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Statistical Methods in Customer Relationship Management
book

Statistical Methods in Customer Relationship Management

by V. Kumar, J. Andrew Petersen
September 2012
Intermediate to advanced
286 pages
8h 7m
English
Wiley
Content preview from Statistical Methods in Customer Relationship Management

3.2 Response Probability

The first issue in customer acquisition is to model the probability of prospects being acquired. Hansotia and Wang [5] argued that prospects' response likelihood varies based on their profiles and the promotional materials they received. The authors adopted a logistic regression to model prospects' probability of response and used prospect profile variables as predictors. In logistic regression, because we can only observe whether the prospects respond or not, a latent response variable img indicating unobserved utility is assumed. Thus, img is usually defined such that

(3.1) equation

where img the acquisition of customer i (1 = acquired, 0 = not acquired) and img = a vector of covariates affecting the acquisition of customer i. The probability that the prospect responds is given by

(3.2) equation

For a logistic regression, has a logistic distribution, with mean 0 and variance equal to /. The ...

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