Objectives

  • Identify friction points in onboarding, search, and checkout.
  • Improve AI recommendations by understanding user preferences and behavior.
  • Track retention and repeat rentals to validate trust and usefulness.

Key Segments

Dimension Examples
User typeRenter vs Owner
DemographicsAge, location (city/zip), hobby/interest
BehaviorFirst-time, frequent renters, high-value items, niche categories
Device & localityMobile vs desktop; neighborhood demand

Hyper-local segmentation helps prioritize availability and improve matching.

Funnel Metrics

Stage What to track
Micro-conversionsSignup, listing creation, first message, wishlist/favorites
ConversionCompleted rental (goal), search→rental rate
RetentionRepeat rentals (30/90 days), churn for renters and owners
AcquisitionChannel mix, CPA, signup rate by source

Baseline targets: 2–5% marketplace conversion; 25–40% repeat usage within 90 days.

Tools & Reporting

Measurement tools
  • GA4 for traffic + behavior
  • In-app dashboards for recommendation performance
Reporting cadence
  • Weekly: micro-conversions, device usage, acquisition
  • Monthly: conversion, retention, hyper-local demand

Action loop: use findings to iterate onboarding, search UX, and trust signals.