Dynamic Time Warping and RFMS-Based Clustering: A Three-Stage Framework for Customer Segmentation and Churn Prediction in Climbing Gyms

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Keywords	Churn Prediction, RFM model, Dynamic Time Warping, Customer Segmentation, K-means Clustering, RFMS+DTW
Thesis Advisor	Koppius, Otto, Quinn, Martin
Persistent URL	hdl.handle.net/2105/72041
Series	Business Analytics & Management
Organisation	Rotterdam School of Management
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Asa Yudhistira, Asa. (2024, July 9). Dynamic Time Warping and RFMS-Based Clustering: A Three-Stage Framework for Customer Segmentation and Churn Prediction in Climbing Gyms. Business Analytics & Management. Retrieved from http://hdl.handle.net/2105/72041

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