I have a dataset of store IDs with its performance related to Customer enrollment.
I am running a reward program for around 150 stores for getting customer enrollment with proper customer data.
Stores are encouraged to do customer enrollment for loyalty program but many stores didn’t collect all required details, such as Mobile no, Email id, communication preferrence , gender, date of birth.
a sample data row looks like this–
Store id- 0001
Count of Enrollment- 1200
% of customer Mobile number present= 85%
%of Email present=90%
%of dob mentioned= 82%
% of gender mentioned= 80%
%of communication preference mentioned= 70%
total record count (/stores) = 150
so, we have to decide on what weightage to give on each variable and then come up with a solid logic to rank stores. Finally top10 and bottom 10 leader board is intended.
What analysis, logic/ statistical tool should I be using?
(please suggest/refer code/logic implementable in python or R studio).
Thanks for reading this. please reply.