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Proposed analytical customer centric model for an automobile industry

Author

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  • Archana Singh
  • Ajay Rana
  • Jayanthi Ranjan

Abstract

Research practitioners have contributed extensively in maximising the customer value using different models. It has been realised that customer lifetime models are industry dependent. The analysis of customer lifetime value is done with different customer value models. Recency, frequency, and monetary (RFM) model is traditional used for market segmentation to detect patterns customers/buyers. In this research paper, a new customer centric analytical model has been proposed for an automobile industry. The paper explores new dimensions in the proposed model to determine the customer value and further by using data mining approach helps the management to build new strategic customer relationship model. The data mining technique association rule mining, direct hashing and pruning is used to generate rules and market patterns for the market management which in turn facilitates in effective and efficient decision making.

Suggested Citation

  • Archana Singh & Ajay Rana & Jayanthi Ranjan, 2015. "Proposed analytical customer centric model for an automobile industry," International Journal of Data Mining, Modelling and Management, Inderscience Enterprises Ltd, vol. 7(4), pages 314-330.
    • Handle: RePEc:ids:ijdmmm:v:7:y:2015:i:4:p:314-330
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    Cited by:

    1. Archana Singh & Apoorva Sharma & Gaurav Dubey, 2020. "Big data analytics predicting real estate prices," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 208-219, July.

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