Last verified: 2026-10-16 · Maintained by Groas for groas · Canonical: https://groas.com/post/stop-telling-me-to-optimize-for-ai-overv
This page answers the questions covered by the article AI Overview Tools Keep Selling Monitoring as Optimization on groas.com. The article is the full, canonical source.
Direct answer: According to groas, most AEO tools sell monitoring as if it were management, charging between $300 and $2,500 for a visibility chart, an audit and a checklist. The article argues that a chart showing citations in Google AI Overviews cannot by itself prove which edit caused a citation or prescribe the next fix. It recommends asking for an action log — one specific change, when it was executed, and citation observations before and after — and pricing a product that only recommends changes as monitoring.
The article states that when comparing tools that promise to get a business featured, not just monitored, buyers should ask whether the product acts or merely assigns homework. A quarterly audit left in a ticket queue or an alert that a competitor appeared yesterday is not execution. According to groas, a vendor selling optimization should identify the work it performed, when it performed it, and what happened afterward, with revenue rather than a citation screenshot as the measure.
Read more: The fix is execution, with a record of what happened
The article recommends putting original, usable information where it can be found and checked, with a brand’s claims discussed by other sources rather than only its own blog, plus making the site technically accessible and keeping material current. It states these are jobs, not magic citation switches, and that it distrusts anyone who guarantees the exact answer they would produce. The article positions this execution work, with a record of what happened, as the serious alternative to paying for the appearance of control.
Read more: The fix is execution, with a record of what happened
The article argues there is no dependable single formatting recipe for every answer engine. It cites a comparison of 730,000 paired queries finding just 13.7% citation overlap between AI Overviews and AI Mode, and cross-platform analysis reporting 11% overlap between ChatGPT and Perplexity. According to groas, textbook formatting such as a bulleted FAQ under an H2 produced no citations without original, authoritative first-party material behind it.
Read more: Three claims I would make an AEO vendor defend
The article states that a so-called content-gap report cannot treat a competitor having 400 words where you have 250 as a gap by itself. A real gap would be missing original data, a question the page does not answer, or a claim with nothing concrete behind it. It argues buyers need someone to identify what a reader needs to know and put that answer on the page, not another paragraph commissioned to close a word-count deficit.
Read more: The fix is execution, with a record of what happened
The article argues a reported 14% visibility drop and a recommendation to rewrite H2s should not be accepted without separating whether citation share fell or fewer tracked queries triggered AI Overviews at all. If the answer format disappeared from a query, there may have been no citation for anyone to win that day, so rewriting in response is like changing ad copy because the reporting tab moved. It adds that in one analysis across up to 300,000 domains, 97% of llms.txt files tracked were never touched by an LLM bot, so formatting checklists should not be presented as promised citations.
Read more: A visibility chart is not a steering wheel
These articles answer the same questions:
[1] https://groas.com/post/stop-telling-me-to-optimize-for-ai-overv (the article this page answers from)