Share of Recommendation
A metric measuring how frequently an AI answer engine recommends your brand relative to competitors.
Overview
Share of Recommendation tracks the percentage of relevant AI-generated answers that include your brand recommendation compared to all competitors.
Defining Share of Recommendation
Share of Recommendation (SoR) is the primary metric for AI visibility. It measures the frequency with which AI answer engines recommend your brand relative to all competitors for relevant queries.
Why SoR replaces traditional rankings
In the AI era, users do not see ranked lists — they see synthesized answers. The question is not "where do we rank?" but "how often are we recommended?" SoR directly measures the competitive metric that matters.
Calculating Share of Recommendation
Query AI platforms with representative questions from your industry. Track which brands appear in the recommendations. Your SoR is the percentage of recommendations that include your brand divided by total recommendations across all competitors.
Related Guides
Answers
Frequently Asked Questions about Share of Recommendation
How do you measure Share of Recommendation?
By querying AI platforms with relevant questions in your industry and tracking how often your brand is recommended versus competitors. This requires systematic, repeatable testing across platforms.
What is a good Share of Recommendation?
Benchmark against the competitors the engines already name beside you, not against an absolute figure. What matters is the direction of travel between two runs of the same prompt set, and whether the brands ahead of you are the ones you actually compete with.
The first move
Find out how six answer engines describe you.
The free AI Visibility Audit reports what ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude and Copilot say about your brand today — and where the gaps are.
- Platform-by-platform visibility snapshot
- Entity clarity assessment
- Competitor comparison
- Prioritized actions