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Informative Article | Information Technology | India | Volume 9 Issue 8, August 2020 | Popularity: 5.5 / 10

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Customer Segmentation and Personalization in Banking Services: Investigating the use of Big Data Analytics to Segment Banking Customers based on their Behavior, Demographics, and Preferences, and Leveraging these Insights to Personalize Banking Services and Marketing Campaigns

Sree Sandhya Kona

Abstract: In the dynamic realm of financial services, the strategic implementation of customer segmentation and personalization has become paramount due to the evolving expectations of consumers and the competitive market landscape. This paper explores the instrumental role of big data analytics in transforming banking services through sophisticated customer segmentation based on behavior, demographics, and preferences. Utilizing vast datasets, banks can now segment their customer base with unprecedented precision, enabling tailored marketing strategies and personalized service offerings that resonate more effectively with individual customer needs. Furthermore, the study delves into various analytical tools and techniques, such as machine learning algorithms and advanced data processing software, which aid in the extraction of actionable insights from complex datasets. Through real - world case studies, this paper illustrates successful applications of these strategies in leading banks, highlighting significant improvements in customer satisfaction and retention. The discussion also navigates through future trends in banking personalization, including the integration of artificial intelligence and real - time data analytics, while addressing potential challenges such as privacy concerns and regulatory compliance. This comprehensive analysis underscores the transformative potential of big data in refining customer interactions and shaping the future of banking.

Keywords: Big Data Analytics, Banking Services, Behavioral Analytics, Machine Learning, Data Mining, Customer Data, Marketing Strategies, Customer Satisfaction, Customer Retention, Financial Services, Predictive Analytics, Artificial Intelligence, Data Privacy

Edition: Volume 9 Issue 8, August 2020

Pages: 1566 - 1570

DOI: https://www.doi.org/10.21275/SR24522131706

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