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A Methodological Approach for the Journey through Real-Time Marketing: From Customer Journey Analytics to Personalization Engines

Author

Listed:
  • Claudiu-Catalin Munteanu

    (Romanian Academy)

  • Adina Cristea

    (Bucharest University of Economic Studies)

Abstract

Many companies rely in practice on personalization engines and value co-creation in order to boost the efficacy of their one-to-one customer relationships. Real-time marketing (RTM) can increase the efficacy of marketing activities by taking advantage of technology, big data analysis, social media and constant connectivity. RTM fosters consumer engagement in value co-creation and in the personalization of products, offers and customer service. This paper suggests a methodology for implementing RTM by considering the main characteristics of customization strategies: novelty, serendipity and diversity. Based on the seven rules for RTM implementation, we propose and discuss the process of incorporating big data and customization strategies into a personalization engine driven by machine learning and big data analytics. We include in the personalization engine value co-creation drivers based on marketing drive value, customer lifetime value and strength and intensity of brand associations. The proposed process-based framework for RTM implementation integrates algorithms related to customer profile to calculate their future purchase probability, thus being a useful managerial tool for segmenting and targeting consumers in real-time. By adapting marketing communication patterns to these permanently ‘evolving’ segments, value co-creation and consumer satisfaction increase, while the AI algorithms also improve.

Suggested Citation

  • Claudiu-Catalin Munteanu & Adina Cristea, 2021. "A Methodological Approach for the Journey through Real-Time Marketing: From Customer Journey Analytics to Personalization Engines," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 849-855, December.
    • Handle: RePEc:ovi:oviste:v:xxi:y:2021:i:2:p:849-855
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    References listed on IDEAS

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    More about this item

    Keywords

    real-time marketing; personalization engines; big data marketing; customization strategiesm value co-creation;
    All these keywords.

    JEL classification:

    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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