Which mathematical model is most commonly used in retail to calculate Customer Lifetime Value (CLV) when accounting for variable purchase frequency and spending patterns?

In the world of retail mathematics, customer lifetime value (CLV) calculations are essential for strategic decision-making. Different mathematical models are used by data scientists to predict future purchasing behaviors and optimize marketing spend. This poll tests your knowledge about advanced mathematical approaches in retail analytics that drive profitability through precise customer valuation.

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Pareto/NBD (Negative Binomial Distribution) model
Basic RFM (Recency, Frequency, Monetary) scoring
Simple historical average calculation
Monte Carlo Markov Chain simulation