Monthly tracking of your brand across every major LLM

AI search is dynamic. ChatGPT and Perplexity update their retrieval constantly. LLM training data evolves. Competitors publish new content and earn new citations. A one-time audit tells you where you stand on one day. A monthly retainer tells you whether you are gaining or losing ground, catches competitor movements early, and gives you the trend data to know whether optimization work is actually moving the needle. Trend lines require consistent methodology over time. That is the only way to know if interventions worked.

Standard tracking covers ChatGPT (with Browse enabled), Perplexity, Google Gemini, and Claude. We run the same prompt set across all four monthly. Additional platforms (Microsoft Copilot, Meta AI) can be added as the market warrants. Each LLM is tracked separately because citation patterns differ in meaningful ways: Perplexity cites open web sources heavily; ChatGPT Browse weights Bing authority; Gemini draws from Google index signals; Claude projects from training data.

We design prompt sets with your category team at program start. A typical set of 75 prompts covers: 20 informational queries about your domain (what your buyers research before they buy), 20 comparison queries (how you stack up against specific competitors), 20 recommendation queries (who should I use for X?), and 15 brand-direct queries (tell me about [company name]). The set gets reviewed quarterly and updated as your product or market evolves.

Month 1 establishes baseline. Month 2 gives you the first data point. By month 3 you can see directional movement. Six months of consistent tracking gives you statistically meaningful trend lines that you can use to evaluate whether specific optimization initiatives worked. We are transparent from the start: the first two months are baseline-building, not optimization proof. The value compounds from month 3 onward.

Yes. The tracking retainer is designed to be used standalone or as the measurement layer for an active optimization program. Many clients start with tracking only to build the baseline, then add AEO or entity SEO work once they know which gaps are most urgent. Others run tracking alongside active optimization from month one. We scope both options and recommend based on where you are in your AI search maturity.

A standard report is 8-12 pages: executive summary with headline metrics, citation frequency charts per LLM, competitive share of voice chart, accuracy flag summary, and a prioritized action table with estimated impact per recommendation. We deliver it in the first week of every month covering the prior month. Clients get a 30-minute debrief call with the tracking analyst to walk through findings and agree on next steps.