This project simulates a real-world SaaS analytics dashboard to monitor business performance metrics like Monthly Recurring Revenue (MRR), Churn Rate, and Customer Lifetime Value (LTV). Built in Python and Google Colab, it uses mock data to demonstrate how product teams can track subscription performance and make data-driven decisions.
Product managers and analysts often rely on clean, clear KPIs to measure growth. This notebook generates mock customer data, processes key SaaS metrics, and visualizes revenue trends to simulate how a startup might monitor its B2B product performance.
🎯 Focus Areas:
- Translating customer activity into actionable KPIs
- Simulating business insight from raw data
- Laying the groundwork for a future Streamlit dashboard
- MRR Calculation: Monthly revenue from active subscribers
- Churn Rate: Customer loss % for a selected month
- LTV Estimate: Average lifetime value per customer
- MRR Trend Visualization: Line chart showing revenue growth
- Clean, commented Colab notebook: Easy to follow and extend
- Python: Core logic and metric functions
- Pandas: Data wrangling and calculations
- Matplotlib: Visualization
- Google Colab: Development environment