Recommendation Moments
Discovery happens when a user crosses from gathering information into choosing where to go, buy, book, or contact. Your site needs to be there at that moment.
Outcome Alignment
The model recommends the site that best fits the user's desired outcome — not the site with the most content. If your site speaks to the problem, not just the solution, you enter the conversation earlier.
Decision Confidence
The model needs enough confidence to route a user to your site instead of keeping them inside the chat. That confidence comes from structure and visibility working together.
Why it matters
Eligible doesn't mean recommended. A site can be structured, visible, and trusted — and still not get cited. Discoverability is where context meets intent. The model asks: does this site make sense for the user asking this question, right now?
Back to: AI Structure →What Is LLM Discoverability?
Discoverability is not whether the model can see a website. It is whether the model recommends it when a user is ready to act.
AI DiscoverabilityOutcome-based targeting
The strongest discoverability pages enter the conversation before the buying moment and carry context forward until the user is ready to act.
AI DiscoverabilityContext-based targeting: event-driven uncertainty
When a disruption hits before service intent forms, the strongest page enters the event and carries context forward.
How to optimize for AI search
Outcome alignment is what makes a website the right answer in a recommendation moment.
AI DiscoverabilityAI citation research: WhatsMyArtWorth.com findings
A live experiment showing how citation, completion gaps, and structural signals affect when a website gets recommended.