Customer Analysis Using the RFM Methodology in A Dental Clinic
Resumen
Digital transformation and data collection are needs that are emerging in companies, including in the dental clinic "Red Odontológica de Lima" which will be taken as the case of this study. Customer retention is essential in business management, given the investment required to attract new customers, so customer satisfaction and loyalty are critical to success. This study seeks to optimize decision-making in the patient care process using the RFM methodology as the main tool. The purpose is to show whether there are deficiencies in the patient care process by segmenting those with low recurrence, frequency, and monetary value. For this research, the CRISP methodology and the RFM methodology were used in the extraction and classification of patients. Recency analysis revealed that more than 600 patients did not return to the clinic after more than half a year, possibly due to various reasons such as a change of clinic, single treatment, or dissatisfaction. In terms of Frequency, more than 800 patients visited the clinic only once, suggesting similar factors for this lack of repeat visits. The Monetary Value parameter, essential for evaluating investments, showed that some patients invested up to more than S/20,000, indicating the effectiveness of the clinic. The methodology provides a revealing insight into the patient care process in the dental clinic. The results indicate the importance of retention and loyalty. The strategic groups are "Best Customers" and "Big Spenders". The presence of "Almost Lost" highlights areas for improvement. These results offer potential for decisions and strategies to improve the experience and foster loyalty in the dental practice.
Cómo citar
Pablo Félix, M. D., Pillaca Castro, A. M., & Taquía Gutiérrez, J. A. (2023). Customer Analysis Using the RFM Methodology in A Dental Clinic. In Proceedings of the 2023 9th International Conference on Industrial and Business Engineering (pp. 454-458). https://doi.org/10.1145/3629378.3629441Editor
ACMTemas
Coleccion(es)
- Ingeniería Industrial [135]