Alternative-data methods for independent TMT research: entity resolution, panel measurement, pipelines, and dashboards.
Python toolkit for simulating SaaS subscriptions and analyzing business metrics using the Razorpay API in test mode
This model Generates 2 years of synthetic user subscription and revenue event data for cohort retention analysis. It builds weekly and monthly cohort tables from subscription event data then computes retention curves, churn rates, and Net Revenue Retention (NRR) from the cohort tables.
Python CLI to fetch all Chargebee account data and run rule-based subscription analytics: churn prediction, revenue forecasting, CLV, customer segmentation, payment failure detection, anomaly detection, and more.
Cohort-driven subscriber forecasting with Weibull survival, SARIMA gross adds, and cohort stacking
Auditable subscription contribution and portfolio P&L analytics for fees, benefit costs, renewal, sensitivity, and executable SQL.
Retention, CAC payback and cohort analysis on 9,300 gym subscribers: 42% retained at month 3, 12% at month 12, 2024 cohort CAC recovered by month 7
RevenueCat Charts API analytics
Customer retention and churn analysis project using SaaS subscription data. Includes cohort analysis, churn patterns, customer lifetime trends, dashboard visuals, and business recommendations.
B2B SaaS analytics platform covering subscriptions, recurring revenue, billing, product adoption, retention, customer success and experimentation.
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