Context
The setup before I touched it.
When buyers ask ChatGPT, Perplexity, or Gemini for recommendations, the answer rarely matches the Google SERP. Brands need a new kind of visibility tool that watches the LLM layer, not the search layer.
Problem
- 01No clear way to know whether AI assistants recommend your product for the prompts that matter.
- 02Citation sources differ wildly between models and shift week to week.
- 03Marketing teams optimise for SEO while the buying conversation moves into LLMs.
Approach
- 01Define a tracked set of buyer prompts per brand and category.
- 02Run scheduled probes across multiple AI models and capture mentions, position, and cited URLs.
- 03Score share-of-voice and surface week-over-week movement at a glance.
- 04Show which sources LLMs are pulling from so content teams know where to invest.
Outcome
- 01Brands get a measurable AI-visibility metric instead of guessing.
- 02Content teams know exactly which sources to influence to move rankings.
- 03Early signal on competitor moves inside the LLM layer, before it shows up in pipeline.
Role
Designed, built, and shipped end-to-end.
Status
Live - internal