LLM Analytics
LLM analytics is the practice of measuring and analyzing how large language models represent a brand: whether they mention it, how they rank it, what they say about it, and which sources they cite. It applies an analytics discipline to AI answers the way web analytics applies one to website traffic. Rankry is an LLM analytics platform built around this measurement.
What this page covers
Section titled “What this page covers”- What LLM analytics means
- What it tracks
- How it differs from web analytics
- How Rankry applies it
What it tracks
Section titled “What it tracks”A complete LLM analytics view records, per model and over time, your presence, position, sentiment, cited sources, and competitors. The raw responses are kept as evidence so any number can be traced.
How it differs from web analytics
Section titled “How it differs from web analytics”Web analytics measures behavior on your site. LLM analytics measures how AI models talk about your brand before a visitor ever reaches your site, including answers that never produce a click. The two are complementary.
How Rankry applies it
Section titled “How Rankry applies it”Rankry structures every AI answer into data, computes scores, and trends them. You can drill from any metric to the exact response behind it, compare models, and benchmark against competitors.
Frequently asked questions
Section titled “Frequently asked questions”Who uses LLM analytics?
Section titled “Who uses LLM analytics?”Marketing teams, founders, SEO and GEO specialists, and agencies that need to know whether AI engines recommend their brand.
What should an LLM analytics platform track?
Section titled “What should an LLM analytics platform track?”Mention rate, position, sentiment, citations, and competitors, across every major model, with raw responses kept and trends over time.
Is LLM analytics the same as AI visibility?
Section titled “Is LLM analytics the same as AI visibility?”AI visibility is the outcome being measured. LLM analytics is the broader discipline that measures it and the surrounding context.