Why Your AEO Isn’t Working

In this week’s episode of Voices of Search, we spoke with Jenna Hannon, founder and CEO at Hatter. Jenna was one of the first marketing hires at Uber Eats before launching one of the first agencies dedicated to AI search visibility – with a background in performance and product marketing rather than traditional SEO.

Our conversation covered why AEO starts with better marketing fundamentals, why AI search rewards differentiation over algorithm hacks, and why the brands chasing five channels at once are usually working against themselves rather than for themselves.

Key Takeaways From This Episode:

• AI search functions as a recommendation engine built on commercial intent, not the informational queries traditional SEO was built to chase
• AI struggles to recommend brands that sound identical to their competitors online—differentiation is what actually earns a citation
• Scaling across five channels without a positioning foundation works against a brand, not for it
• Traditional attribution doesn’t capture AI visibility well; citation frequency, sentiment, and sales-call attribution are better leading indicators
• Older, SEO-strong brands don’t automatically win in AI search, which gives smaller challenger brands a real opening

The Pendulum Swings Back to Marketing 101

Jenna’s path to AEO didn’t run through traditional SEO. She started in performance marketing on Uber’s growth team, spent four years on Uber Eats, and eventually moved into product marketing—work built around identifying an audience and figuring out what message they respond to.

That background shapes how she approaches AEO now: start with the marketing fundamentals, then build the strategy on top. 

Jenna pointed to two changes that separate how AI search works from the search engines marketers spent two decades optimizing for:

• It’s a recommendation engine: instead of returning dozens of links to sort through, AI search summarizes and narrows the field down to a handful of picks
• It favors commercial intent: informational searches that used to funnel someone toward a brand over time rarely surface a citation at all, which pushes the entire strategy toward more directly commercial content

“SEO for a long time actually kind of steered away from that,” she said. “The pendulum has switched towards more classic marketing, where AEO is rewarding having a deeper marketing foundation, not just the hacks.”

Differentiation Is What AI Can’t Fake

Those two shifts converge on a single requirement: AI has to be able to tell a brand apart from its competitors to recommend it at all. 

“If what is being said around you online on your website is similar to your competitors, it’s not going to know how to recommend you or your differences, because you’re going to look the same as competition,” Jenna said.

That’s the same problem product marketing exists to solve—understanding a target audience well enough to know what message actually lands, then making sure it’s the same message that’s showing up everywhere.

The Multi-Channel Myth

When asked about the biggest misconception in AEO today, Jenna didn’t point to a missing tactic. She pointed to an overcorrection: brands trying to be everywhere—Reddit, LinkedIn, X—before they’ve done the harder work of figuring out what makes them different in the first place.

“Most brands and companies have not figured out what their differentiation is. They haven’t done that positioning exercise, and therefore scaling those channels means they’re not going to be consistent across them,” she said. 

Without that foundation, five channels done poorly will cost more and do less than one channel done well. This is a pattern she’d already seen play out as a fractional CMO, long before AEO existed as a category.

Rebuilding the KPI Funnel

Because AI search compresses so much of the buying journey into a single recommendation, the metrics that used to define SEO success stop mapping cleanly onto it. Jenna’s team tracks visibility—how often a brand shows up in the queries that matter—alongside citation frequency and the sentiment behind those citations, which behaves nothing like a click.

The most important thing to note here is that the clearest signal often isn’t digital at all. 

“The best way to measure is, especially on the B2B side, how are people hearing about you—on your sales calls, how did you learn about us?” Jenna said. 

Beyond that, a few imperfect but useful leading indicators fill the gap: shifts in direct traffic, impressions on the pages AI is pulling from, and crawl logs that ping every time a citation triggers a fetch. This holds true even without visibility into the exact prompt behind it.

What the Delete Uber Campaign Taught Jenna About Brand

Jenna traced her conviction that some marketing value simply won’t show up in an attribution funnel back to her time at Uber. The company had a brand problem for years—perceived as the aggressive player next to a friendlier Lyft—and nobody on the performance-heavy marketing team owned fixing it. The Delete Uber campaign became the forcing function.

“We had no idea why this happened, and we’re not sure what actions we did that led to this,” she said. “That moment, the whole company was like, okay, cool—we’re going to take our performance marketing budget, and we’re going to start to think about reputation and brand and how people feel about us, which is fundamentally how humans choose to buy.” 

It’s the same argument she now makes for AI visibility: some of what moves a brand forward will never fit neatly into a dashboard.

Being an Old SEO Brand Doesn’t Guarantee AI Visibility

One pattern Jenna’s team sees repeatedly cuts against the assumption that established brands carry their SEO advantage into AEO automatically. Companies that built years of search equity through scale—thin location pages, broad keyword targeting, high page volume—often don’t show up in AI search at all, because those tactics were never fundamentals to begin with.

“A lot of these older brands that have been around for years, that were good at SEO, are not showing up as much in AI search,” she said. “SEO doesn’t necessarily translate into AEO, especially for companies that were doing kind of hacky SEO.” 

That opening is what makes the moment genuinely useful for smaller, challenger brands willing to do the positioning work larger competitors skipped.

Input Equals Output

When it comes to the marketing fundamental that AI will never replace, Jenna landed on strategy itself—the human judgment behind figuring out why someone actually buys. AI can scale the output, but it can’t originate the insight.

“Input equals output in AI,” she said. “If the message that you’re putting in there, or the inputs you’re putting in there, are not good, you’re going to get crap out.” 

Good marketing scaled with AI becomes very good, very fast. Bad marketing scaled with AI just becomes bad at a much larger volume.

Retire the Content Farm and the Checklist

Closing out the conversation, Jenna named the tactics she sees actively failing brands right now: 

• Programmatic pages produced purely for volume
• Keyword stuffing and article-length padding left over from old SEO best practices
• The going-through-the-motions checklist mentality that treats a hundred technical fixes as a strategy in themselves.

The common failure underneath all of them is sameness. 

“If you’re just regurgitating the same information that lives on a thousand different web pages, there’s nothing that separates you,” Jenna stated.

It’s the same differentiation problem the whole conversation kept circling back to, just showing up again at the tactical level.

The Fundamentals Didn’t Change, the Stakes Did

Every problem Jenna described in this conversation—channels chosen without a foundation, metrics that don’t map to the new funnel, brands that look interchangeable online—traces back to the same missing step: the positioning work marketing has always required, just skipped in favor of something that scaled faster.

AI search didn’t lower the bar for getting noticed. It removed the shortcuts that used to let brands clear that bar without doing the work.

Voices of Search is a daily SEO and content marketing podcast hosted by Jordan Koene and Tyson Stockton. The show delivers actionable strategies and data-driven insights to help marketers navigate the ever-evolving world of search engine optimization and content marketing. New episodes air weekly, covering everything from technical SEO to AI discovery, featuring industry leaders and practitioners sharing real-world frameworks and proven tactics.

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