Elbow Method for Optimal Customer Segmentation Using K-Means Clustering
Customer segmentation is a crucial task in marketing and business strategy, allowing companies to targetspecific groups effectively. This paper explores the application of the elbow method to determine the optimalnumber of clusters for customer segmentation using K-means clustering. By analyzing customer data from aretail business, we demonstrate how the elbow method helps in identifying the most meaningful segments. Ourstudy highlights the practical utility, benefits, and limitations of this approach in real-world scenarios.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-15
- DOI
- https://doi.org/10.5281/zenodo.16883249
- Primary Topic
- Customer churn and segmentation
- Type
- article
- Field-Weighted Citation Impact
- 0.00