Benchmark module · Use case
Benchmark against competitors in AI search
You know a competitor gets recommended more often than you do, but you cannot prove it or quantify the gap. Recommendation Share™ measures how often each named competitor appears against you for the same buying-intent prompts, engine by engine.
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How do you benchmark against competitors in AI search?
Recommendation Share™ measures how often each named competitor appears against you for the same buying-intent prompts, engine by engine. The work runs in four steps: name the competitors you actually lose deals to; run identical prompts for every brand in the set; calculate recommendation share™ per engine and per prompt; track the gap over time and attribute movement to specific changes. A share-of-voice number for AI answers, with the specific prompts where you are losing.
Key facts
- Job to be done
- Benchmark against competitors in AI search
- Platform module
- Benchmark
- Typical owner
- Competitive intelligence and marketing leadership
- Available from
- Growth — $119 / month
- Engines covered
- ChatGPT, Gemini, Claude, Perplexity, Copilot, Grok
- Outcome
- A share-of-voice number for AI answers, with the specific prompts where you are losing.
The problem
You know a competitor gets recommended more often than you do, but you cannot prove it or quantify the gap.
This is not a reporting inconvenience — it is a measurement gap. AI answers are generated fresh each time and vary between sessions, so anecdotal checks cannot establish a trend and cannot prove whether anything you changed made a difference.
How Geosystems AI handles it
Recommendation Share™ measures how often each named competitor appears against you for the same buying-intent prompts, engine by engine.
- Name the competitors you actually lose deals to.
- Run identical prompts for every brand in the set.
- Calculate Recommendation Share™ per engine and per prompt.
- Track the gap over time and attribute movement to specific changes.
What you get
Everything below lands in your private workspace and is exportable as PDF or CSV, so the evidence travels with the decision.
| Output | What it contains |
|---|---|
| Recommendation Share™ | Your share of mentions versus named competitors |
| Per-prompt breakdown | Exactly which questions you lose and to whom |
| Engine comparison | Where a competitor is strong and where they are not |
| Movement report | How the gap changes after each intervention |
What good looks like
A share-of-voice number for AI answers, with the specific prompts where you are losing.
The measurement backbone is the same across every use case: GVI™ scores each answer on Presence, Prominence, Attribution, and Accuracy, while Recommendation Share™ places that score against the competitors you name. Both are re-run on a schedule so movement is a trend, not a screenshot.
Benchmark against competitors in AI search
Start with a free AI Visibility Scan and get the baseline this use case builds on — a GVI™ score across all six AI engines, plus every inaccuracy currently in circulation.
Frequently asked questions
Who typically owns this inside a company?
Competitive intelligence and marketing leadership. In smaller teams it usually sits with whoever owns demand generation, because the impact lands on pipeline first.
Which plan do I need?
Growth — $119 / month. Starter is $59 per month, Growth is $119 per month, and Scale is $199 per month. Annual billing is discounted.
Does this cover every AI engine?
Yes — ChatGPT, Gemini, Claude, Perplexity, Copilot, and Grok are all tracked on the same prompt set, so results are directly comparable between engines.
How do I try it before subscribing?
Run the free AI Visibility Scan at /free-ai-visibility-check. It returns a GVI™ baseline across all six engines with no account required.