Guide · Playbook
The AEO playbook
How to get recommended and cited by AI answer engines — the same measure-fix-remeasure method we run for clients, in five steps.
1 · Measure your share of model
Start from data, not a screenshot. Build the real buyer "money prompts" for your category, run each 10+ times per engine across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews, and compute your share of model — the % of qualifying answers that name you — with a confidence interval. A single answer is one sample from a distribution.
2 · Fix entity & schema signals
Make it unambiguous what you are and what you do. Keep your name and one-line description consistent everywhere; publish Organization/Product schema and clean sameAs links so engines resolve you to one entity. Ambiguous identity is the most common reason a strong product is skipped.
3 · Publish answer-first content
Write pages an engine can lift verbatim: a one-paragraph answer at the top, then the detail. Comparison and "best-for" pages, FAQs, and benchmark posts — all schema-marked (Article + FAQ). This is what gets quoted.
4 · Earn third-party citations
Roughly 95% of the citations behind AI answers are third-party — review sites, directories, and community threads. Get listed and discussed where the models actually read: G2, Capterra, Crunchbase, Product Hunt, Reddit, and the round-ups that rank in your category.
5 · Re-measure on a cadence
AI answers shift continuously. Re-run your prompt set monthly and tie every change back to share-of-model movement versus named competitors — not vanity counts. That loop is the product.
Last reviewed: June 19, 2026. We re-check figures on a monthly cadence because AI engines change continuously.
FAQ
How long does AEO take to move?
Entity and schema fixes can land in days; third-party citation work and content compound over weeks to a few months. We re-measure monthly so movement is visible.
Can you guarantee a #1 spot?
No honest provider can — engines change continuously. We guarantee reproducible measurement and evidence-based work against a measured share-of-model target.
Logan Adams · Founder, Clear Cited
Writes on how AI answer engines pick what to recommend, share-of-model methodology, and reproducible AI-visibility measurement. About Clear Cited →