Why daily and not weekly?

AI engine answers change frequently as models update, indices refresh, and competitor signals shift. Daily tracking shows trend within 30 to 60 days. Weekly tracking is too coarse to see real movement. Monthly is useless.

For each prompt: was your business named at all (citation), was it in the first three names (top-3 rate), did the citation link to the correct URL (link integrity), and what competitors were named instead (competitive intel).

How many prompts should I track?

Between 14 and 25 prompts per business is a sweet spot. Cover the top buying-intent queries: "best [service] in [city]", "[service] near me", "how much does [service] cost in [city]", "[service] open now", "[service] that speaks [language]", and similar variations.

Can I do this myself?

Yes, manually. Open ChatGPT, Claude, Perplexity, and Gemini in five tabs. Run your prompts. Record the results in a spreadsheet. Takes about 30 minutes a day. Or use a tool like Traccion Visibility that runs the tracking automatically and surfaces the trends in a dashboard.

Glossary

What is LLM tracking?

LLM tracking is the daily practice of querying AI engines to measure whether your business gets named in their answers.

For twenty years, the analytics layer for search visibility was rank tracking. You'd track where your site ranks on Google for a set of keywords. Position 4 today, position 3 tomorrow, position 7 after Google's update.

In 2026, that layer is incomplete. Increasingly, customer queries are answered directly by AI engines without the user ever scrolling a ranking. The new analytics question is: when ChatGPT, Claude, Perplexity, Gemini, or Google AI Overviews answers a question your customer would ask, are you one of the businesses named?

LLM tracking measures exactly that.

What good tracking looks like

14 to 25 prompts per business, picked to match real buying-intent queries. Not vanity keywords, real questions customers ask.
5 AI engines queried in parallel. ChatGPT (free and paid often differ), Claude, Perplexity (free and Pro tiers), Gemini, and Google AI Overviews.
Daily cadence. Weekly misses fast-moving changes.
Structured results. Was your business named? Was it top-3? Did the link match your real URL? What competitors got named instead?

What the data tells you

After 30 to 60 days of tracking, three patterns emerge.

Which prompts you are winning. Double down on the content that supports those wins.
Which prompts you are losing. Identify what the winning competitors have that you do not, and ship the missing piece.
Which engines weight you highest. Sometimes you dominate Perplexity but are invisible on ChatGPT. Tells you where to focus citation work.

What to do with it

Tracking without action is a number on a screen. The point of tracking is to drive weekly decisions about content, citations, and structured data work. A good visibility program runs the tracking, reads the data weekly, and ships the highest-leverage fix every week.

We do this automatically in the Traccion Visibility service, with a customer-facing dashboard updated daily. You can also see your current state with a free Visibility audit.

Common questions

What is LLM tracking?: LLM tracking is the practice of querying AI engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) on a regular cadence (typically daily) using the buying-intent prompts your customers actually ask, and measuring whether your business gets named in the answer.
Why daily and not weekly?: AI engine answers change frequently as models update, indices refresh, and competitor signals shift. Daily tracking shows trend within 30 to 60 days. Weekly tracking is too coarse to see real movement. Monthly is useless.
What metrics matter?: For each prompt: was your business named at all (citation), was it in the first three names (top-3 rate), did the citation link to the correct URL (link integrity), and what competitors were named instead (competitive intel).
How many prompts should I track?: Between 14 and 25 prompts per business is a sweet spot. Cover the top buying-intent queries: "best [service] in [city]", "[service] near me", "how much does [service] cost in [city]", "[service] open now", "[service] that speaks [language]", and similar variations.
Can I do this myself?: Yes, manually. Open ChatGPT, Claude, Perplexity, and Gemini in five tabs. Run your prompts. Record the results in a spreadsheet. Takes about 30 minutes a day. Or use a tool like Traccion Visibility that runs the tracking automatically and surfaces the trends in a dashboard.