Peker SerhatKart Özge2023-03-222023-03-22202225097873https://doi.org/10.1007/978-981-16-8997-0_5https://hdl.handle.net/20.500.14034/845In today’s digital world, enterprises accumulate large quantiles of customer data which drives firms to implement data-driven CRM strategies to manage customer relationships. In CRM, machine learning techniques are widely used as a tool for using customer data and thereby acquiring knowledge from such data. In this context, this research presents a holistic framework for the implementation of machine learning methods in data-driven CRM applications. The proposed framework relies on past transactional data of customers and employs state-of-art machine learning techniques. This research serves as a foundation for future studies on data-driven CRM applications utilizing machine learning techniques. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.eninfo:eu-repo/semantics/closedAccessArtificial intelligenceAssociation analysisClassificationClusteringCRMCustomer attractionCustomer retentionData miningKDDMachine learningRegressionBook Chapter10.1007/978-981-16-8997-0_5871032-s2.0-85130788146N/A