The short answer
Start with the answers where a relevant buyer need favors a rival. Identify the reason given and inspect the cited pages. Then choose a specific response: correct a fact, publish missing proof, improve a useful comparison, or address a real product gap. Record the change and rerun the same questions. No content edit guarantees a recommendation.
“Create more helpful content” is fine advice in the same way that “get better at tennis” is fine coaching. It leaves rather a lot of the work unspecified.
An AI visibility report should narrow the next decision. If it cannot connect a recommendation to an actual answer and an identifiable buyer need, you are still holding a writing prompt rather than a plan.
Choose one lost recommendation worth understanding
Pick a question that matters commercially and that your product can honestly satisfy. Read every available repeat, not just the answer that annoyed you most. Check whether the same competitor and the same reason recur across providers.
Write down the stated reason in the answer’s own terms: easier migration, documented data location, a lower entry price, a particular integration. Treat this as an explanation expressed by the model, not a forensic account of every factor that generated the response.
Open the cited sources. Is the claim current? Is your product absent from the page, misdescribed, or accurately described but unsuitable? Those situations deserve different work. Our guide to mentions and citations shows how to separate them.
Turn the observation into a testable change
| Evidence | Hypothesis | Next action |
|---|---|---|
| Answers call a supported integration unavailable. | Public documentation may be missing or unclear. | Publish a precise integration page with scope and limitations; correct outdated owned pages. |
| Rivals are preferred for migration help. | Buyers lack accessible evidence of our migration process. | Document the actual steps, responsibilities, costs and a permissioned example. |
| A frequently cited directory has old facts. | That listing may contribute to outdated answers. | Request a factual correction through the publisher’s normal process. |
| The requested capability is absent from our product. | This is a product-fit gap. | Review demand with the product team; do not imply the capability exists. |
Give the action an owner and a review date. Add the answer IDs and source URLs to the ticket. Someone who was not in the meeting should be able to see why the work exists.
Resist turning every missing mention into a new landing page. If the answer already exists on your site, improve its clarity, discoverability or factual completeness first. Ten near-duplicates can leave a human buyer with more searching to do.
Keep the technical foundation boring and sound
Google’s official guidance for its generative AI search features points back to established SEO and useful, original content. It says no special schema or llms.txt file is required for those features. This is Google’s guidance for Google Search; it is not a specification for every assistant.
Check that intended public pages can be fetched, contain readable text, have sensible internal links and accurately describe the product. Make prices, eligibility, availability and limitations easy for a person to verify. Those are worthwhile improvements even if the next AI run does not move.
Use independent coverage responsibly. Supply reviewers with verifiable information and request corrections when facts are wrong. Buying fake discussion or presenting your own promotion as an independent recommendation undermines the very evidence a buyer needs.
Rerun the question, keep the receipts
Save the baseline before making the change. Later, rerun the same question panel under comparable settings and inspect both the counts and the explanation text. Was the old error corrected? Did the source mix change? Is the recommendation now supported by a different fact?
A before-and-after movement is an observation, not automatic causal proof. Models, retrieved sources and competitors can all change during the interval. Repeated runs and unchanged comparison questions help you interpret what happened. This guide explains the limits of that comparison.
Prioritize work that helps a buyer make a better decision and fixes a demonstrated gap. Even when attribution is messy, you will have a clearer product story and a record of why you changed it.
Sources & context
This guide responds to a question raised in Anyone here actually paying for GEO/AEO tools? on Reddit. The discussion informed the topic; it is not evidence of the effectiveness of any product mentioned there. Platform documentation is linked alongside the claims it supports.
Examples and figures are illustrative unless explicitly stated otherwise. Written and published by Share of Voice, a Superstellar LLC product. We sell AI visibility reports; our commercial perspective is worth keeping in mind.
Spotted something we should correct? Let us know.