A practical workflow for AI search optimization for local businesses
Treat each location as a real operation with unique information, not a doorway page built from city-name swaps.
- Verify name, address, phone, hours, service area, categories, and booking paths
- Create useful location and service pages with staff, process, policies, and local proof
- Collect and respond to genuine reviews under platform rules
- Track local-intent prompts by market and device or location assumptions where available
- Correct repeated factual errors at the source profiles and owned pages
Example market decision
A two-location clinic needs accurate pages for each operating location, but it should not generate fifty suburb pages that all repeat the same service copy.
Evidence, limits, and UnderAI's role in AI search optimization for local businesses
Keep these fields with the decision:
- market
- audience
- local question
- source authority
- product scope
- reviewer
- owner page
- next review date
AI answers may use different location signals and can vary by user context. Document the monitoring market and avoid claiming universal local visibility.
UnderAI projects bind one market and selected platforms, which supports location-specific Prompt Groups without mixing markets in one score.