Which mathematical model revolutionized retail customer lifetime value calculations in the 2010s by incorporating machine learning to predict future purchase probability?

In today's data-driven retail landscape, mathematical models have transformed how businesses understand customer lifetime value (CLV). These sophisticated algorithms analyze purchasing patterns, frequency, and spending habits to predict future customer behavior with remarkable accuracy. The evolution of these predictive models represents one of the most significant advancements in retail customer analytics, helping businesses make strategic decisions about marketing investments, personalization strategies, and loyalty programs.

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The Pareto/NBD (Negative Binomial Distribution) Model
The RFM (Recency, Frequency, Monetary) Analysis Framework
The BG/NBD (Beta-Geometric/Negative Binomial Distribution) with Random Forest Extensions
The Markov Chain Monte Carlo (MCMC) Basic Attribution Model