instance, reportedly pulled back on plans to integrate ads into their AI search engine, and internal documents showed the company made only $20,000 in ad revenue in the fourth quarter last year. We spoke with Garrett Johnson, a professor of marketing at Boston University, to get a sense of why jumping into the ad business is difficult. There's a lot of challenges.
I think there's challenges of competition. There's intense competition for users, maybe more so than we saw in search engines and in social. And there's also competition on the advertiser side because they have to compete with mature digital ad platforms like Meta and Google and Amazon. And if you look at the challenge of setting up an ad model, I think there's many approaches they can take.
They could do something that looks kind of like what Google does or something that looks more like Meta with in-feed ads. or something totally new that's better suited to AI platforms, but increasingly it may be all of the above. And then the last thing is just the difficulty of scaling these models.
Chapter 2: How does competition affect ad integration in AI platforms?
So you need to onboard many advertisers, including small and medium sized businesses, You need to build this personalization flywheel. And that's why if you look at like OpenAI and their partnerships with Walmart and Shopify, that's really valuable. It gives them some sort of beachhead that gives them some conversion data of what consumers like.
Another challenge is that these companies are going to need to start simple and evolve into what they envision as their ultimate or broader ad offering. And so they have to meet users and advertisers where they are with things that are more familiar to them.
You mentioned this idea that in search and in social media, there has been this kind of platform dominance, winner-take-all thing that has happened. And right now, at least, there is still a lot of competition between different AI search, AI chatbot platforms online.
OpenAI, ChatGPT is obviously probably the brand name, but they recently said that they were putting advertising kind of on the back burner while they have this code red to recompete with Google after Gemini kind of won in the downloads for a while. I mean, what does this kind of say to you about the competitive landscape and how that might affect the rollout of advertising in AI? For sure.
I think these companies have a strategic dilemma between investing in their platform today to grow the user base in the hopes that they can have some future revenue opportunity versus investing in ads today, which would create revenue that would also fund that investment in the platform and create revenue down the road.
If you're going to do advertising, you probably want to get started sooner rather than later because you do have these returns to scale. I see, you know, in the OpenAI case, yes, you want to put the focus on this AI race. But especially Google has got a lot of a huge head start on the advertising side.
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Chapter 3: What strategies can AI companies use to develop ad models?
So they are going to start playing catch up. And certainly they've hired a lot of meta people at OpenAI to help them with this. They want to get started. I saw you were kind of making scare quotes when I said OpenAI might be putting ads on the back burner. You don't believe that?
All of these companies say, from Netflix to OpenAI to all these companies say, we're never going to have ads and we hate ads. But they ultimately use it because it pays the bills. And also, if you're going to be a general purpose platform like Google Search or an AI platform, one of the things that people want to do is they want to help buying things. And advertisers have...
have knowledge, they know how to meet the consumer's needs, and there's gains to be had from all sides for advertising. We'll be right back. You're listening to Marketplace Tech. I'm Megan McCarty Carino. We're back with Garrett Johnson, professor of marketing at Boston University.
I think a lot of consumers are enjoying using chatbots for search recommendations right now because there isn't advertising.
Chapter 4: How is the competitive landscape changing for AI advertising?
It seems like there could be a big penalty for whoever moves first on that. I mean, I think consumers are primarily using these things because they're amazing and they're revolutionizing how we can get distilled answers to our questions. Sometimes ads can be the whipping boy of the internet, but really they're not so bad.
Ads on these platforms are often pretty unobtrusive because they're text ads or product listing ads, something we're kind of familiar with. And ads can be useful. It's interesting to see Sam Altman start to get religion around ads and talk about how, well, maybe the targeted ads are kind of useful. And hey, those ads that Instagram has have things that I learn about and buy and like.
So I see what you're saying that maybe nobody wants to be first because they're competing for users here. But if you think through this, who are you losing? Well, if your subscribers are seeing fewer ads, then you're losing users that are generating no revenue today and that are costly for you to serve. So you have to value those users down the line pretty highly to justify that.
The search model spawned a whole industry of search engine optimization, and it was pretty straightforward. Companies had a good roadmap for how to get your business at the top of a search result. Now we're seeing this shift toward generative engine optimization as more consumers use chatbots for online search. What does this mean for businesses that want to buy ad space or that want to optimize?
Chapter 5: What is the impact of generative engine optimization on businesses?
Yeah, so businesses are now shifting their objective from just trying to be at the top of the search rankings to now being mentioned in AI chats in response to related search queries. And, you know, as much as some people might say this is the death of the SEO, the principles of search engine optimization and the principles of generative engine optimization are pretty similar.
You want to write quality content for queries that your users have. And you want to have your brand being talked about by high authority websites. One difference is that chat results may list fewer options. And so this can strengthen the winner take most dynamics that we already see.
And certainly now we're seeing this renewed interest in these SEO or geo strategies because companies want to be showing up. One thing, if you think about how advertising shows up here right now, if you look at search engines, they show you four brands and then in the paid listings and right below that, it's often the same four brands in the organic listings.
And I don't think you're going to see that with a generative engine. I think you're going to see four listings. Three of them may be organic. One of them may be sponsored. And in that kind of world, if you're searching for pizza, maybe Domino's and Pizza Hut don't have to pay because they're the large chains that would show up organically.
And maybe smaller chains like Little Caesars have to pay to play. But I think that shows you, you know, that exactly how these things get designed has got enormous consequences for the ad market.
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Chapter 6: How do ad placements differ in traditional versus generative search engines?
And we don't know just how these things are going to look. That was Garrett Johnson at Boston University. Daniel Shin produced this episode. I'm Megan McCarty Carino, and that's Marketplace Tech. This is APM.