Work

An algorithmic marketing approach to analyzing consumer well-being: Incorporating psychological factors in customer loyalty

Year: 2025

Type: article

Abstract: In recent years, there has been growing interest in consumer well-being in marketing research. This study examines psychological loyalty, which connects corporate profits with consumer well-being, and proposes an algorithmic marketing approach to analyze survey data from the Matsuya Ginza Department Store to identify specific variables that impact consumer well-being. To clarify the structure between each variable and consumer well-being, we considered various gradient boosting machine learning models, which emphasize classification accuracy for qualitative data, and constructed an ensemble learning model. We also conducted clustering on Matsuya Ginza customers, analyzed the variables that significantly contribute to consumer well-being in different clusters, and developed specific measures to improve products and services. Furthermore, using SHAP (Shapley Additive Explanations) and ICE (Individual Conditional Expectation), we conducted instance-level analysis to show to what extent consumer well-being tends to increase or decrease in relation to important variables for each instance.

Source: Journal of Retailing and Consumer Services

DOI: 10.1016/j.jretconser.2025.104238

Authors: Yu Zhao, Michiko Tsubaki

Institution: Tokyo University of Science

Language: English

Topic: Customer Service Quality and Loyalty

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $4,510

Funder: Japan Society for the Promotion of Science