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Predicting Consumer Choices Through Analysis of Interactions in Social Networks

Author

Listed:
  • Todor Krastevich

    (Department of Marketing, Tsenov Academy of Economics, Svishtov, Bulgaria)

Abstract

Analysis of interactions in social networks has emerged as a new research paradigm in modern marketing. It focuses not on modeling behavior of the individual but rather than on the measurement and analysis of its relationships and interactions with other users within the network. Measurement and analysis of these interactions can help understand the structure and dynamics of social networks and their impact on consumer choice. In this paper we present a data mining approach to measure and analyze the interactions in social networks between clients of mobile telecommunication networks. Our goal is to demonstrate how to use Call Data Records (CDR) to build predictive choice models (e.g. to predict customer churn). The approach and methodology can be applied to analyze the customer choice behavior in other markets where customer interactions are tracked automatically and saved electronically

Suggested Citation

  • Todor Krastevich, 2013. "Predicting Consumer Choices Through Analysis of Interactions in Social Networks," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 3, pages 24-40, September.
    • Handle: RePEc:nwe:eajour:y:2013:i:3:p:24-40
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    References listed on IDEAS

    as
    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331.
    3. ., 2010. "Open Innovation and the Networked Firm," Chapters, in: Innovation and Commercialisation in the Biopharmaceutical Industry, chapter 3, Edward Elgar Publishing.
    4. Verbeke, Wouter & Dejaeger, Karel & Martens, David & Hur, Joon & Baesens, Bart, 2012. "New insights into churn prediction in the telecommunication sector: A profit driven data mining approach," European Journal of Operational Research, Elsevier, vol. 218(1), pages 211-229.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    social network analysis; churn management; direct marketing; predictive analytics and modeling; data mining; knowledge discovery;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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