Modeling Framework for Customer Retention in Auto Service
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V6I4P123Keywords:
Marketing Analytics, Customer retention, Cohort Analysis, Machine Learning, Segmentation, Value, Attrition, Potential, RegressionAbstract
The automotive industry faces a critical challenge in maintaining long-term relationships with customers post-sale. Retaining customers in the after-sales service market is vital, given its competitive nature and potential for recurring revenue. This paper proposes a machine learning-based framework for customer retention by predicting attrition probability and future spending potential. By leveraging data segmentation, personalized engagement strategies, and predictive modeling, this framework aims to optimize marketing efforts and enhance customer loyalty. We also explore additional insights based on current trends in customer analytics and service personalization
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