The AI-era metric
Share of Model: the only metric that matters in AI search
Share of Model is how often AI mentions or recommends your brand for the buying questions that matter. Track it by model, compare it with competitors, then act on the signals holding you back.
Definition
What Share of Model measures
The percentage of AI-generated answers that mention or recommend your brand when the AI is asked a buying-intent prompt in your category. Tested per model, then averaged.
Formula
SoM = ( responses_with_brand_mention
÷ total_buying_intent_prompts )
× 100Composite SoM averages the per-model score across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews. Outrigger also tracks a recommended sub-score (positive sentiment + actionable phrasing) and a linked sub-score (your URL appears as a citation).
Why Share of Model replaces keyword rank
One answer, not ten
Google gave 10 blue links per query. AI gives one paragraph. There's no scroll. You're in the answer or you're invisible.
Multiple models, no overlap
The five AI experiences don't agree — a brand ChatGPT cites can be invisible on Gemini. Per-experience SoM gives you the honest read.
Buyer behavior already shifted
65.9% of businesses are invisible to AI (our study of 1,004 businesses). If your category buyers ask AI, your visibility metric is SoM. If they ask Google, it's still keyword rank. Most categories are now both.
Benchmark distribution
What a good Share of Model score looks like
From the Outrigger AI Visibility Index — our published study of 1,004 businesses.
Invisible
0–5%
65.9% of businesses sit here (n=1,004)
Emerging
5–25%
Early, inconsistent presence
Recognized
25–60%
Mentioned but rarely the top pick
Category leader
60–95%
Recommended in most answers
Five levers that move Share of Model
Ranked by measured leverage in our published research — not guesswork.
01
Entity & directory sync
Directory presence correlates with AI visibility at r=0.391
02
Cited-source placement
Presence in the sources AI cites shows a 5.5× lift
03
Review velocity
G2, Trustpilot, Google, Capterra
04
Press coverage
Outlets AI cites — not PR-wire churn
05
Technical GEO
Schema, structured data, robots.txt
Share of Model FAQ
What is Share of Model?
Share of Model (SoM) is the percentage of AI-generated answers that mention or recommend your brand when an AI experience is given a buying-intent question in your category. Outrigger measures ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews separately, then rolls all five into a composite view.
How do you calculate Share of Model?
Share of Model = (number of AI responses where your brand is mentioned) ÷ (number of buying-intent prompts tested) × 100. Outrigger's AI Monitor tests buying-intent prompts across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews. The composite SoM is the average across all five experiences. We also break out 'mentioned only' vs 'recommended' vs 'recommended with a link cited' for finer-grained tracking. Prompt volume and monitoring cadence depend on your plan.
Why is Share of Model better than keyword rank?
Keyword rank measures whether you're in a list of 10 blue links on Google. Share of Model measures whether you're in the actual answer the buyer reads. With AI, there's often only one recommendation — the buyer doesn't scroll to the next result. Either you're in the answer or you're not. Share of Model captures that binary in a way keyword rank can't.
What's a good Share of Model score?
A useful score is relative to your own market, prompt set, and starting baseline. In our study of 1,004 businesses, 65.9% appeared in none of the answers across the five systems tested. Compare your score with the competitors buyers actually consider, then track whether the same prompt set improves over time.
How do you increase Share of Model?
Five levers recur in our observational research: directory and entity presence; inclusion in sources AI answers cite; review momentum; relevant press coverage; and technical GEO such as schema and structured data. These are associations, not guaranteed causes. Outrigger identifies the gaps, ranks the next moves, and prepares the work for review.
How often should you measure Share of Model?
Weekly monitoring gives most teams a useful balance between signal and noise. Scan volume depends on the plan and prompt set, and every run uses credits. The important part is using a consistent prompt set so the change over time is comparable.
See your Share of Model in 2–3 minutes
Free audit tests your brand across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews. Composite SoM, per-model breakdown, and your top three improvement levers. Then move the number — paid plans pair monitoring with prepared workflows, with capabilities that vary by tier.