saas-analytics

A web + mobile app (PWA) with Stripe integration for forecasting SaaS revenue

End-to-end Data Analyst portfolio featuring 5 projects across SaaS, A/B testing, ecommerce, marketplace, and customer journey analytics. Showcases SQL, Python, Power BI, Tableau, Excel, data cleaning, ETL, statistical testing, KPI validation, and actionable business insights.

SaaS metrics in a nutshell

End-to-end SaaS revenue and churn analytics project using Python, SQL, and Power BI to uncover subscription growth, MRR/ARR trends, cohort retention, churn drivers, and customer revenue risk.

End-to-end SaaS churn analytics platform — MySQL data pipeline, Tableau executive dashboard, and a LightGBM machine learning model with a Streamlit app to flag at-risk customers before they cancel

Board-Level Decision Intelligence Operating System. A future-state enterprise operating model for governing forecast confidence, commercial risk, recovery investment, capital allocation, and executive decision-making under uncertainty.

🚀 End-to-end SaaS Product Analytics project using Python, PostgreSQL, and Power BI to analyze user growth, engagement, revenue, churn, marketing, and customer health.

End-to-end Product Analytics portfolio using SQL, Python, Excel, and BI. Features 6 real-world-style projects covering funnels, SaaS, user journeys, retention, revenue, Salesforce, experimentation, product insights, and business decision-making.

Open-source, cookieless revenue analytics. A self-hosted DataFast alternative that shows which traffic source makes you money. Polar and Dodo Payments built in, free on Cloudflare.

24-month SaaS subscription retention engine constructing triangular monthly cohort matrices and modeling LTV:CAC unit economics in SQL and Python.

SaaS Expansion Scenario Model using real Datadog FY2025 data. SQL + Financial Modeling.

End-to-end SaaS customer churn and revenue risk analysis using Python, Pandas, and Power BI to identify churn trends, At-Risk MRR, high-value customer segments, and retention priorities.

End-to-end SaaS analytics project using SQL and Power BI to clean and analyze subscription data, measuring customer lifetime, churn behavior and customer lifetime value (CLV) to identify revenue drivers and retention opportunities.

Production-grade Causal AI engine that replaces flawed churn prediction with uplift meta-learners to target true Persuadables. Simulates enterprise SaaS revenue recovery, eliminates spend on Sure Things, and protects revenue from Sleeping Dogs.

End-to-end SaaS customer retention, churn and revenue analytics using Python, SQL, MySQL and Power BI.

Executive product analytics case study diagnosing why efficient SaaS growth breaks without retention durability, and why Enterprise-led strategy outperforms volume-led acquisition.

Demonstrates practical data analysis using Python for exploration and Power BI for delivering business-ready, interactive insights.

Revenue and product analytics with tested dbt metrics for churn, retention, and usage, plus Power BI project source.

Official MCP connection and discovery repository for Revinho business intelligence