An exploratory analysis of user engagement and churn patterns in the Waze app, highlighting factors that influence retention and identifying opportunities for churn mitigation.
- Cleaned and explored user activity data (drives, recency, weekend behavior)
- Investigated missing values and removed unlabeled rows
- Engineered features:
Time to Unicorn,Funding (M),days_since_last_trip - Visualized user churn vs retention and correlations with activity
- Summarized key behavioral indicators associated with churn
- Churn rate is ~72%, indicating potential engagement challenges or aggressive churn definition
- Recent activity and total drive count are highly correlated with retention
- Weekend usage may signal habitual users more likely to stay active
- The dataset skews toward newer users with low drive counts
👉 Read the full project breakdown on Notion
Includes:
- Business takeaways
- Visual summaries
- Stakeholder-oriented interpretation