Track whether AI engines cite you.

AI citation tracking is the practice of running a curated set of real prompts against the major AI engines on a recurring basis and recording, for each run, whether your brand was cited, which competitors were cited instead, and where in the answer the citation appeared.

• Engine: ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews.
• Prompt: the exact text run against each engine.
• Citation status: cited, partial, or not cited.
• Position: where in the answer the brand was referenced.
• Competitor presence: who got cited in place of you.
• Timestamp & provenance: when the run happened, with the captured answer.

AI engines change. Their training data refreshes, their retrieval systems update, and their answer-shaping behavior drifts. A snapshot from last quarter doesn't tell you what an engine is recommending today.

Citation tracking turns a one-time audit into a moving picture. It surfaces regressions early, shows whether implementation work is actually moving the needle, and gives you an evidence log when stakeholders ask whether AI visibility is improving.

Citation tracking is layer 4 (AI Answer-Surface Presence) measured continuously. It uses the same prompt sets and evidence model defined in the audit, re-run on a recurring cadence. See the full layered model on the AI Visibility Score page, or learn what an initial audit produces on GEO Audit.

For SaaS brands ready to operationalize tracking continuously, the SaaS Monitoring product handles the recurring runs and evidence log.

The simplest first step is to see what one real run looks like. The free teardown runs one prompt against your category and shows you whether you, your competitor, or neither was cited — with the answer captured as evidence. From there, the full audit builds the prompt set and baseline that ongoing citation tracking is measured against.