Full Stack Analysis project demonstrates a complete, production-grade analytics pipeline that transforms raw user data into actionable business intelligence. Starting from a normalized MySQL database with 10,000 users and 51,000+ events, the analysis identifies a critical feature adoption bottleneck and quantifies a $570K/year revenue opportunity through A/B testing and statistical validation.
Problem Identified:
10K users showed 70% activation (healthy) but only 35% adopted core features. Time-to-value analysis revealed gap: activation 1.1 days → feature discovery 11 days.
Hidden revenue leak: ₹200K+/year in unrealized upgrades.
This project delivers a complete Product-Led Growth (PLG) analytics framework for a SaaS platform. Most SaaS businesses generate large amounts of product usage data but lack clarity on where users drop in the journey, which features actually drive revenue, and which experiments materially improve conversion.
This solution converts raw event logs into actionable intelligence by mapping the end-to-end user journey:
The results reveal that while activation is strong (70%+), major drop-off occurs at feature adoption and monetization, making mid-funnel engagement the primary growth opportunity. Tested interventions demonstrate revenue lift exceeding $500K/year, confirming the business impact of PLG optimization.
Problem Solved