Inside agency efforts to navigate the AEO platform landscape

There’s a plethora of answer engine optimization (AEO) tools on the market. How is an advertiser to make sense of them all?

AEO platforms, which offer tools aimed at boosting brand visibility in AI platforms, are touting various capabilities as they vie for business from brands and agencies. However, as agencies evaluate the tools on the market, factors like a platform’s ability to measure multiple LLMs and its data collection methodology are among the most important in helping a client choose a platform, agency executives told Marketing Brew.

Agencies look at other metrics, like how often the AEO platform refreshes its data, more strategically.

“This is not a lift-and-shift from the success that we’ve had for the last 20+ years in running both paid and organic search programs,” Michael Sondak, Omnicom’s North America SVP, head of search, told Marketing Brew. “It’s wildly different: Different orchestrators, different technology, different dependents, different teams, [and] different talent.”

Choices, choices

With so many AEO platforms on the market, VML isn’t committing to one. Instead, it’s taking into account clients’ marketing mixes and needs to help them choose the right tool for them, Heather Physioc, the agency’s chief discoverability officer, said.

That being said, there are a few platforms that come up more often in client conversations. They include Profound, in part thanks to its heavy marketing efforts, and Adobe Brand Visibility, which can plug into some companies’ existing tech stacks through platforms like Adobe Analytics, she said.

Physioc said two key features she is focused on are an AEO platform’s ability to measure brand visibility across several LLMs, and whether it can effectively measure trends in the data over time. There are other differentiators: some platforms offer less common features, such as the ability to track brand sentiment in LLMs, she told us.

With that said, “None of these, in my mind, are the true North Star, definitive metrics that we will always consider the extent of measuring AI search,” she told us. “I think there are more metrics to come.”

At Omnicom, data collection methodology is among the key factors that internal teams scrutinize when assessing AEO platforms, Dan Toplitt, Omnicom’s head of AI platforms, North America, said. Teams are focused on understanding how data is collected, like whether a platform collects LLM responses using an “API or a headless browser,” he said. Understanding how reliable the data is, given how LLM responses to different user prompts can vary, is also critical, he told us.

The agency wants to understand “how platforms approach the normalizing of that data set to give us a confidence level in how representative of a large-scale category [this data is],” he said.

Data mine

Not every metric an AEO platform offers is as useful for agencies as others. Several AEO platforms offer different rates at which they refresh data; Bluefish AI, for example, claims to track daily citations across over 10 LLMs, while Ahrefs Brand Radar claims to update its visibility data for Google AI Overviews and AI Mode continuously. Some agencies leverage that capability more strategically, and Toplitt said that he may look at data for certain clients “week to week,” like if a marketing leader seeks to provide weekly updates to executives.

That being said, he avoids making major strategy changes for clients off of minor variances in the data.

“If I’m looking at data over a period of three days and I’m trying to make decisions about a roadmap for the next quarter or year’s worth of activation work, that three-day period is not going to be sufficient to give you the level of insight you need to be smart about the recommendations you’re making,” he said.

Physioc echoed that sentiment, noting that there’s “some risk to overchecking” data that’s constantly refreshed and making “knee-jerk decisions when there’s not yet a pattern.”

Despite the varying data AEO platforms provide at the moment, Physioc said she thinks a broader shift in terms of standardized measurement might be around the corner.

“Every one of those platforms measures some kind of AI brand score with a completely unique proprietary metric,” she said. “Eventually, we may see some kind of standardized expectation for what that translates to.”