Abstract
Brand loyalty is an important factor for companies to consider, as it can affect their ability to generate revenue and grow their business. The purpose of this study is twofold: first, it aims to examine the determinants of brand loyalty in the Fast-Moving Consumer Goods (FMCG) sector using household consumer panel data. To do this we propose a definition of brand loyalty based on household consumption volumes in different FMCG channels and then utilize machine learning techniques including Fuzzy C-Means (FCM) to segment customers based on their purchasing behavior, predict consumers’ brand loyalty, and identify the factors influencing brand loyalty. Secondly, we aim to investigate the relationship between store loyalty and brand loyalty using Propensity Score Matching (PSM). Results reveal that customers who show loyalty to stores are also more likely to show loyalty to particular brands.
Original language | English |
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Pages (from-to) | 209-236 |
Number of pages | 28 |
Journal | Journal of Multiple-Valued Logic and Soft Computing |
Volume | 44 |
Issue number | 3 |
Publication status | Published - 2025 |
Bibliographical note
Publisher Copyright:©2025 Old City Publishing, Inc.
Keywords
- brand loyalty
- fast-moving consumer goods
- Fuzzy C-Means
- household panel data
- machine learning
- propensity score matching
- store loyalty