How captainmmd1304/user-funnel-and-drop-off-analysis works
This repository analyzes user-journey funnel data through both a command-line report and an interactive Streamlit dashboard. The main workflow loads stage events, computes conversion and drop-off metrics, and presents results; additional analyses cover time to convert, churn timing, segment comparisons, and chi-squared tests. The README also describes synthetic data generation, but the referenced generator is absent from the supplied tree, so it is not represented as an implemented component.
Main entry points: analysis.py CLI Runner · dashboard.py Streamlit App · user_funnel_data.csv Journey CSV
Components 17
Funnel Data
- Journey CSV
user_funnel_data.csv
CLI Analysis
- CLI Runner
analysis.py - CSV Loader
analysis.py - Funnel Metrics
analysis.py - Funnel Efficiency
analysis.py - Conversion Timing
analysis.py - Churn Analysis
analysis.py - Segmented Funnels
analysis.py - Chi-Squared Tests
analysis.py - CLI Charts
analysis.py
Interactive Dashboard
- Streamlit App
dashboard.py - Cached CSV Loader
dashboard.py - Device and Source Filters
dashboard.py - Dashboard Metrics
dashboard.py - Funnel Views
dashboard.py - Interactive A/B Test
dashboard.py
Other components
- Analyst
Connections 17
- Analyst → CLI Runner: runs
- CLI Runner → CSV Loader: loads
- CSV Loader → Journey CSV: reads
- Analyst → Streamlit App: opens
- Streamlit App → Cached CSV Loader: loads
- Cached CSV Loader → Journey CSV: reads
- CLI Runner → Funnel Metrics: calculates
- CLI Runner → Funnel Efficiency: calculates
- CLI Runner → Conversion Timing: calculates
- CLI Runner → Churn Analysis: analyzes
- CLI Runner → Segmented Funnels: plots
- CLI Runner → Chi-Squared Tests: tests
- CLI Runner → CLI Charts: plots
- Streamlit App → Device and Source Filters: filters
- Device and Source Filters → Dashboard Metrics: calculates
- Streamlit App → Funnel Views: renders
- Streamlit App → Interactive A/B Test: runs