How iyadidier/customer-churn-retention-analytics works
StreamPlus is a customer churn and retention analytics project. Its main workflow inspects and cleans customer data, analyzes churn and segments, assigns explainable risk levels, then produces reports and visualizations for retention review. README documents notebooks and SQL as analysis stages; sampled Python confirms the reporting and visualization scripts read the processed dataset and write outputs. Source for notebooks and SQL was not sampled, so their internal calls and detailed wiring are not inferred.
Main entry points: processed Processed customers · reports CSV reports · database SQLite database · raw Raw customer data
Components 17
Data preparation
- Raw customer data
data/raw - Data exploration
notebooks/01_data_exploration.ipynb - Data cleaning
notebooks/02_data_cleaning.ipynb - Processed customers
data/processed
Churn analysis
- Churn analysis
notebooks/03_churn_analysis.ipynb - Risk scoring
python/generate_reports.py - Customer segments
sql/customer_segments.sql
Decision outputs
- Report generation
python/generate_reports.py - CSV reports
reports - Visualization export
python/export_visualizations.py - Churn charts
visualizations - Result validation
python/validate_results.py
SQL analytics
- SQLite schema
sql/schema.sql - SQL churn analysis
sql/churn_analysis.sql - SQLite database
database
Other components
- Dataset provider
- Retention decision-makers
Connections 16
- Dataset provider → Raw customer data: provides data
- Raw customer data → Data exploration: inspected by
- Data exploration → Data cleaning: informs cleaning
- Data cleaning → Processed customers: writes dataset
- Processed customers → Churn analysis: analyzed by
- Processed customers → Report generation: read by
- Report generation → CSV reports: writes CSVs
- Processed customers → Visualization export: read by
- Visualization export → Churn charts: writes charts
- Processed customers → Result validation: read by
- CSV reports → Result validation: validated by
- CSV reports → Retention decision-makers: supports review
- Churn charts → Retention decision-makers: supports review
- SQLite schema → SQLite database: defines schema
- SQLite database → SQL churn analysis: queried by
- SQLite database → Customer segments: queried by