Market Segmentation and Tag Optimization in Customer Behavior Data Analysis: Current Status and Future Research Directions

DOI: https://doi.org/10.62517/jnme.202510405

Author(s)

Zixiang Yan

Affiliation(s)

York University, Faculty of Science, Toronto, Ontario, Canada

Abstract

With the rapid collection of customer behavior data, a key factor for businesses in their digital transformation was obtaining accurate marketing and personalized recommendations by effectively segmenting the market and optimizing labels. Traditional methods face difficulties in dealing with multidimensional, dynamic and heterogeneous customer data. This paper systematically discusses current market segmentation techniques and tag optimization strategies based on literature reviews, analyzes their optimization paths in terms of model accuracy, real-time performance, semantic significance and more. Combining typical examples of application in industry, the paper addresses the potential shortcomings and challenges of existing methods in practical application and provides recommendations for future research in areas such as intelligent systems, semantics-based approaches, and dynamic tag generation.

Keywords

Customer Behavior Data; Market Segmentation; Tag Optimization; Ontology Methods; Multi-Layer Tags; Precision Marketing

References

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