AI Citation Source Mapping (Delivery)

AI Citation Source Mapping (Delivery)

1. 01

   Define the client's priority topics and buyer-intent queries

   Pull the top 10 to 20 keywords from the client's paid and organic accounts, then phrase them as natural-language questions a prospect would ask an AI assistant.

2. 02

   Run each query across ChatGPT, Perplexity, and Gemini

   Use a monitoring platform like KIME or Pallix to automate daily checks, or manually query if the client has a small budget. Record the answer text and the sources cited for each response.

3. 03

   Extract the cited sources and classify them by domain and content type

   Note whether citations come from the client's own site, competitor domains, Reddit threads, YouTube videos, or industry publications. This reveals which content formats the AI engines trust most.

4. 04

   Compare the client's citation share against the top three competitors

   Benchmark how often the client appears versus competitors in the same query set. Tools like SpyFu can supplement this with traditional keyword overlap data, while Voxoria tracks AI answer mentions.

5. 05

   Identify gaps where competitors are cited but the client is absent

   For each gap, check whether the client has content that answers the query. If not, flag it as a content creation priority; if yes, investigate why the AI engine is not surfacing it.

6. 06

   Prioritize the gaps by search volume and revenue potential

   Score each gap using estimated monthly searches and the client's historical conversion rate for similar terms. Focus the delivery team's effort on the top five gaps that offer the quickest wins.

7. 07

   Deliver a source-mapping report with recommended actions

   Present the findings in a client-facing deck that shows the citation landscape, the gaps, and a prioritized action list. Include a timeline for content updates and a re-measurement date in 30 days.