Churn Case Studies

Churn Case Studies

Copyright: © 2015 |Pages: 53
DOI: 10.4018/978-1-4666-6288-9.ch011
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Abstract

This case study chapter brings two business cases in the domain of churn, both unique in many ways, combining almost all the topics covered inside book. The first business case presents a retail company facing new competitors and consequently preparing a customer-retention strategy. The case introduces the business environment in which the company was operating prior to the arrival of new competitors while the model is being devised for the purpose of preventing or at least buffering the churn trend as a reaction to the new competition. Development of an early warning indicator system based on data mining methods is also described as a support to the management in the early detection of both market opportunities and threats. The second business case describes the situation in a telecommunication company in the domain of churn prediction and churn mitigation. The churn project was divided into a few stages and is fully described in the chapter. The case explains how the company can decrease the churn rate and gives directions for better understanding of customer needs and behaviors.
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11.2 Case Study 1: Preparing For New Competition In The Retail Industry

A business case presents a retail company facing new competitors and consequently preparing a customer retention strategy. The business environment in which the company was operating prior to the arrival of new competitors can be described as a stable market. Bearing in mind the plans and marketing activities of a competitor retail chain and making use of the data mining methods a system is being devised for the purpose of preventing or at least buffering the churn trend. Development of an early warning indicator system based on data mining methods is also being described as a support to the management in early detection of both market opportunities and threats. Research in data mining could also be concentrated on applying existing data mining techniques to find the best solution regarding practical business problems in the public or private sector. Knowledge regarding how some business cases were solved using data mining techniques could contribute in a better understanding of the nature or data mining nature and help solve specific business issues (Klepac, 2010).

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