SQL analysis of marketing channels (LTV, CAC, Payback, retention)
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Apr 8, 2026
#
ltv-cac-ratio
Here are 8 public repositories matching this topic...
Python cohort retention & LTV:CAC analysis (synthetic e-commerce): heatmaps + channel unit economics (HTML/PDF report).
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Jan 17, 2026 - Jupyter Notebook
A system dynamics engine that models compounding cohort decay to help users predict future user retention, estimate required marketing or network subsidy costs, and model value extraction across different business models like SaaS, Web3 networks, and autonomous AI economies.
pandas saas predictive-analysis web3 system-dynamics phython ai-agents dau growth-engineering ploty streamlit ltv-prediction ltv-cac-ratio ltv-analysis retention-modeling cohort-an
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Aug 6, 2026 - Rust
Auditoría estratégica de ROI y Unit Economics para la plataforma Showz. Identificación de ineficiencias críticas en la captación de usuarios y optimización de la rentabilidad operativa mediante el análisis profundo de LTV, CAC y ROMI.
python customer-retention eda pandas business-intelligence cohort-analysis marketing-analytics pyarrow roi-analysis unit-economics data-driven-intelligence ltv-cac-ratio
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Feb 17, 2026 - Jupyter Notebook
Comprehensive unit economics analysis for a manufacturing company. Upgraded, corrected, and expanded edition of the original project.
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Apr 30, 2026
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.
python data-science machine-learning random-forest scikit-learn jupyter-notebook saas business-intelligence data-analysis predictive-analytics churn-prediction k-means-clustering customer-segmentation customer-analytics price-elasticity pricing-strategy pricing-optimization saas-metrics revenue-forecasting ltv-cac-ratio
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Aug 8, 2026 - Jupyter Notebook
Descriptive and formula-based predictive CLV analysis, revealing how survivorship bias inflates historical customer value estimates for high-churn segments. Built with Python, DuckDB, SQL, and pandas.
data-science sql jupyter-notebook pandas data-analysis customer-lifetime-value clv-analysis ltv-cac-ratio ltv-analysis
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Aug 5, 2026 - Jupyter Notebook
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