@inproceedings{ec4f7429b54e496a8bdd9f042be5dba6,
title = "Unpacking Retail Customer Retention Through Cohort Analysis and Demographic Segmentation",
abstract = "Understanding customer retention in retail presents a challenge that this research addresses by leveraging cohort analysis and demographic segmentation. The relevance lies in its ability to enhance retail competitiveness by uncovering how different customer segments exhibit varying retention behaviors over time, thus informing more effective retention strategies. The methodology combines cohort analysis with demographic segmentation to examine retention rates among diverse customer groups. This approach facilitates efficient detection and analysis of retention trends that reveal significant differences in customer retention patterns across demographic segments. Female customers exhibit higher loyalty than males across various cohorts, while Baby Boomers and Gen X display distinct engagement levels. These insights suggest that tailored retention strategies are necessary to address the unique behaviors of different demographic segments. The study{\textquoteright}s managerial implications are substantial, providing actionable insights for business stakeholders to optimize marketing efforts and enhance customer relationship management practices based on demographic and cohort analysis.",
keywords = "Cohort Analysis, Customer Retention, Demographic Segmentation",
author = "Kh{\textquoteright}ng, \{Xin Yi\} and Beh, \{Woan Lin\} and Ooi, \{Boon Yaik\} and Yeoh, \{William Ging Sun\}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 7th International Conference on Smart Computing and Informatics, SCI 2025 ; Conference date: 08-04-2025 Through 09-04-2025",
year = "2026",
doi = "10.1007/978-3-032-08243-5\_14",
language = "English",
isbn = "978-3-032-08242-8",
volume = "1683",
series = "Lecture Notes in Networks and Systems",
pages = "145--158",
editor = "Vikrant Bhateja and Hoong, \{Angela Lee Siew\} and Kong, \{Jude Dzevela\} and Junali, \{Jasmine Jena\}",
booktitle = "Smart Computing Paradigms",
}