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Research on the Application of Sentiment Analysis in Customer Segmentation and Precision Marketing
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Abstract
Sentiment analysis is emerging as a vital approach to uncovering customer behavior patterns. Powered by natural language processing and deep learning, emotional tendencies expressed in user-generated text can be quantified and modeled to reflect attitudes toward products, brands, or services. Embedding sentiment insights into customer segmentation and precision marketing enables a shift beyond static demographic labels, allowing for more granular audience clustering, content recommendation, and marketing efficiency enhancement. This study explores key aspects, including emotion data acquisition and preprocessing, sentiment vector-driven clustering strategies, and real-time personalization in marketing workflows. Practical applications demonstrate the positive impact on user engagement, satisfaction, and operational outcomes, highlighting the strategic value of sentiment analysis in marketing ecosystems.
Keywords
Sentiment Analysis; Customer Segmentation; Precision Marketing; Natural Language Processing; Emotion-Driven Strategy
References
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How to cite this paper
Research on the Application of Sentiment Analysis in Customer Segmentation and Precision Marketing
How to cite this paper: Huisheng Liu. (2025) Research on the Application of Sentiment Analysis in Customer Segmentation and Precision Marketing. Advances in Computer and Communication, 6(4), 244-249.
DOI: http://dx.doi.org/10.26855/acc.2025.10.015
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