Application analytics

Return-User Signal Study

Rebuild retention cohorts from raw history and isolate early behaviours that actually predict returning users.

₩3,800,000 · 3-week study

Printed charts and data tables arranged on a desk

Retention charts move for reasons that have nothing to do with product quality: SDK upgrades, timezone mishandling, silent user-id changes, or onboarding renames that break day-one events.

This study rebuilds cohort definitions, checks identity continuity, and tests early-session behaviours against return rates—with explicit limits on what the sample can prove.

You leave with behaviours worth protecting, artefacts to stop treating as insights, and a cohort outline your analysts can maintain.

Typically included

  • Cohort definition rebuild
  • Identity continuity checks
  • Behaviour predictor shortlist
  • Analyst handoff notes

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