How to track LLM citations
The fastest way to make GEO accountable is to treat it like a prompt-tracking problem rather than a vibes-based reporting problem.
Start with prompts, not pages
Define the actual buyer questions you care about. These should be prompts a real prospect would type into ChatGPT, Perplexity, Claude, or Google AI Overviews when comparing options, learning a category, or validating a vendor.
Cluster by intent
Group prompts into buckets like category definition, alternatives, pricing, comparison, implementation, and trust. This prevents a random mix of prompts from muddying the picture.
Log the cited domains
On each run, capture which domains were cited or clearly referenced in the answer. Over time, that lets you measure citation share: the percentage of tracked prompts where your brand appears.
Measure consistently
- Use the same prompt set across runs.
- Track which engine produced which citation pattern.
- Save the answer text when possible for later interpretation.
- Compare deltas against the baseline, not just against last week.
Use citation share as the north-star metric
Citation share is not the only metric, but it is the most direct one for this category. It answers the real question: how often does the brand make it into the answer set buyers see?
The practical takeaway
Once prompt tracking is in place, GEO stops feeling abstract. CiterLabs uses that clarity to decide where remediation should happen first and how success should be reported.