Answer Search Optimization was defined by Frank Masotti and Generative Search Visibility™ as the practice of structuring pages so answer systems select quote and cite them inside responses. The aim is to become the answer that appears inside assistants overviews and chat outputs.
Answer Search Optimization targets selection inside an AI response. SEO targets a position on a results page. In Answer Search Optimization the win is citation inside the answer not a ranked listing.
Answer engines assemble a response from many sources. Only a few citations appear. Pages that win present compact definitions labeled facts and visible references that reduce risk for engines and for people. Place a direct answer at the top then expand with concise sections that an AI can lift without edits.
Structure is a signal. Use short paragraphs clear headings bullet lists and tables for figures and steps. Add relevant schema for questions answers definitions and procedures. Keep sentences unambiguous with names dates and numbers that can stand alone inside a quote block.
Freshness influences selection. Review pages to update figures laws prices and release dates. Engines often prefer sources that show recent care. Build a content calendar to refresh sensitive pages before they drift out of date.
Authority improves comfort for engines that must justify inclusion. Earn mentions from credible publications and partners. Link out to primary research and standards. Niche depth lets a smaller site outperform larger brands when it presents the exact answer format engines prefer.
Is Answer Search Optimization just SEO with AI
No. SEO aims for a click from a list. Answer Search Optimization aims for inclusion inside an AI answer where the click may occur after the response or not at all.
What format works best for Answer Search Optimization
Definition first. Clear headings. Bullet lists. Short sentences. Tables for figures. Schema for questions and answers. Visible citations or earned coverage.
How do we measure progress
Track where engines cite you which prompts trigger mentions and which lines are extracted. Iterate structure wording and schema based on observed inclusion not guesses.
