Framework for Targeting High Value Customers and Potential Churn Customers in Telecom using Big Data Analytics | Zendy

Inderpreet Singh | Zendy; Sukhpal Singh | Zendy

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Framework for Targeting High Value Customers and Potential Churn Customers in Telecom using Big Data Analytics

Author(s) -

Inderpreet Singh,

Sukhpal Singh

Publication year - 2016

Publication title -

international journal of education and management engineering

Language(s) - English

Resource type - Journals

eISSN - 2305-8463

pISSN - 2305-3623

DOI - 10.5815/ijeme.2017.01.04

Subject(s) - profitability index , big data , business , telecommunications , customer lifetime value , value (mathematics) , analytics , marketing , computer science , customer retention , data science , data mining , finance , machine learning , service quality , service (business)

Since the more importance is played on customer’s behavior in today’s business market, telecom companies are not only focusing on customer’s profitability to increase their market share but also on their potential churn customers who could terminate the relation with the company in near future. Big data promises to promote growth and increase efficiency and profitability across the entire telecom value chain. This paper presents a framework for targeting high value customers and potential churn customers. Firstly, customers are segmented on basis of RFM (Recency-Frequency-Monetary) analysis and finally customers in each segment are targeted by various offers on basis of their similar characteristics.

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