The Waze data team is currently developing a data analytics project aimed at increasing overall growth by preventing monthly user churn on the Waze app. For the purposes of this project, churn quantifies the number of users who have uninstalled the Waze app or stopped using the app.
The following project is composed of four parts of the PACE Model consisting of Plan, Analyze, Construct and Execute.
The goal of this project is to reduce churn and improve user retention. By identifying users who are at risk of churning and offering them personalized incentives, Waze can prevent these users from leaving the platform. This will help Waze to maintain its user base and grow its business.
| Stage | Tasks | Deliverables |
|---|---|---|
| PLAN | Establish Workflow Structure (PACE), Establish Project Goals | Global-level project document |
| ANALYZE | Compile Summary information regarding the data, Data Exploration, Cleaning, Visualizations, Compute for Descriptive Statistics | Data is ready for EDA, EDA Report, Tableau Visualizations (if needed), Summary of Statistical Tests |
| CONSTRUCT | Run Statistical Tests, Hypothesis Testing, Determine what Model is applicable given the data, Feature Engineering (prepare the data for modeling), Build Model | Analysis of testing results between two important variables, Working Model for Evaluation, Determine if model is successful |
| EXECUTE | Communicate findings to stakeholders | A report that adheres to properly communicating findings to any kind of audience. |