IDEAS home Printed from https://ideas.repec.org/a/dba/pappsa/v11y2026ip248-257.html

Research on the Application Strategies of Precision Marketing and User Engagement in the Big Data-Driven Retail Industry

Author

Listed:
  • Liu, Ao

Abstract

With the rapid development of big data technology, the retail industry is facing unprecedented opportunities and challenges in precision marketing and user engagement. In-depth analysis of user behavior, purchase habits, and preferences helps enterprises personalize marketing strategies, thereby effectively improving customer loyalty and sales conversion rates. This paper discusses the precision marketing strategy in the retail industry based on big data analysis, including data collection, data mining, user portrait construction, and precision marketing implementation. It examines how big data facilitates user life-cycle management and enhances user value through engagement, and assesses the practicality and effectiveness of the proposed strategy using case studies. Specifically, the study first establishes a comprehensive theoretical framework that integrates big data analytics with contemporary marketing paradigms, highlighting the critical role of real-time data processing in enabling dynamic customer segmentation. Subsequently, the paper proposes a multi-dimensional user portrait construction methodology that leverages machine learning algorithms to capture granular behavioral patterns across diverse digital touchpoints. The research further explores the application of predictive analytics in optimizing promotional campaigns, inventory management, and personalized recommendation systems within the retail ecosystem. Through detailed case studies of leading retail enterprises, the paper evaluates the measurable impact of data-driven precision marketing on key performance indicators such as customer retention rates, average transaction values, and overall revenue growth. Additionally, the study addresses the ethical considerations and privacy concerns associated with large-scale consumer data utilization, proposing a balanced framework for responsible data governance. This paper puts forward a series of practical suggestions to help retail enterprises achieve sustainable development in the era of big data, contributing valuable insights for both academic researchers and industry practitioners seeking to harness the transformative potential of data-driven marketing strategies.

Suggested Citation

  • Liu, Ao, 2026. "Research on the Application Strategies of Precision Marketing and User Engagement in the Big Data-Driven Retail Industry," Pinnacle Academic Press Proceedings Series, Pinnacle Academic Press, vol. 11, pages 248-257.
  • Handle: RePEc:dba:pappsa:v:11:y:2026:i::p:248-257
    as

    Download full text from publisher

    File URL: https://pinnaclepubs.com/index.php/PAPPS/article/view/854/815
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:dba:pappsa:v:11:y:2026:i::p:248-257. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joseph Clark (email available below). General contact details of provider: https://pinnaclepubs.com/index.php/PAPPS .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.