An 'AEO' tools market emerges to measure whether ChatGPT and Gemini cite your brand

By Zendoric · September 12, 2026.

A new verb has appeared in the digital marketing vocabulary: AEO, answer engine optimization. According to the tech-insider.org portal, there is already a handful of tools dedicated exclusively to measuring whether a brand appears cited — and how — in the answers generated by ChatGPT, Gemini, Perplexity or Google's generative views, and to tracking whether those mentions translate into real visits to the brand's website.

The article reviews six platforms with different approaches. Similarweb AI Search Intelligence, which the outlet itself singles out as the most complete, connects mentions in AI answers with the subsequent referral traffic: which platform generated the visit, which page received it and on which topics the brand shows up. Profound is aimed at large enterprises and adds competitive monitoring and analysis of which sources feed the language models. AirOps goes a step beyond measuring: it generates and updates content to win those mentions. Rankscale.ai and PromptWatch focus on tracking prompts and citations — PromptWatch adds tracking of how AI crawlers behave on the site itself — and Rankability links classic content optimization with the new visibility in AI.

It is worth putting this in perspective: it is a vendor comparison piece, of the kind that fills the digital marketing sector, with no market, funding or adoption figures that would allow the real size of this segment to be gauged. We treat the six names for what they are — a snapshot of the current offering according to an industry source, not a ranking verified by Zendoric — and we are more interested in the underlying phenomenon than in the ranking itself.

And the underlying phenomenon is real. When users stop clicking on ten blue links and instead receive a paragraph written by a model, marketing's unit of measurement changes: it is no longer enough to come up in position one, you have to appear cited within an answer that does not even always link to the source. Hence the text rightly distinguishes between AEO and SEO: they are not substitutes, they are layers. Classic web analytics measures clicks; this new generation of tools measures whether the model, in building its answer, decided to mention you or your competitor.

That new layer replays, under a different owner, the same dynamic that dominated two decades of search engine optimization: whoever controls the criteria for what gets cited — now a handful of AI labs instead of Google's algorithm — concentrates de facto power over which businesses are seen and which disappear from the radar. In the short term, this is going to shift budget and jobs within marketing itself: fewer classic SEO analysts, more profiles auditing prompts, citations and AI crawler behavior, in line with what we are already seeing in other administrative sectors: the task does not disappear, it changes shape and requires understanding how a model reasons rather than how a search engine indexes.

In the long term, the reading fits Zendoric's underlying thesis: if AI ends up answering the user's original question better and faster — which product to buy, which doctor to visit, which technical solution to apply — the friction of searching for information is reduced, and with it the time people and companies spend on purely administrative visibility tasks. The risk to watch is not the measurement software itself, but that the new gatekeeper of access to information — the AI models and whoever decides their training sources — turns out to be even less transparent than the search algorithm it replaces.