Scientific validation framework with statistical rigor and investor-grade reporting
Standardized, comparable metrics that translate user behavior into investment signals
Retention 40% + Task Success 30% + UX Severity 30%
Composite validation metric combining behavioral and qualitative signals
% of testers completing task correctly
Measures usability and flow effectiveness
% change in retention between rounds
Tracks improvement in user engagement over validation cycles
Incidents per 1,000 sessions
Technical stability and reliability indicator
% moving between key steps
Measures conversion effectiveness across critical user journeys
We recommend minimum sample sizes based on validation goals to ensure statistical significance and reliable insights.
Core flow validation and bug identification
Cohort analysis and behavioral patterns
Distribution simulation and investor signals
Statistical Rigor: We compute confidence intervals for behavioral metrics and annotate results with statistical significance levels.
Advanced behavioral analytics combining session replays, interaction patterns, and event telemetry to identify optimization opportunities.
Full user journey recordings with interaction timeline
Aggregated click patterns and interaction hotspots
Content engagement and attention metrics
Task completion efficiency and friction points
Drop-off Identification: Event telemetry combined with session data pinpoints exact moments where users abandon flows.
All metrics are presented with confidence intervals, statistical significance annotations, and comparative benchmarks. Reports include executive summaries, KPI dashboards, and evidence attachments suitable for due diligence.