Порівняння методів

	NBD-Dirichlet Model	Пожиттєва цінність клієнта
Галузь	Маркетинг	Маркетинг
Родина	Regression model	Process / pipeline
Рік появи	1984	1996
Автор методу	Gerald J. Goodhardt, Andrew S. C. Ehrenberg & Christopher Chatfield	Robert Blattberg and John Deighton
Тип	Stochastic model of category purchase incidence and brand choice	Financial modeling methodology
Основоположне джерело	Goodhardt, G. J., Ehrenberg, A. S. C., & Chatfield, C. (1984). The Dirichlet: A Comprehensive Model of Buying Behaviour. Journal of the Royal Statistical Society: Series A (General), 147(5), 621-655.	Blattberg, R. C., Getz, G., & Thomas, J. S. (2001). Customer Equity: Building and Managing Relationships as Assets. Harvard Business School Press. ISBN: 978-0875847191
Інші назви	Dirichlet Model, NBD-Dirichlet, Goodhardt-Ehrenberg-Chatfield Model, Dirichlet Model of Buying Behaviour	CLV, LTV, Customer Value
Пов'язані	4	5
Підсумок	The NBD-Dirichlet model is the canonical stochastic model of repeat buying and brand choice in stationary, competitive consumer-goods markets. Introduced by Gerald Goodhardt, Andrew Ehrenberg and Christopher Chatfield in their 1984 Journal of the Royal Statistical Society paper "The Dirichlet," it integrates two processes: how often households buy in a product category, modeled by the negative binomial distribution (NBD), and how those purchases are split across competing brands, modeled by a multinomial-Dirichlet process. From just a few parameters, the model reproduces a remarkably wide set of empirical regularities, including each brand's penetration (how many people buy it), its buyers' purchase frequency, repeat-purchase rates, the share of category requirements each brand earns, and the duplication of purchase between brands. The model encodes Ehrenberg's classic 'laws' of buying behavior, most famously double jeopardy, whereby small brands suffer twice over by having both fewer buyers and slightly less loyal buyers. It assumes a stationary, non-partitioned market with brand choice that looks like sampling 'as if from an urn,' and it serves as a benchmark of what normal, no-loyalty-segmentation buying looks like, against which deviations such as genuine partitioning or excess loyalty can be detected.	Customer Lifetime Value (CLV) is a financial metric that quantifies the total profit a company expects to generate from its relationship with a customer over the entire duration of that relationship. Developed through work by Blattberg, Getz, and Thomas in the 1990s-2000s, CLV integrates acquisition costs, purchase behavior, retention rates, and margin information to estimate the net present value of each customer.