Enhanced churn models helped the client to reduce churn in their most valuable customer segments by more than 40%.
For data monetization the accuracy in prediction of the subscribers’ profile was over 96%.
We also developed multinomial logistic regression to predict pre-paid subscribers’ demographic profile such as Nationality, Gender and Age to design campaigns with relevant offers. This resulted in increased campaign responses enhancing the attractiveness of the client’s data monetization platforms.
We used Greenplum native programming ability to process the data and to automate periodical scoring of all models saving the time taken in data movements.