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ISSN: 2582-8266 (Online)  || UGC Compliant Journal || Google Indexed || Impact Factor: 9.48 || Crossref DOI

Fast Publication within 2 days || Low Article Processing charges || Peer reviewed and Referred Journal

Research and review articles are invited for publication in Volume 18, Issue 2 (February 2026).... Submit articles

Breaking down attribution modeling in predictive analytics

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  • Breaking down attribution modeling in predictive analytics

Ashish Mohan *

University of Connecticut, USA.

Review Article

World Journal of Advanced Engineering Technology and Sciences, 2025, 15(02), 2851–2859

Article DOI: 10.30574/wjaets.2025.15.2.0827

DOI url: https://doi.org/10.30574/wjaets.2025.15.2.0827

Received on 15 April 2025; revised on 27 May 2025; accepted on 29 May 2025

This article presents a comprehensive overview of attribution modeling in predictive analytics, detailing how organizations can effectively evaluate the impact of various touch points throughout the customer journey. Attribution modeling has become essential as consumers interact with brands across multiple channels before making purchase decisions, requiring sophisticated techniques to assign appropriate credit to each interaction. The article explores the conceptual framework of attribution modeling, discusses various model types from single-touch to data-driven approaches, addresses common implementation challenges, and outlines strategies for organizational integration. By adopting advanced attribution frameworks, organizations can allocate marketing resources more efficiently, enhance customer understanding, improve forecasting accuracy, and align marketing activities with broader business objectives, ultimately creating a sustainable competitive advantage in increasingly complex markets. 

Attribution Modeling; Customer Journey Analytics; Multi-Touch Attribution; Marketing Optimization; Predictive Analytics

https://wjaets.com/sites/default/files/fulltext_pdf/WJAETS-2025-0827.pdf

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Ashish Mohan. Breaking down attribution modeling in predictive analytics. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(02), 2851–2859. Article DOI: https://doi.org/10.30574/wjaets.2025.15.2.0827.

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