Breaking down attribution modeling in predictive analytics

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.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-05-30
DOI
https://doi.org/10.30574/wjaets.2025.15.2.0827
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
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article

Breaking down attribution modeling in predictive analytics

Ashish Mohan
World Journal of Advanced Engineering Technology and Sciences
Big Data and Business Intelligence
article

Breaking down attribution modeling in predictive analytics

Ashish Mohan
article en

Abstract

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.

World Journal of Advanced Engineering Technology and SciencesVol. 15(2)
Openalex Percentile: Top 80%
Big Data and Business Intelligence
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Breaking down attribution modeling in predictive analytics — Ashish Mohan · World Journal of Advanced Engineering Technology and Sciences (2025) | TGRS Research Map | TGRS