Let's assume Customer Lifetime Value (CLV) is defined as
average basket x
Option A is to build model predicting CLV for each customer.
Option B is to model customer's basket size and frequency, each via separate models and multiply the results at the end.
Is there any mathematical reason why one would select B over A? E.g. would option B reduce variance of the CLV because it is an ensemble of two models?