AI Citation Readiness Review (Delivery)

AI Citation Readiness Review (Delivery)

1. 01

   Identify the buyer-intent queries that matter for each client location

   List the top 10 to 20 questions a prospect might ask an AI assistant before choosing a local service, such as 'best plumber near me' or 'reliable HVAC contractor in [city]'.

2. 02

   Run live scans across major AI platforms for each query

   Use a tool like VisiScan to check whether ChatGPT, Claude, Perplexity, and Gemini recommend the client, and capture the quoted answers and cited sources for evidence.

3. 03

   Compare AI recommendations against the client's local pack and map rankings

   Cross-reference the AI visibility results with traditional local search performance tracked in BrightLocal or Whitespark to spot discrepancies between classic and AI-driven discovery.

4. 04

   Audit the client's structured data and citation consistency

   Verify that Name, Address, Phone (NAP) details are uniform across directories and that schema markup (LocalBusiness, FAQ, Review) is correctly implemented, since AI engines rely on these signals.

5. 05

   Identify gaps in authoritative content that AI engines cite

   Review the client's website, Google Business Profile posts, and third-party mentions to find missing topics or entities that competitors are cited for, using the 107M AI answers study as a benchmark.

6. 06

   Document the findings in a client-ready report with prioritized fixes

   Produce a white-label report that lists each query, whether the client appeared, which competitors were named, and the specific actions needed to close the gaps, such as adding FAQ content or earning local backlinks.

7. 07

   Schedule a recurring monthly review to track AI visibility changes

   AI citation landscapes shift quickly, so set a monthly cadence to re-run the scans and adjust the strategy, ensuring the client stays visible as AI platforms update their algorithms.