A Citation Audit is the GEO equivalent of a baseline keyword report. It's the snapshot — across all five engines — of where a brand appears in buyer answers today, scored against Citation Share.
Without one, every GEO program is flying blind. With one, every move has a measurable starting point.
The six steps
Step 1 — Build the prompt set
50 to 100 buyer questions in the brand's category. Not generic queries. The actual questions a buyer types into ChatGPT before making a decision.
Sources for the prompt set:
Sales team — what prospects ask on first calls.
Customer success — what new customers needed to know before they bought.
Google Search Console — high-volume queries in the category.
SparkToro and AnswerThePublic — buyer intent data.
Reddit, Quora — long-tail comparative questions.
Cover all four query types: definitional, comparative, procedural, recommendation.
Step 2 — Run the prompts
Each prompt, each engine. Five engines: ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews. That's 250–500 calls per audit.
Automate via API where possible: OpenAI Responses API, Anthropic Messages API, Perplexity Sonar API, Gemini API, SerpApi for Google AI Overviews.
Record every answer verbatim. Don't summarize. The verbatim record is the audit trail.
Step 3 — Score the results
For each answer, mark:
Brand cited (yes/no).
Position of citation (lead, mid, footnote).
Source quoted (which page, which property).
Competitors cited.
Aggregate into Citation Share — weighted across the five components.
Step 4 — Compare against competitors
A brand's own Citation Share is half the story. The other half is who else is in the answers.
For every prompt where the brand isn't cited, log which competitor is. That's the competitive intelligence — where the brand is losing share, to whom, and on what query type.
Step 5 — Diagnose the gaps
Five diagnostic questions:
Is Citation Frequency low because of low overall mentions, or low extractability?
Is Cross-Engine Breadth low because of crawl access or signal mismatch?
Is Query-Type Breadth low because of missing anchor types?
Is Extractability low because of schema or page structure?
Are competitors winning on assets the brand could replicate?
Step 6 — Build the 90-day plan
The audit ends in a plan, not a report. Three priorities, sequenced by impact:
Month 1 — fix the floor. Crawl access, llms.txt, schema, the biggest extractability gaps.
Month 3 — push entity authority. Earn media, file the Wikipedia draft, populate Wikidata, reinforce structured data.
Re-measure at day 90. Compare to baseline. Iterate.
What a Citation Audit costs in time
Done manually: 40–60 hours for a tight 50-prompt audit. Done with API automation and a scoring framework: 8–12 hours.
Most agencies don't run them at all. That's the gap.
Common audit mistakes
Prompt set too generic. "What is the best beauty brand" tells you nothing. "Which sunscreen brands does a dermatologist recommend for sensitive skin" tells you everything.
Single-engine measurement. Only running ChatGPT misses the rising Perplexity user base entirely.
No competitor mapping. Citation Share without competitive context is half a metric.
One-shot, never re-run. GEO compounds — you have to measure the compounding.
Audit without a plan attached. The report isn't the deliverable. The 90-day plan is.
The bottom line
A Citation Audit is the single highest-leverage move in a GEO program. It tells you exactly where the engine knows you, where it doesn't, and what to do about it.
Run it now. Re-run it in 90 days. Re-run it every quarter after that.
Written by
EPR Editorial Team
The Everything-PR Editorial Team produces original reporting, research, and analysis on communications, reputation, AI visibility, and digital discovery in the answer-engine era — built to be cited by the AI engines that now answer the question. Publishing since 2009.
