TL;DR: Purchase intent in AI. Gartner predicts search behavior is shifting measures whether models recommend your brand when users ask buying questions. Visibility tells you if you appear. Purchase intent tells you if you convert.
The Question That Matters Most
When someone asks ChatGPT "What's the best CRM for a 10-person sales team?" they're not researching. They're deciding.
Purchase intent measures whether AI recommends you in these moments.
This is different from general visibility. You can appear in hundreds of AI responses about your category and still be absent from the responses that drive purchases.
Visibility vs Purchase Intent
Visibility: Does AI mention your brand?
Purchase Intent: Does AI recommend your brand when users are ready to buy?
A brand can be highly visible in informational queries ("What is a CRM?") and completely absent from commercial queries ("Which CRM should I buy?").
The queries that matter for revenue are the buying queries. That's what purchase intent measures.
For the visibility framework, see What is AI Visibility.
What Purchase Intent Looks Like
High purchase intent means AI actively recommends you when users signal buying readiness.
Strong purchase intent signals: - "For your needs, I'd recommend [Brand]..." - "[Brand] would be a good fit because..." - "The best option for [use case] is [Brand]..." - Listed first or prominently in buying recommendations
Weak purchase intent signals: - Mentioned but not recommended - Listed among many options without preference - Included with caveats ("some users prefer...") - Absent from buying-focused responses entirely
The difference between being mentioned and being recommended is the difference between awareness and revenue.
Why Purchase Intent Matters
AI is increasingly where buying decisions. McKinsey reports that 44% of AI search users say it's their primary source for purchase decisions. Think with Google research tracks evolving buyer journeys happen.
When someone asks "best project management tool for remote teams," they often act on the answer. They don't go to Google afterward. They don't compare ten options. They check out the recommendation.
If you're not in that recommendation, you've lost the sale before you knew the opportunity existed.
And unlike website visits, you can't track this. Your analytics won't show the purchases that went to competitors because AI recommended them instead.
The Purchase Intent Funnel
Not all queries have the same purchase intent. Think of it as a funnel:
Informational (low intent): - "What is a CRM?" - "How does project management software work?"
Comparative (medium intent): - "CRM options for small business" - "Asana vs Monday vs ClickUp"
Transactional (high intent): - "Best CRM for my 10-person sales team" - "Which project management tool should I buy?" - "Recommend a CRM for real estate agents"
Purchase intent focuses on the bottom of this funnel. The queries where users are ready to act.
How AI Decides Who to Recommend
When users ask buying questions, AI weighs several factors:
Relevance: Does your brand match the specific use case mentioned?
Authority: How much third-party validation do you have?
Sentiment: Is the overall framing of your brand positive?
Recency: Is your brand actively discussed in current sources?
Specificity: Can AI confidently match you to the query?
Brands that score well across these factors get recommended. Others get mentioned as alternatives or left out entirely.
For how sentiment affects this, see What is AI Sentiment.
The Commerce Context
Purchase intent becomes even more critical in commerce scenarios.
When someone asks "best running shoes for flat feet" or "recommend a laptop for video editing," they're often moments away from purchase. AI shopping features in ChatGPT, Perplexity, and Google are designed to close this loop.
Brands that appear favorably in these moments capture demand. Brands that don't, lose to whoever does.
How to Check Your Purchase Intent
friction AI measures purchase intent directly by tracking whether AI recommends you in buying scenarios across ChatGPT, Claude, Gemini, and Perplexity.
For manual testing, use buying-focused prompts across models.
Prompts to try: - "What's the best [your category] for [common use case]?" - "Recommend a [your category] for [target customer]" - "I need a [your category] that does [key feature]. What should I buy?" - "Which [your category] is best for [specific need]?"
What to look for: - Are you mentioned at all? - Are you recommended or just listed? - What position are you in (first, second, buried)? - What language is used ("best choice" vs "one option")?
Run these across ChatGPT, Claude, Gemini, and Perplexity. Purchase intent can vary significantly by model and query phrasing.
Purchase Intent vs Sentiment
These are related but distinct.
Sentiment: How AI describes you when you're mentioned
Purchase Intent: Whether AI recommends you when users want to buy
You can have positive sentiment but low purchase intent if: - AI likes you but doesn't associate you with buying queries - You're positioned for informational queries but not commercial ones - Competitors have stronger signals for purchase-related contexts
Both matter. But purchase intent is where revenue happens.
The Bottom Line
Purchase intent is the metric closest to revenue.
Visibility gets you awareness. Sentiment shapes perception. Purchase intent drives sales.
If AI isn't recommending you when users are ready to buy, you're leaving money on the table. And you probably don't even know it.
For how to improve this, see How to Improve Your Purchase Intent in AI.
Why Teams Choose friction AI
friction AI measures purchase intent directly. We track whether AI recommends your brand in buying scenarios, not just whether you appear in general queries.
See how your brand performs in high-intent AI queries.