GENERATIVE ENGINE OPTIMIZATION: WHAT ACTUALLY CHANGES FOR AI SEARCH

Collect questions from sales calls, proposals, support tickets, and search data. Group them by the decision a buyer is trying to make: understand a problem, compare an approach, or select a provider. Answer the question directly, then show how you know. Original examples, specifications, methods, and trade-offs matter more than renaming a generic SEO post as an “AI” page.

For a manufacturer, that might mean explaining which materials a process can handle and what an RFQ needs. For a roofer, it might mean showing the inspection and estimate process. The page should help a human buyer even if no AI product ever cites it.

Keep important information in indexable text, link it from the site’s real navigation or topic structure, and use titles that describe the page accurately. Structured data can clarify eligible content, but it must match what visitors can see. Add original images or video when they improve the explanation, with clear context around them.

Google says pages need to be indexed and eligible for a snippet to appear as supporting links in its AI features; inclusion is not guaranteed. Be skeptical of claims about secret GEO schema, an “AI.txt” requirement, or a fixed citation recipe.

Track crawl and index status, search queries, qualified visits, assisted conversations, and leads by topic. Where a platform exposes AI-feature data, treat it as one signal. A citation or impression does not prove a sale, and many journeys will cross search, direct visits, calls, and word of mouth.

Review a small set of important buyer questions regularly. Improve the answer when it is incomplete, outdated, or weaker than the proof your business can show. The goal is a stronger information asset, not a page multiplied for every wording variant.