Advances in Multi-Channel Attribution Modeling for Enhancing Marketing ROI in Emerging Economies

• Author(s): Abiodun Yusuf Onifade ; Jeffrey Chidera Ogeawuchi ; Abraham Ayodeji Abayomi ; Oluwademilade Aderemi Agboola ; Remolekun Enitan Dosumu; Oyeronke Oluwatosin George
• Paper ID: 1708473
• Page: 360-376
• Published Date: 31-12-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 5 Issue 6 December-2021

Abstract

Advances in multi-channel attribution (MCA) modeling have become pivotal in optimizing marketing return on investment (ROI), especially within the dynamic context of emerging economies. Traditional attribution models, such as last-click or first-touch, often fail to capture the complexity of consumer journeys that span multiple digital and offline channels. As emerging markets experience rapid digital transformation and increasing consumer access to varied media platforms, the need for robust, data-driven attribution frameworks becomes more pronounced. Recent developments in data analytics, machine learning, and artificial intelligence (AI) have enabled the construction of sophisticated MCA models that offer granular insights into channel effectiveness, temporal influence, and user interactions. These models allow marketers to allocate budgets more efficiently by accurately assessing the contribution of each touchpoint toward conversion. In emerging economies, where marketing budgets are often constrained and consumer behavior exhibits significant heterogeneity, the implementation of advanced MCA techniques can be a game-changer. The integration of real-time data sources such as mobile usage, social media engagement, and e-commerce transactions enhances the precision of attribution metrics and supports agile marketing strategies. Moreover, innovations in probabilistic and algorithmic attribution models, such as Markov chains and Shapley value-based approaches, further empower marketers to understand non-linear pathways and synergistic channel effects. Despite these advancements, several challenges remain, including data fragmentation, limited technological infrastructure, and a shortage of analytical talent. Nonetheless, the trajectory of MCA modeling in emerging economies is promising, driven by growing investment in analytics capabilities and increasing demand for accountability in marketing expenditures. This review explores these advances and evaluates their implications for enhancing marketing ROI in diverse, rapidly evolving markets. By leveraging cutting-edge attribution methodologies, businesses in emerging economies can unlock deeper customer insights, optimize cross-channel performance, and achieve more sustainable growth in competitive digital environments.

Keywords

Advancement, Multi-channel, Attribution, Modeling, Enhancement, Marketing, ROI, Emerging economies

Citations

IRE Journals:
Abiodun Yusuf Onifade , Jeffrey Chidera Ogeawuchi , Abraham Ayodeji Abayomi , Oluwademilade Aderemi Agboola , Remolekun Enitan Dosumu; Oyeronke Oluwatosin George "Advances in Multi-Channel Attribution Modeling for Enhancing Marketing ROI in Emerging Economies" Iconic Research And Engineering Journals Volume 5 Issue 6 2021 Page 360-376

IEEE:
Abiodun Yusuf Onifade , Jeffrey Chidera Ogeawuchi , Abraham Ayodeji Abayomi , Oluwademilade Aderemi Agboola , Remolekun Enitan Dosumu; Oyeronke Oluwatosin George "Advances in Multi-Channel Attribution Modeling for Enhancing Marketing ROI in Emerging Economies" Iconic Research And Engineering Journals, 5(6)