I have researched quite a bit to try an answer on my own but found very contradicting answers.. Would appreciate if this community can help..
I set up a test to measure the impact of an offer sent via email to customers in the test group.. Three months have passed and my test group constitutes ~ 164K customers, while control has ~ 18K customers (90:10 split). Now I am trying to determine the impact of the offer on test group.. I want to determine if mean number of transactions of test is significantly higher than control.
The problem I have is most of the customers ~95% do not do any transactions in the three months period which makes the distribution heavily right skewed. Which test/methodology can i use to determine if the mean of test > control.. The two sample parametric test has an assumption that the populations should be normally distributed which is so not true in my case and I've read in few places that Mann- Whitney shouldn't be used for comparing means. Plz advise