You cannot improve your LLMO performance without knowing your baseline. A systematic LLMO audit — querying AI systems with target queries and recording which sources are cited — provides the data foundation for a content strategy that compounds rather than guesses.
The LLMO Audit Process
Step 1: Build a query list. Identify 50–100 queries that your target audience asks AI assistants — questions your content should be answering. Use keyword research tools, "People also ask" data, and your own analytics (which queries drive traffic to your site). Step 2: Run systematic queries. Query Perplexity, ChatGPT (with web search enabled), and Gemini with each query on a regular schedule (weekly or monthly). Record all cited sources in a spreadsheet. Step 3: Analyse citation patterns. Which of your pages are cited? Which competitor pages appear? Which queries are unclaimed (no clear authoritative source)? Which of your pages rank well in organic search but are not cited by LLMs (an indication that structural improvements could convert SEO authority into LLM citations)? Step 4: Prioritise improvements. Focus improvement efforts on: pages that rank on page 1 but are not LLM-cited (structural LLMO improvements needed), and unclaimed queries in your topic area (new content opportunity).