Business question: What are your practices for using the BG/NBD model in terms of size of training, and how you scale to larger datasets?

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Fitting with model.fit(fit_method=‘map’) allows us to scale sufficiently. I can train 100k in about 6 seconds and 1 million in about 20 seconds.

Here’s a related question. If I have 20 million customers, would you recommend I train the model on all of them, or train on a representative sample of say 1 million or 5 million customers then apply that model output to the out-of-sample customers?

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