For a retailer, it’s extremely useful to know whether a customer will be back or has abandoned you for good. Starting in the late 1980s, academic researchers began to develop sophisticated predictive techniques to answer that question. The best-known is the Pareto/NBD (for negative binomial distribution) model, which takes a customer’s order history and sometimes other data points, then simulates whether and how much she will buy again.
When a Simple Rule of Thumb Beats a Fancy Algorithm
In prediction, sometimes less is more.
October 02, 2014
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Practical ways to improve your decision-making process.