DropDiag

Diagnose why users drop off at each conversion funnel stage with behavioral evidence

Analytics AIPaid

DropDiag investigates conversion funnel drop-offs by correlating user behavior patterns, session characteristics, error events, and qualitative survey responses at each funnel stage to diagnose root causes rather than just measuring rates. The tool categorizes drop-off reasons into actionable buckets—technical failures, UX friction, pricing hesitation, content gaps, and trust concerns—and estimates the revenue recoverable by addressing each category. Product teams use it to prioritize conversion optimization work while growth teams use it to build business cases for funnel experiments.

Key Features

• ✓Root cause diagnosis
• ✓Behavioral correlation
• ✓Revenue recovery estimates
• ✓Category classification
• ✓Evidence collection