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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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.
Objective: Forecast monthly merchant revenue across 50 merchants (5 years of data) and compare multiple forecasting methods.
Free educational tool for small businesses to plan revenue, costs, and cash flow through scenarios and forecasting
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