Predicting the Average Monthly Billing Amount of a Mobile Customer

Project Details




Dinesh Fernandes, Gautam Vasappanavara, Hans Hummer, Kathyayani GBS, Manojna Belle





With more than 25 Mobile service providers in India, all the service providers want to increase their market share as quickly as possible. Few techniques to improve market share can be by good marketing campaigns or by providing customized connection plans and excellent customer service when the customer walks in to the store. In most of the cases, the customer’s interaction with the representative from service provider will determine whether the customer will continue service with that provider or not.

We employed various data mining techniques on the 3100 users data collected to determine important predictor variables required for predicting average monthly mobile billing of a customer. The predictor variables so found can thus be used for better predicting billing amount of customers. Thereby, customized plans can be suggested by service provider as the customer walks in the store.

Data mining analysis enables us to rank potential customers on their probable amount of expenditure per month. It would be helpful for predicting customer service plan selection and preference patterns, and also for the development and extension of customer services and the service plan portfolio.

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