--- title: "AI Overview Tools Keep Selling Monitoring as Optimization" description: "AEO dashboards can chart your AI citations. They cannot necessarily show which action earned one. Before paying for optimization, ask to see the work." image: "https://cdn.prod.website-files.com/6823bbd57170ea42b357cf81/6abc9be458af345c43bbfc86_d6e76416-8764-4e53-80d3-672a094d8ed0.png" --- September 30, 2026 • min read # AI Overview Tools Keep Selling Monitoring as Optimization ![Young man with curly hair wearing a black shirt outdoors against green foliage background.](https://cdn.prod.website-files.com/6821efca072e48f6f495a47e/68562d390107b3921a6e3d68_1743932904108.jpg) **Alexander Perleman**, Head Of Product @ groas Ex-Goldman Sachs and Stanford Computer Science alex@groas.ai [LinkedIn](https://groas.com/post/stop-telling-me-to-optimize-for-ai-overv#) ![Cover image for: AI Overview Tools Keep Selling Monitoring as Optimization](https://cdn.prod.website-files.com/6823bbd57170ea42b357cf81/6abc9be458af345c43bbfc86_d6e76416-8764-4e53-80d3-672a094d8ed0.png) AEO vendors keep selling monitoring as if it were management. They show me a brand linked inside a Google AI Overview, an upward-sloping visibility chart, and a subscription fee somewhere between $300 and $2,500. Then comes the promise: run an audit, patch a content gap, paste in some schema, and watch the citations appear. Apparently the model has a thermostat. I know this pitch. Agencies ran a version of it with Quality Score a decade ago. A buyer would record whether an ad group sat at a six or an eight, swap two headlines to match a keyword, and wait. If the score rose, that was management. If it stayed flat, that was Google’s black box. The work might have been useful; the claim of control was doing more work than the buyer. Ask an AEO vendor one question: **Which edit on which URL caused an AI system to cite the client?** A screenshot taken after an edit does not answer it. Neither does a proprietary visibility index. Yet monitoring an outcome, suggesting a change, and taking credit when the outcome improves have become one seamless sales demo. The vendor does not have to say it controls Google. It only has to let you leave the call thinking it does. #### A visibility chart is not a steering wheel The basic loop is easy to recognise. An AEO platform checks target queries across Google, ChatGPT, or Perplexity and records whether your domain appears in the answers. Your name appears; the line rises. Your name vanishes; it falls. As I argued in my [teardown of the standard AEO sales deck](https://groas.com/post/the-ai-search-visibility-deck-a-straight), that can tell you what happened. It cannot, by itself, tell you what made it happen or what to change next. ![Marketers polish a decorative barometer while rain pours through an office ceiling.](https://cdn.prod.website-files.com/6823bbd57170ea42b357cf81/6abc9be558af345c43bbfcfe_ce9734d9-2cc2-4f8d-a3b4-3f23ac9eb210.png) Say the dashboard reports a 14% visibility drop on Thursday and recommends rewriting your H2s. Before anyone touches the page, I want to know whether your citation share fell or whether fewer of the tracked queries triggered AI Overviews at all. [Practitioners discussing AEO visibility drops](https://www.reddit.com/r/DigitalMarketing/comments/1vg9td6/anyone_else_seeing_google_ai_overview_visibility/) have pointed out how those measures can be bundled into one score. A falling line may reflect a change in the search results rather than a problem with your article. The recommendation card does not make that distinction for you. It just gives you something to do. That distinction is not fussy measurement etiquette. If the answer format disappears from a tracked query, there may be no citation for anyone to win on that query that day. Rewriting your page in response is like changing your ad copy because the reporting tab moved. Before I accept the diagnosis, show me the queries behind the drop, which ones still produced an AI answer, and whether the brand lost ground *within those answers*. If the tool cannot separate those observations, it should not prescribe the fix. Then comes the placebo checklist: schema markup, tidy bullet summaries, an `llms.txt` file. Some formatting work can help make a page easier to use. That is different from promising a citation. In [one analysis of `llms.txt` across up to 300,000 domains](https://www.reddit.com/r/SEO/comments/1uclth8/does_llmstxt_impact_your_ai_visibility_and/), 97% of the files tracked were never touched by an LLM bot. Yet the checklist looks excellent in a client update. Nothing says progress like a completed task whose effect nobody can establish. **Before you pay for a visibility score, ask what the tool can do when the score moves.** An alert is useful if someone can act on it. Calling the alert an optimization engine is the old Quality Score trick with a newer chart. #### Three claims I would make an AEO vendor defend The pitch rests on three promises: the vendor can attribute citations to its edits, repeat the result across AI search surfaces, and keep the visibility it earns. Those are separate claims. A graph going up proves none of them. **Make the vendor defend each promise separately.** 1. **“Our edit earned that citation.”** Traditional search gives you familiar clues: fix a canonical tag, earn links, and watch where a page lands. Even there, a ranking change is not a laboratory result. AI citations make the leap from sequence to cause harder. [Ahrefs analysed 863,000 search results and four million AI Overview URLs](https://ahrefs.com/blog/ai-overview-citations-top-10/) and found that 37.9% of cited pages ranked in Google’s top 10 organic results. Another 31.2% ranked from 11 to 100, while 31.0% did not make the top 100. An organic position alone does not explain why a source appeared. Neither does a content edit followed by a citation. If the vendor cannot show what it changed and how it separated that change from everything else, “we got you cited” is a guess dressed for a sales call. I would still want the edit logged. I just would not let the timestamp do the job of an explanation. 2. **“Our playbook works everywhere.”** Even Google’s AI surfaces do not consistently cite the same sources. An [Ahrefs comparison of 730,000 paired queries](https://ahrefs.com/blog/ai-overviews-vs-ai-mode/) found just 13.7% citation overlap between AI Overviews and AI Mode. [OtterlyAI’s analysis across generative platforms](https://otterly.ai/blog/the-25-best-ai-seo-tools/) reported 11% overlap between ChatGPT and Perplexity. That does not mean every content improvement is useless. It means a vendor should not sell one formatting recipe as a dependable way into every answer engine. “Add an FAQ block” is not a theory of how all these systems choose sources. If the sales deck says *AI search* while the demo shows a win on one surface, ask to see the rest. 3. **“We can maintain your citation.”** First show me how you earned it. Then show me how you plan to keep it when the answers change. Tracking reported by [Search Engine Land put AI Overview volatility at 0.73 over 13 weeks](https://searchengineland.com/google-ai-overviews-organic-rankings-volatile-452255), against 0.55 for traditional organic rankings. BrightEdge analysis also found [30 times higher week-to-week brand citation volatility in AI Overviews](https://searchengineland.com/google-ai-mode-overviews-brands-study-459754) than in AI Mode. A recurring fee may pay for real, recurring work. It does not turn a citation into a durable asset just because the dashboard checks it every morning. If the citation disappears, I want to hear what the vendor will investigate and do, not how quickly it can email me the news. ![A house of cards collapses beside scattered technical SEO audit printouts.](https://cdn.prod.website-files.com/6823bbd57170ea42b357cf81/6abc9be558af345c43bbfce2_ec89db21-2a87-4514-846e-f4b5a50f3fa1.png) Here is where the pitch gets especially thin. The software flags a missing definition, suggests a bulleted FAQ under an H2, and presents the result as an answer-engine strategy. In [practitioner testing discussed on r/SEO](https://www.reddit.com/r/DigitalMarketing/comments/1wt6gag/writing_an_article_for_aeo_what_must_i_do_and/), textbook AEO formatting produced no citations without original, authoritative first-party material behind it. I would rather have a useful fact on an imperfectly formatted page than a beautifully structured paragraph that says nothing new. A machine can extract either. Only one gives it a reason to cite you. **Do not confuse making content readable with making it worth citing.** The first is a task. The second is the hard part. #### The fix is execution, with a record of what happened I am not arguing that businesses should stop trying to appear in AI answers. I am arguing that they should stop paying for the *appearance of control*. If you want a serious answer to **how to get your website cited in Google’s AI Overviews**, start with the work a dashboard cannot perform for you. Look beyond your own page. A brand’s claims are more credible when other sources discuss its work than when its blog declares itself the leading solution. Put original, usable information where it can be found and checked. Then make the site technically accessible and keep the material current. Those are jobs, not magic citation switches, and I would distrust anyone who guaranteed the exact answer they would produce. The same distinction applies to a so-called content-gap report. A competitor having 400 words where you have 250 is not, by itself, a gap. Missing original data, a question your page does not answer, or a claim with nothing concrete behind it might be. If the report cannot tell those apart, it is a keyword table wearing an AEO name badge. I do not want another paragraph commissioned to close a word-count deficit. I want someone to identify what a reader needs to know, find out whether we can answer it, and put the answer on the page. That takes more than colouring a cell red. And if the tool recommends a change, ask who makes it. A quarterly audit left in a ticket queue is not execution. Neither is an alert that a competitor appeared in an answer yesterday. When you compare [tools that promise to get a business featured, not just monitored](https://groas.com/post/tools-to-get-featured-in-google-ai-overviews), **ask whether the product acts or merely assigns homework**. The difference matters most when your team has no spare hours to implement another stack of recommendations. I do not expect a vendor to control a model’s answer. I do expect one selling optimization to identify the work it performed, when it performed it, and what happened afterward. That record will not prove causation on its own. It will at least tell you whether the vendor did anything beyond watch. And if the record shows a change that did not help, keep that in the conversation too. An honest failed edit teaches me more about the work than a highlight reel of citations with no edits attached. #### Ask for the action log, not the product tour The next time a sales rep promises AI search visibility, skip the comfortable upward trend line. Ask for **one specific change the tool executed**, the time it executed it, and the citation observations before and after. Then ask what other changes or query fluctuations could explain the result. If the answer is a recommendation card, you have found a monitoring product. Price it as one. ![A sales demo screen paused on an empty audit-log table, reflected in office glass.](https://cdn.prod.website-files.com/6823bbd57170ea42b357cf81/6abc9be558af345c43bbfcdf_03aa4f33-e9ad-4995-a375-02cb7e583b99.png) That is the part these demos tend to glide past. They can show that a competitor gained citation share. They can tell your marketing manager to publish an explainer page or insert FAQ schema. Your manager still has to decide whether the advice makes sense, find someone to do the work, and check whether it helped. You might be paying $1,500 a month for a task list. I have seen enough of the old agency version of that arrangement to recognise the economics: the report looks finished; the work has barely started. And yes, a monitoring product can be worth paying for. Knowing that an answer changed can be useful. But it should arrive with the right label on the invoice. The moment the vendor calls observation *optimization*, the burden changes. Show me the action, not the slide explaining what my team ought to do after the call. I want the work. That is why [groas](https://groas.com/) is built around an autonomous growth engine across paid and organic search: specialized models execute search work continuously within guardrails, while a named human strategist owns direction and accountability. The point is not to put a shinier visibility chart in front of the client. It is to spend less time reading out what changed and more time doing something useful about it, with revenue rather than a citation screenshot as the measure that matters. In 2016, I did not need someone to read a Quality Score aloud on a Friday call and invoice for management. I do not need an AEO vendor to tell me Gemini cited a competitor, either. Show me the change you made, what you observed afterward, and the business result you can actually trace. If all you have is a graph, sell me a graph. Don’t bill me for a steering wheel when you brought a barometer. ## Related Posts [![](https://cdn.prod.website-files.com/plugins/Basic/assets/placeholder.60f9b1840c.svg) ##### Agency AEO: Managing Knowledge Graphs and Auto-Publishing to Client CMS Guide for agencies on evaluating AEO software for knowledge-graph and citation management and auto-publishing to client CMS, and how groas documents that workflow. 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