Business to consumers (B2C): the effect of machine learning application in telecom customer churn management
Authors
Adeniji, Olanrewaju
Issue Date
2020
Degree
MSc in Data Analytics
Publisher
Dublin Business School
Rights holder
Rights
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Abstract
Customer churn also know as customer attrition is one of the major challenges faced by telecoms service providers and other types of businesses. Revenue is lost annually and marketing budget is wasted due to customer attrition. In order to maintain a strong business to consumer management, companies adopt business intelligence and data analytic models to extract and process necessary customer information. The project research will be divided into two (a) to predict customer churn (b) to create innovative idea to maximize profit for telecom in business to customer sector. Two different analytical tools were used to process a public telecom dataset and model algorithms for classification. The aim of this project will suggest how to reduce losses in marketing cost, fraud, and create an innovative digital idea to breach the revenue gap between telecom and digital platforms using customer and network data for profit maximization.