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

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.

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

New Bridge is an Enterprise Revenue Governance and Decision Science Framework demonstrating how SaaS organizations can connect revenue realization, forecast governance, enterprise risk management, recovery planning, capital allocation, and executive decision-making into a unified governance model.

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.

End-to-end Product Analytics portfolio with real-world projects using SQL, Python, Excel, and BI dashboards (Power BI & Tableau). Includes datasets, case studies, KPI frameworks, and decision-focused analysis.

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

Business Intelligence analysis of SaaS customer acquisition patterns and data quality audit using Python and Pandas.

The Early Churn Intelligence analyzes user behavior patterns over time to: - Detect early signs of disengagement - Assign a churn risk score - Estimate the likely time window in which the user may churn

Local SaaS analytics warehouse built with dbt and DuckDB, modeling synthetic HubSpot, Stripe and product event data into CRM, billing and revenue marts.

Auto-generate invoices, send reminders, track payments, and flag overdue accounts. Get paid faster with zero manual follow-up.

Open-source MCP server for Claude AI with Stripe and Supabase integration for SaaS analytics, churn analysis, subscription tracking, and revenue insights using natural language

AI-powered self-service analytics dashboard for SaaS platforms. Features comprehensive metrics (MRR, CAC, LTV, Churn), natural language queries with Claude AI, automated anomaly detection, and interactive visualizations. Built with Streamlit, Pandas, and Plotly.

SaaS Subscription & Churn Analytics | SQL Server + Power BI | 40+ queries across 4 complexity levels | MRR, ARR, churn drivers, feature usage, support impact | 3-page interactive dashboard built on normalized relational database.

Pipeline de dados end-to-end para analytics de RevOps em uma empresa SaaS B2B fictícia, com Python, BigQuery, dbt, Airflow e Power BI.

📈 A machine learning pipeline for SaaS revenue forecasting using time-series regression, Optuna hyperparameter tuning, and SHAP-based model explainability.

B2B SaaS product analytics: activation funnels, cohort retention, churn, and A/B testing (z-test framework) on 1.4M+ product events. SQL + DuckDB + Python (statsmodels) + multi-page Streamlit dashboard.

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.