Hi All ,

I've recently  build a predictive data model for a campaign to target  group of customer who can switch from  payment method  "A" to Payment method "B".

The idea was to come up with predictive model with payment/usage variables as independent variable and  the event of switch in past is taken as  dependent variable.

i) I used logistic regression model for probability  estimation.

ii) The  data  is sorted in order of descending probability and  customer's were solicited. 

iii)  The results analysed after campaign suggests , the customer have low probability have better switch rate and high probability have  lower switch rate.

iv) Below are the results:

I assumed the customer with high propensity should have high switch rate , so the switch rate in top  decile should have been higher.

Could anyone please suggest

 i ) what mistakes I could have done.

ii) Any similar experience and remedy .

Regards,

Himanshu