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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 .