Measurement
AI Share of Recommendation
AI Share of Recommendation measures how often answer engines recommend a brand, not just whether they mention it. Learn how to track and improve it.
04 Read · 7 min
Presence, share of voice, and how a brand can be mentioned everywhere and recommended nowhere.
Presence is whether you appeared at all. Share of voice is how much of the named competitive set was you. Recommendation is whether the engine actually endorsed you rather than merely listing you.
These decouple constantly. A brand can appear in nine of ten answers and be recommended in none, because it keeps being named in the roll-call of alternatives while a competitor is named as the choice. On a presence metric that looks like a win. Commercially it is a loss, and a loss you will not notice unless you look at recommendation separately.
A single visibility score is useful for tracking direction over time and nearly useless for deciding what to do. The decision information lives in the per-prompt breakdown: which specific questions you lose, and to whom.
Sort by the prompts where you are absent and read those responses first. That set is your actual work queue. A prompt where you are absent and a well-corroborated competitor is recommended is a different problem from one where the engine gave a generic answer naming nobody — the first is a competitive gap, the second is an unclaimed space, and they need opposite responses.
Needs a free SolCrys account (no credit card). No quota consumed.
Start Free — free plan, no credit card.
This lesson is the spine. These guides are the depth.
Measurement
AI Share of Recommendation measures how often answer engines recommend a brand, not just whether they mention it. Learn how to track and improve it.
Measurement
AI can name your brand and recommend a rival in the next sentence. The Recommendation Score grades every AI answer 0-100 on how favorably it positions you across ChatGPT, Gemini, Perplexity, Google AI Overviews and Claude, plots you against every competitor, and shows the verbatim line behind every point.
Citation & Source Influence
Getting cited as a source and getting recommended as the pick are two different AI-search outcomes, and they are decoupling. Why most teams track the wrong one, what a 100-query study and our own 5-engine data show, and the KPI to measure instead.
Measurement
Your CEO wants AI visibility on the dashboard and your gut says vanity metric. It is - if you track raw rank on vanity prompts. Here are the three conditions that turn it into a leading indicator, a CEO-ready reporting template, and an illustrative 100%-vs-0% scenario that proves the point.
Free · No credit card
Start free with a ChatGPT visibility read, then add multi-engine tracking, Corporate Context governance, and the action-to-result loop when you are ready.