Leveraging Cloud Computing for Real-Time Marketing Analytics: A Technical Perspective

Kamini Murugaboopathy

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025, vol. 11, issue 2, 1229-1243

Abstract: This article examines how cloud computing has revolutionized marketing analytics by enabling real-time data processing and decision-making capabilities previously unattainable with traditional on-premise systems. It presents a comprehensive technical analysis of cloud-native architectures for marketing analytics, detailing the multi-layered framework that spans from data ingestion through to action delivery. The article explores how organizations have overcome the historical limitations of traditional analytics environments—including data silos, batch processing constraints, and limited computational resources—through the implementation of cloud-based platforms. The technical architecture is dissected across its primary components: the data ingestion layer that captures customer interactions as they occur; the processing layer that transforms raw data into actionable insights within milliseconds; specialized storage technologies optimized for analytical workloads; the analytics layer with its visualization and machine learning capabilities; and the action layer that enables immediate customer engagement. The article further addresses critical implementation considerations related to performance optimization, scalability, data governance, and cost management. Through examination of real-world applications like dynamic audience segmentation, predictive customer lifetime value modeling, and personalized content orchestration, it demonstrates how cloud technologies deliver substantial competitive advantages. The article concludes by exploring emerging trends at the intersection of artificial intelligence and cloud computing that will shape the next generation of marketing analytics capabilities.

Keywords: Real-time analytics; Cloud computing; Marketing personalization; Data architecture; Artificial intelligence (search for similar items in EconPapers)
Date: 2025
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112450
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v11:y2025:i2:id:1189

DOI: 10.32628/CSEIT25112450

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