When buyers ask AI who to choose,does your brand make the shortlist?
Pendulu measures recommendations across ChatGPT, Gemini, Perplexity and AI search. See who wins, which sources influence the answer, why you lose visibility and what to fix first.
Recommendation benchmark
Acme vs market
Highest-leverage gap
Competitor A is repeatedly recommended on high-intent comparison prompts and supported by stronger third-party citations.
Priority: fix evidence coverage, then retest.
Across AI engines
Not a ChatGPT-only tracker.
Buyers switch between answer engines. Pendulu is designed around the recommendation layer itself: the same commercial questions, compared across multiple AI systems.
What Pendulu measures
The metrics behind AI recommendations.
Recommendation rate
How often your brand makes the shortlist
Share of answer
How much recommendation space you own vs competitors
Primary position
How often AI puts you first
Citation share
Which sources are supporting the answer
Buyer-intent visibility
Visibility on prompts closest to purchase
Competitor displacement
Where another brand replaces you
Decision layer
Measure → Explain → Prioritize → Fix → Retest.
A visibility score is not enough. Pendulu turns recommendation gaps into ranked actions, then measures whether the change actually moved the result.
- 01MeasureRun buyer-intent prompts across AI engines.
- 02ExplainInspect recommendation patterns and citations.
- 03PrioritizeRank the gaps by commercial impact and confidence.
- 04FixChange the highest-leverage evidence and content gaps.
- 05RetestMeasure whether AI recommendation behavior actually changed.
Start with evidence