Teaching Case: Who Renews? Who Leaves? Identifying Customer Churn in a Telecom Company Using Big Data Techniques
1. INTRODUCTION The purpose of this teaching case is to introduce students to some of the ways in which big data analytics can be utilized to make business decisions. In this paper, we present big data as data that is defined by multiple characteristics including volume, velocity, variety, and veracity (Chen, Chiang, and Storey, 2012) Whereas some data utilized for big data applications may possess all the above mentioned characteristics, others may possess only some of the characteristics mentioned above, with volume occurring frequently as a dominant characteristic. Specifically, we focus on the volume and variety components of the definition of big data and show how to leverage those characteristics to build business driven, big data applications. The case exposes students to the use of big data analytics to reduce customer churn in the telecom industry. Churning occurs when a business loses a customer to another competitor, leading to loss of sales (Adwan et al. 2014) For privacy's sake, the authors use the pseudonym New Horizon Telecom (NHT) for the telecom company on the basis of which this case was developed. This written case is presented as a non project based exercise to facilitate a class discussion about the business application of big data analytics (Cappel and Schwager, 2002) By following one of the most prominent Business Intelligence (BI) model curriculum guidelines (Gupta, Goul, and Dinter, 2015) we focus on designing a teaching case that supports the teaching of a Level 2 Management Information Systems (MIS) course as designed in the MSIS 2006 Model Curriculum (Gorgone et al. 2006) In the MSIS 2006 Model Curriculum, Level 2 courses are those that focus on sophisticated and emerging topics such as Big Data. Whereas previous efforts to teaching BI in the Business School has focused on the design of comprehensive analytics programs, this teaching case supports Asamoah et al.'s (in press) effort in designing content at the micro level where specific courses are utilized to teach BI. In subsequent sections of this paper, we first situate the teaching case within a telecommunications background and present the use of big data analytics to solve a business problem. Next, we present a case story in which the authors first explain the challenges NHT was facing in terms of retaining its core customer base and its motivation for analyzing customer churn as part of its business operations. The case text also presents the opportunities that the vast amount of NHT's customer data presented in their quest to utilize customer communication data to reduce churn. This involved an exposition of NHT's data sources, data management, and analysis. The case text also describes how and why NHT sessionized the data from multiple channels and identified potential churn based on customer activities. A Big Data assignment derived from the case is presented in the subsequent section. A feedback survey of a pre test of the assignment in an actual Big Data course is also presented. In the conclusion, we discuss how structural changes were made in NHT based on the results of the churn analysis. The objectives of the case are for students to: 1. Understand the technical and operational environment for a Big Data driven approach to solving business problems. 2. Use an analytics approach to analyze customer interactions data and reduce customer churn in a business organization such as a telecommunications company. 3. Study and understand how to utilize a Big Data Analytics tool, using Teradata Aster as a sample platform. 2. BACKGROUND NHT is a nationwide telecommunications service provider that offers fourth generation mobile cellular services to its customers. NHT operates in a highly volatile telecommunication industry where customer churn is a common problem. For instance, worldwide, the rate of customer churn in the telecom service industry ranges from 20% to 40% per year (Ahn, Han, and Lee, 2006)
J. Inf. Syst. Educ.