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

Authors

  • Kamini Murugaboopathy Wonderbow Analytics Private Ltd., India Author

DOI:

https://doi.org/10.32628/CSEIT25112450

Keywords:

Real-time analytics, Cloud computing, Marketing personalization, Data architecture, Artificial intelligence

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.

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References

Matt Ariker et al., "Quantifying the Impact of Marketing Analytics," Harvard Business Review, 2015. [Online]. Available: https://hbr.org/2015/11/quantifying-the-impact-of-marketing-analytics

Flexera, "2024 State of the Cloud Report," Flexera Software LLC, Tech. Rep., 2024. [Online]. Available: https://resources.flexera.com/web/pdf/Flexera-State-of-the-Cloud-Report-2024.pdf

GeeksforGeeks, "Difference between Cloud Computing and Traditional Computing," GeeksforGeeks, 2024. [Online]. Available: https://www.geeksforgeeks.org/difference-between-cloud-computing-and-traditional-computing/

Funnel.io, "A guide to efficient marketing data integration," LinkedIn, 2025. [Online]. Available: https://www.linkedin.com/pulse/guide-efficient-marketing-data-integration-funnel-io-0r7ff

Redpanda Data, "Real-time data analytics—Use cases and architectural considerations," Redpanda Data, Inc.. [Online]. Available: https://www.redpanda.com/guides/fundamentals-of-data-engineering-real-time-data-analytics

Gartner, Inc., "Cloud Strategy Leadership," Gartner Research, Stamford, CT, 2017. [Online]. Available: https://www.gartner.com/imagesrv/books/cloud/cloud_strategy_leadership.pdf

Dave McCarthy et al., "IDC FutureScape: Worldwide Cloud 2023 Predictions," IDC Research, Framingham, MA, Doc #US48602322, Oct. 2022. [Online]. Available: https://www.idc.com/getdoc.jsp?containerId=US48602322

Rusty Warner et al., "The Forrester Wave™: Real-Time Interaction Management, Q2 2022," Forrester Research, Inc., Cambridge, MA, USA, Tech. Rep. RES176354, 2022. [Online]. Available: https://www.forrester.com/report/the-forrester-wave-tm-real-time-interaction-management-q2-2022/RES176354

Adobe, "Adobe Digital Economy Index," Adobe Inc., San Jose, CA, USA, 2020. [Online]. Available: https://business.adobe.com/content/dam/dx/us/en/experience-cloud/digital-insights/adobe_analytics-digital-economy-index-2020.pdf

Aditi Rao et al., "Tech Trends 2023," Deloitte Insights, New York, NY, 2023. [Online]. Available: https://www2.deloitte.com/content/dam/insights/articles/us175897_tech-trends-2023/DI_tech-trends-2023.pdf

Michael Chui et al., "The state of AI in 2022—and a half decade in review," McKinsey Global Institute, 2022. [Online]. Available: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2022-and-a-half-decade-in-review

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Published

15-03-2025

Issue

Section

Research Articles