Dear all


I'm currently facing the following situation. We have run a marketing campaign 
providing to some members one of two type of coupones. In addition to this, 
some of these members were already touched in the short past by another 
campaign.

So I have the following dataset, where:

-mixpre3M= is a flag variable telling us if the customer had already purchased 
somethign in the past

bono recibido: is the kind of coupon recived by the customer. The type "3euros" 
is the coupon identifying the customers already touched in the past by a 
campaign. the type "benchmark" identify the customer who haven't received any 
coupon (control group)
tran_during: is the N of redeemers or purchasers
enviados: is the number of people included in each group
mixpre3M bono_recibido TRAN_DURING_CAMP_FLG enviados
0 benchmark 5948 33336 
1 benchmark 557 2102 
0 BONO3EUROS 96 1233 
1 BONO3EUROS 17 83 
0 BONO6EUROS 4823 25434 
1 BONO6EUROS 626 1793
What I want achive is if there is a redemption or purchasing rate 
significatively different between each group, and see between which group there 
is difference

Now, I have the following doubts:

a. I understand I should run a multiple comparison test, like maybe a GLM with 
binominal distribution, but I'm not sure it is a correct procedure, considering 
that some of the groups (for instance the fourth one, with n=83) are quite 
smaller than the main other groups. Is the model I choose the correct one for 
this kind of analysis, and I should exclude the smaller groups?

b. I understand this is a kinda similar to a multiple A/B test. Does anyone 
know any tutorial or material which could help with the topic? Never managed 
this kind of test before

Many thanks for the help Bests


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