I want to conduct an A/B test between two different Ad Copies I have for a given advertisement on Google.
Ad Copy A might have 30 k impressions (number of times ad was displayed) with approximately $700 in revenue.
Ad Copy B might have 60 k impressions with approximately $600 worth of revenue.
Originally I thought I should use a chi-squared distribution -- but thought against it as the variables used, were not discrete but continuous (revenue could be from 0 to infinity).
I was looking online and I saw something regarding a MWW test (Mann-Whitney U Test) used for testing web pages vs. the revenue per visitor.
Is this the correct test to use for my split? Does anyone have any other suggestions regarding what statistical test I can use to reject my null hypothesis(H0: there is no statistically significant difference between the two ad copies; or in other words, A and B cannot be compared because such differences in performance could be due to experimental/sampling size errors).