Arrow Use scenario-based proof modules
Group feedback by buyer segment and trip type to reduce ambiguity for AI engines and human readers.
- Family trips
- Corporate events
- Long-route charters
Evidence stack
Turn testimonials into evidence buyers can cite
Generic review sections underperform. We organize proof into scenario-based pages, making confidence signals easier to extract and compare.
Trust layertestimonial relevance
GEO readinessproof freshness
Lead qualityAI answer lift
Pair each claim with context
Attach dates, constraints, and explicit boundaries to every proof block.
- Date stamps
- Outcome scope
- Scope restrictions
Execution system
Proof taxonomy
Classify feedback by intent, not by source alone.
Permission workflow
Only publish evidence where rights and consent are clear.
SEO + GEO structure
Use consistent section headings and FAQ links to improve discoverability.
Optimization
Retire stale proof and replace with higher-signal proof quickly.
Frequently asked questions
Can all reviews be used?
Only those that are genuine, consented, and context-rich enough for decision support.
Do we need verified buyer permission?
Yes, especially for identifiable stories and imagery.
How do we measure proof impact?
Track citation quality in AI answers and inbound lead maturity over time.
Related: Trust signal playbook · Broker trust visibility · Trust layer service