Brands Briefing: Measurement is the next frontier in GEO for brands
Over the past year, Loftie — a wellness startup best known for a high-tech alarm clock — has started asking people in its post-purchase survey if they first heard of the brand through AI prompt engines like ChatGPT and Gemini.
Toward the end of last year, only about 1.5% of people who completed the post-purchase survey said they first heard about Loftie through an AI recommendation. Within six months, that number has grown to 3%.
There are a few different ways to look at that data. On one hand, the percentage of people who discover Loftie through AI prompt engines is still in the single digits. On the other hand, that number doubled within six months.
That’s what prompted Loftie founder Matthew Hassett — who also runs an AI-native commerce platform for direct-to-consumer brands called Deliberate — to try and measure how often Loftie was getting recommended by ChatGPT, Claude and Gemini. He directed an AI agent he built, called Mariah, to pose the same series of questions to all the major AI models once a month and measure how often Loftie was getting mentioned. They mostly involve queries relevant to the major selling points of Loftie — prompts like “best alarm clock for light sleepers that struggle to wake up gently.”
Measuring how often your company gets recommended by AI engines – and, subsequently, how often those recommendations lead to website visits and sales – is becoming a bigger topic of discussion for brand executives like Hassett.
In the past two years, there’s been an explosion of new tech startups like Evertune and Profound that claim to help brands measure their share of voice within AI and get recommended more frequently. Existing marketing and branding agencies are also launching similar services. And earlier this month, Shopify announced that it is adding a new dashboard for merchants within the Shopify admin panel where they can track sales, orders and conversions generated through AI shopping channels.
In conversations with brand executives and agency owners, the consensus is that, while AI is still a small contributor of referral traffic, it is expected to grow very quickly over time. So, brands are trying to figure out how much they need to pay attention to it. Establishing a framework for measuring share of voice within AI search or more closely tracking referral traffic from AI can be one way to justify that.
Hassett said if he had to quantify it, figuring out how to harness more traffic from AI engines is probably number 10 on his list of priorities as a brand owner right now.
“The whole idea of purchasing [based on] ChatGPT or other platforms is very new,” he said. “But I think that if you don’t prepare for it, you are missing out.”
Jim Cusson, president of the retail branding agency Theory House, launched a new service called Kasper this month in response to clients’ questions about their visibility within AI search. Theory House has worked with CPG conglomerates like PepsiCo, McCormick and Diageo on package design, launch promotions and more. In addition to Theory House, Cusson has a tech incubator called TheoryNXT, which Kasper is part of.
Kasper aims to give CPG brands a clear picture of how AI recommends, describes and positions their brands. It submits up to 1,000 queries per month based on what’s relevant to a particular category. “It’s just conversations that you, as a user, might have, like, ‘I’m planning a backyard barbecue this weekend. What’s a great burger to impress my guests?’” Cusson said.
Kasper then calculates how often a brand appears in AI search and generates action cards with recommendations that brands can act on to improve their visibility within AI search.
“What we’ve been hearing more and more … in the boardrooms [of our clients] is, ‘Hey, are we being recommended by ChatGPT? Is our brand showing up?’ And then that just filters down to the brand directors and VPs of marketing that we work with,” Cusson said.
He added that one of the big challenges for CPG brands, in particular, is that their smaller, digitally native competitors are performing much better in AI search results, given that they may have a larger tranche of digital content to draw from.
Part of the conversation that Cusson is trying to have with clients around Kasper is that, not only can it measure how often a brand shows up in AI search, but it can also compare that rate to competitors and, in theory, model the revenue opportunity at stake for the brand if they make the right improvements.
But many brand executives are still stuck trying to figure out just where harnessing AI search falls on their list of priorities.
Vic Drabicky, founder and CEO of marketing agency January Digital, said that in his conversations with clients, “Everyone’s trying to figure out: Is it big enough for me to pay attention to, and if so, what do I do to make the most of it?” January Digital works with brands like Amika, Steve Madden and Carhartt, among others. “Everybody understands it’s important and that it’s growing, but they don’t know what it means to them, or how to affect it one way or the other.”
Measurement of AI search traffic remains an issue he still thinks is “47 steps down the road.” First, he argued, there are is some low-hanging fruit that brands can address. This involves structuring website content to specifically answer consumer questions that may be frequently posed to an AI agent and strengthening internal linking, among other steps.
Essentially, his argument is that brands need to focus first on giving AI agents a good base of structured content and data to work from. That, then, gives brands an easier path forward to set up a framework to explore whether, if they make a certain set of changes, they can increase the amount of referral traffic they get from AI engines from 2% to 5% over the course of a year.
“The more consistent you are in your measurement, the more consistent you are in your efforts, you can get a really good baseline for where you are,” Drabicky said. “If you’re preparing an organization for the future, you should pay attention to [AI traffic] now, not because you see the benefit right now, but because the benefit will be down the road.”
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