Analytical Approaches in Customer Relationship Management
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Date
2023
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Open Access Color
Green Open Access
No
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Publicly Funded
No
Abstract
This study examines the impact of analytical customer relationship management (aCRM) strategies, specifically the segmentation approach using RFM analysis and artificial learning methods, on customer satisfaction, revenue performance, and loyalty in businesses. The research adopts an approach that integrates data from both online and offline channels onto a single platform, providing a holistic view of customer behaviors. Combining the segmentation obtained through RFM analysis and artificial learning methods with timely campaigns has enhanced shopping opportunities for customers and increased customer satisfaction and loyalty. The use of aCRM as a strategic marketing and sales tool has enabled businesses to manage customer relationships more effectively. This paper contributes to the literature in this field by presenting in detail the advantages offered by aCRM, its application methods, and the results obtained.
Description
ORCID
Keywords
Rfm analysis, Customer satisfaction, Analytical customer relationship management (acrm), Revenue performance, Segmentation
Turkish CoHE Thesis Center URL
Fields of Science
Citation
Sahin, Z., Ergin, K., Akata, M. A., Kaya, B., Kizilay, A., & Cakar, T. (2023, December). Analytical Approaches in Customer Relationship Management. In 2023 4th International Informatics and Software Engineering Conference. IEEE. pp. 1-5.
WoS Q
N/A
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N/A

OpenCitations Citation Count
1
Source
2023 4th International Informatics and Software Engineering Conference (IISEC)
Volume
Issue
Start Page
1
End Page
5
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Scopus : 1
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Mendeley Readers : 26
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1
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300
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30
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