IEEE/ACM Transactions on Networking · 2020 · 21 citations · 41 references
ComputingBusiness EconomicsInformation TechnologyBig Data AnalyticsPredictive AnalyticsRevenue ManagementCapacity ManagementCustomer Service ManagementMachine Learning For Big DataMobile NetworkingMobile NetworksOmnichannel AnalyticsBillingCapacity OptimizationCarrier BillingChurn Prediction In TelecommunicationsCustomer Churn MeasurementCustomer Churn ModelingCustomer Churn ReductionMobile Revenue Management
Recent years have witnessed the rapid growth of mobile virtual network operators (MVNOs), which operate on top of existing cellular infrastructures of base carriers, while offering cheaper or more flexible data plans compared to those of the base carriers. In this paper, we present a two-year measurement study towards understanding various fundamental aspects of today's MVNO ecosystem, including its architecture, customers, performance, economics, and the complex interplay with the base carrier. Our study focuses on a large commercial MVNO with one million customers, operating atop a nation-wide base carrier. Our measurements clarify several key concerns raised by MVNO customers, such as inaccurate billing and potential performance discrimination with the base carrier. We also leverage big data analytics, statistical modeling, and machine learning to address the MVNO's key concerns with regard to data usage prediction, data plan reselling, customer churn mitigation, and billing delay reduction. Our proposed techniques can help achieve higher revenues and improved services for commercial MVNOs.
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