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Pareto/NBD Model/Bukti
Catatan bukti metode

Pareto/NBD Model

The Pareto/NBD model is the foundational buy-till-you-die model of customer-base analysis, answering the question of which customers are still active and how many transactions they will make in the future from a non-contractual purchase history. Introduced by David Schmittlein, Donald Morrison and Richard Colombo in their 1987 Management Science paper "Counting Your Customers," it combines two stochastic stories: customers buy according to a Poisson process while alive, and each customer has an unobserved lifetime after which they are permanently inactive. Purchasing rates vary across customers by a gamma distribution, producing the negative binomial (NBD) for counts, and dropout rates also vary by a gamma distribution, producing a Pareto distribution of lifetimes, which gives the model its name. Unlike later discrete-dropout variants, the Pareto/NBD allows a customer to become inactive at any instant in continuous time, not only after a purchase. From only each customer's recency, frequency and tenure, the model yields a probability that the customer is still alive and an expectation of their future buying. Its main cost is computational: estimation involves Gaussian hypergeometric functions and careful numerical integration, which historically made it hard to apply.

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Catatan sumber

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Pareto / Negative Binomial Distribution (Pareto/NBD) Customer-Base Analysis Model
Catatan metode taksonomi · regression-model / marketing
  • Schmittlein, D. C., Morrison, D. G., & Colombo, R. (1987). Counting Your Customers: Who Are They and What Will They Do Next? Management Science, 33(1), 1-24. · DOI 10.1287/mnsc.33.1.1
  • Fader, P. S., Hardie, B. G. S., & Lee, K. L. (2005). "Counting Your Customers" the Easy Way: An Alternative to the Pareto/NBD Model. Marketing Science, 24(2), 275-284. · DOI 10.1287/mksc.1040.0098
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Taxonomic bucketBG/NBD Modelmachine-suggested · Relational suggestion, not evidence.Used in the same domainCustomer Lifetime Valuemachine-suggested · Relational suggestion, not evidence.Same method familyGamma-Gamma Spend Modelmachine-suggested · Relational suggestion, not evidence.Used in the same domainRFM Analysismachine-suggested · Relational suggestion, not evidence.

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