I’m by no means an expert on BG/NBD models, but generally, if you have access to more data (and more predictors as you’ve alluded here), I think you have the opportunity to create a more robust model by capturing variability at different hierarchies of the data and with partial pooling. Training different models for different types of customers would be appropriate if you believe there’s nothing to be gained from sharing information across customer segments. But if there are common purchasing patterns across groups, a hierarchical model with pooling would be beneficial. I’m sure others can address BG/NBD more specifically.
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