I am building a model of customer spending, and need some help to identify the best way of doing this.
(1) I have an exponential distribution for each customer's spending (2) Bernoulli distribution for whether or not that customer comes at all
For each marketing campaign (a couple of thousand customers) we combine all the cases of [(1)and(2)]. Then we combine all the marketing campaigns for one year. I'm sure this is a common scenario, but I cannot find a definitive answer for what distributions result from the combinations: [Exp+Bernoulli] -> add up for one campaign -> [distribution?] -> add up all for the year -> [distribution?]
Would appreciate it if someone can confirm for me the theory on this, and also any references to how this is implemented in code!