End-to-end sales revenue forecasting with business decision insights using Python, SQLite, and Streamlit
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Updated
Dec 22, 2025 - Python
End-to-end sales revenue forecasting with business decision insights using Python, SQLite, and Streamlit
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Objective: Forecast monthly merchant revenue across 50 merchants (5 years of data) and compare multiple forecasting methods.
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.
Engineered a BI framework to drive growth and operational efficiency. Segmented 90+ customers for churn mitigation, audited logistical ROI to optimize shipping costs, and automated margin protection for discontinued inventory. Delivered actionable KPIs for sales attribution and revenue forecasting using 830+ order records.
Free educational tool for small businesses to plan revenue, costs, and cash flow through scenarios and forecasting
Data-driven SaaS pricing optimization using ML to maximize LTV/CAC ratios. Employs Random Forest, clustering, and elasticity analysis on 4,222 customers to recommend tiered pricing strategies that balance revenue growth with sustainable churn rates.
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