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We ran a A/B test for all the customers and there are two sub groups within each group. How do I determine statistically conversion lift in one group is greater than conversion lift in other group.

For example. Control group (Higher income group, lower income group): out of 100 customers in each group, 20 and 50 purchased the product respectively. Conversion rate(Higher income - control) = 20%, Conversion rate(Lower income - Control) = 50%

Test group (Higher income group, lower income group): out of 100 customers in each group, 40 and 70 purchased the product respectively. Conversion rate(Higher income - Test) = 40%, Conversion rate(Lower income - Test) = 70% Conversion lift in Higher income group = (40 - 20)/20 = 100% Conversion lift in lower income group = (70 - 50)/50 = 40%

How to determine if the lift in higher income group is statistically significant?

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There are plenty of possibilities. E.g. one could probably calculate a logistic regression model with variables "high income group" (yes / no = low), "test group" (yes / no = control) and interaction "high income group" * "test group".

I would then test, if the interaction term is significant. If significant, one could conclude, that the effect of your intervention is different between groups.

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  • $\begingroup$ Thanks...I will build logistic regression model and check for significance of interaction effect. $\endgroup$
    – Saleem
    Feb 28, 2020 at 17:04

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