Real-Time Data Analytics in Customer Experience Management: A Framework for Digital Transformation and Business Intelligence

Amarnath Immadisetty

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 6, 1280-1288

Abstract: Real-time data analytics has emerged as a transformative force in customer experience management, enabling organizations to process and respond to customer interactions instantaneously. This article presents a comprehensive framework for implementing real-time analytics in customer-centric business operations, examining both theoretical foundations and practical applications across multiple industries. Through systematic analysis of implementation strategies, technical architectures, and organizational challenges, this article illuminates the critical role of real-time analytics in enabling personalized customer experiences, dynamic pricing optimization, and predictive service delivery. The article synthesizes current industry practices while identifying key success factors and potential barriers in real-time analytics adoption. Findings indicate that organizations leveraging real-time analytics capabilities demonstrate enhanced customer satisfaction, improved operational efficiency, and strengthened competitive positioning. This article contributes to both theoretical understanding and practical implementation of real-time analytics in customer experience management, providing actionable insights for practitioners while identifying promising directions for future research. The article concludes with a structured framework for organizations seeking to implement or enhance their real-time analytics capabilities in pursuit of superior customer experience.

Keywords: Real-time Analytics; Customer Experience Management; Business Intelligence; Digital Transformation; Predictive Analytics (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT241061172
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i6:id:522

DOI: 10.32628/CSEIT241061172

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