App Pulse – Mobile App Analytics & Engagement Intelligence

Domain & Tools

Product Analytics / User Engagement Python, Pandas, Seaborn, Power BI, Google Colab

Techniques

• Cohort Analysis
• Retention & Churn Analytics
• User Segmentation
• Engagement Scoring

Overview

App Pulse analyzes mobile app usage data to understand user engagement, retention, and churn. The project transforms raw event logs into actionable insights for product teams, highlighting which cohorts stay, which leave, and which features drive long‑term usage.

Highlights

• Built cohort tables by signup month and tracked retention over time.
• Defined engagement tiers based on session frequency and feature usage.
• Identified churn‑prone segments using activity drop‑off patterns.
• Created Power BI dashboards for DAU/MAU, retention curves, and feature adoption.
• Delivered recommendations for onboarding, notifications, and feature prioritization.

Key Insight Summary

Early‑week engagement and feature discovery strongly predict long‑term retention. App Pulse shows how product analytics can guide UX, growth, and lifecycle strategy.

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