Consumer segmentation and pricing optimisation with online reviews: a sentiment analysis-based decision-making framework

Liu, Shiyu, Liu, Zixu, Wang, Jun and Xu, Liwei (2026) Consumer segmentation and pricing optimisation with online reviews: a sentiment analysis-based decision-making framework. Journal of the Operational Research Society, 1-21. (doi:10.1080/01605682.2026.2630957).

Abstract

With the development of online platforms and the continuous advancement of text analysis technologies, online reviews have become an important resource for retailers to understand consumer characteristics. In this paper, we provide a comprehensive decision-making framework for retailers based on online product reviews to conduct consumer segmentation and differential pricing. Existing research mainly focuses on extracting consumers’ preferences for product quality dimensions from online reviews, with little attention given to the price preferences embedded in the text. Thus, this paper proposes a deep learning-based analysis method to extract consumer information on both price and quality sensitivities, aiming to capture consumer purchasing utilities and subsequently segment consumers along these two dimensions. Building upon the identified consumer segmentation and sensitivities within each segment, we establish a differential pricing model to maximise the retailer’s profit. To verify the accuracy and feasibility of our proposed deep learning-based analysis method, we use real-world review data to train and test our model. The experiment results show competitive accuracy compared with the current works, which means our method could provide retailers with a new perspective and approach for analysing online reviews and conducting consumer segmentation. Furthermore, after the consumer segmentation, we continue to validate the effectiveness of the differential pricing model. Comparative experiments demonstrate that our pricing strategies based on both consumer price and quality sensitivities in different segmentations can enhance retailers’ profitability. In conclusion, our framework provides retailers with theoretical support for implementing consumer segmentation and differential pricing strategies based on online reviews in e-commerce scenarios.

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Contributors

Author: Zixu Liu

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