# How to deal with unequal proportions in an A/B test?

I have 100 customers, 40 are Females and 60 are Males. My marketing team has created 2 separate campaigns with different offers for both groups. We create an A/B test for each group to study campaign lift. Below are the splits (A = No offer | B = offer depending on the group)

Counts :

    Group  |  A  |  B  | Total
-----------------------------
Females |  10 |  30 |  40
Males   |  20 |  40 |  60
-----------------------------
Total   |  30 |  70 | 100


Here are the results,

 Results : $value purchased per person during active campaign dates Again, A = Control, B = Test... so lift over control = (B-A)/A Group | A | B | Lift ----------------------------- Females |$5 |  $7 | 40% Males |$3 |  $4 | 33% ----------------------------- Wt. Avg |$3.6| \$5.3|  47%


What's funny is the lift of Total-A vs. Total-B is more than individual groups, and I realise that this has got something to do with the proportion of A:B across groups. (Females = 1:3, Males = 1:2)

My question is what the best way to solve for this discrepancy ?