EMARKETER’s Blake Droesch: AI is Showing Consumers Fewer Products. Brands Need to Understand Why
The retail shelf has always been competitive. AI is making it smaller.
“AI is showing a smaller selection of products to consumers than they would see if they were walking down the aisles of the store or even searching on Amazon,” Blake Droesch, senior analyst at EMARKETER, told Beet.TV contributor David Kaplan at EMARKETER’s Future of Digital event in New York. “The shelf of AI can be completely random at times. So it’s really a wild, wild west for retail, for brands.”
That compression creates both urgency and uncertainty for brands trying to understand how they show up — or don’t — in AI-generated recommendations.
Two paths to AI visibility
LLMs draw from brand websites, retail sites, publishers, and authoritative sources like government agencies and medical associations when generating product recommendations. For brands, Droesch identifies two ways in to that ecosystem.
“Your brand has to be well known enough by the training data that the model goes directly to your brand website, or you need to make sure that your brand has a strong presence on those retailers or publisher channels that the AI is going to for information,” Droesch said. “Those are essentially the only two ways that a brand can become visible on an AI platform.”
The predictable result is that the brands with the largest real-world footprints — Nike, Adidas in footwear — dominate AI recommendations for broad queries. Where it gets complicated is with specific, multi-condition searches.
Specificity creates opportunity and uncertainty
A consumer recovering from knee surgery, with flat feet, seeking a particular shoe size with next-week delivery is asking a question no brand can easily predict. That specificity makes AI visibility harder to game and more dependent on consistent, intentional product positioning across every channel.
“Brands need to be very intentional about what their product is for and who it’s for. Models are learning from that information and giving it to consumers in a similar way that a consumer would take in that information on their own,” Droesch said.
GEO spending faces a scrutiny moment
Generative engine optimization is already becoming a significant marketing investment category. But Droesch thinks the ROI question hasn’t been asked carefully enough yet.
“GEO is getting very surgical at this point. But is your AI visibility going from 18% to 20% really going to pay off? And if that costs a lot of money on behalf of your marketing investments, is that outcome really worth it when that money could be spent on more performance based advertising?” Droesch said. “That’s a legitimate question that marketers are going to really have to start grappling with once those bills come in.”
Own your website, earn your presence
The most actionable finding from EMARKETER’s data is also the most reassuring for brands. On both ChatGPT and Google Gemini, brand websites are the most frequently cited sources. That’s an owned and operated channel that brands already control. It’s an advantage that brands need to be reminded of.
Beyond that, Droesch points to authoritative third-party endorsements and earned media in leading publications, as the signals LLMs consistently weight when generating recommendations.
“If your brand’s showing up there, then you have a better chance of showing up on the AI platforms,” Droesch said.
The retail shelf has always been competitive. AI is making it smaller.
“AI is showing a smaller selection of products to consumers than they would see if they were walking down the aisles of the store or even searching on Amazon,” Blake Droesch, senior analyst at EMARKETER, told Beet.TV contributor David Kaplan at EMARKETER’s Future of Digital event in New York. “The shelf of AI can be completely random at times. So it’s really a wild, wild west for retail, for brands.”
That compression creates both urgency and uncertainty for brands trying to understand how they show up — or don’t — in AI-generated recommendations.
Two paths to AI visibility
LLMs draw from brand websites, retail sites, publishers, and authoritative sources like government agencies and medical associations when generating product recommendations. For brands, Droesch identifies two ways in to that ecosystem.
“Your brand has to be well known enough by the training data that the model goes directly to your brand website, or you need to make sure that your brand has a strong presence on those retailers or publisher channels that the AI is going to for information,” Droesch said. “Those are essentially the only two ways that a brand can become visible on an AI platform.”
The predictable result is that the brands with the largest real-world footprints — Nike, Adidas in footwear — dominate AI recommendations for broad queries. Where it gets complicated is with specific, multi-condition searches.
Specificity creates opportunity and uncertainty
A consumer recovering from knee surgery, with flat feet, seeking a particular shoe size with next-week delivery is asking a question no brand can easily predict. That specificity makes AI visibility harder to game and more dependent on consistent, intentional product positioning across every channel.
“Brands need to be very intentional about what their product is for and who it’s for. Models are learning from that information and giving it to consumers in a similar way that a consumer would take in that information on their own,” Droesch said.
GEO spending faces a scrutiny moment
Generative engine optimization is already becoming a significant marketing investment category. But Droesch thinks the ROI question hasn’t been asked carefully enough yet.
“GEO is getting very surgical at this point. But is your AI visibility going from 18% to 20% really going to pay off? And if that costs a lot of money on behalf of your marketing investments, is that outcome really worth it when that money could be spent on more performance based advertising?” Droesch said. “That’s a legitimate question that marketers are going to really have to start grappling with once those bills come in.”
Own your website, earn your presence
The most actionable finding from EMARKETER’s data is also the most reassuring for brands. On both ChatGPT and Google Gemini, brand websites are the most frequently cited sources. That’s an owned and operated channel that brands already control. It’s an advantage that brands need to be reminded of.
Beyond that, Droesch points to authoritative third-party endorsements and earned media in leading publications, as the signals LLMs consistently weight when generating recommendations.
“If your brand’s showing up there, then you have a better chance of showing up on the AI platforms,” Droesch said.
