Which mathematical model is most commonly used in advanced retail analytics to predict customer lifetime value when accounting for varying purchase frequencies and time-dependent behaviors?

Customer Lifetime Value (CLV) is a critical metric in retail mathematics that forecasts the total revenue a business can expect from a single customer throughout their relationship. Advanced mathematical models have revolutionized how retailers calculate and leverage CLV for strategic decision-making. This poll tests your knowledge about the mathematical foundations behind modern CLV calculations in retail analytics.

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Pareto/NBD (Negative Binomial Distribution) Model
Simple Linear Regression Model
Monte Carlo Simulation without Markov Chains
Basic RFM (Recency, Frequency, Monetary) Scoring without Probabilistic Components