Revenue optimization of telecom marketing campaigns for prepaid customers

Abstract

The design and optimization of marketing campaigns today usually still includes a high level of manual expert in- volvement. This applies particularly to the prepaid mobile phone sector of the highly competitive telecommunication industry. Since prepaid telecom customers are characterized by highly volatile and sparse usage data their future behavior is hard to predict, and marketers often rely mainly on experience and gut feeling when designing marketing campaigns, using only simple data analysis tools. The project developed a methodology and software prototype that helps marketers in this area to exploit the full potential of real-time big data-driven analytics for microtargeting, allowing them to make fact-based and informed decisions. Specifically, it provides an interactive solution for the semi-automated visual support of the design and optimization of single-channel marketing campaigns. The developed solutions brings a huge step towards the automation of the whole process of optimizing marketing campai