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Bridging marketing theory and big data analytics: The taxonomy of marketing attribution

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  • Buhalis, Dimitrios
  • Volchek, Katerina

Abstract

The integration of technology in business strategy increases the complexity of marketing communications and urges the need for advanced marketing performance analytics. Rapid advancements in marketing attribution methods created gaps in the systematic description of the methods and explanation of their capabilities. This paper contrasts theoretically elaborated facilitators and the capabilities of data-driven analytics against the empirically identified classes of marketing attribution. It proposes a novel taxonomy, which serves as a tool for systematic naming and describing marketing attribution methods. The findings allow to reflect on the contemporary attribution methods’ capabilities to account for the specifics of the customer journey, thereby, creating currently lacking theoretical backbone for advancing the accuracy of value attribution.

Suggested Citation

  • Buhalis, Dimitrios & Volchek, Katerina, 2021. "Bridging marketing theory and big data analytics: The taxonomy of marketing attribution," International Journal of Information Management, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:ininma:v:56:y:2021:i:c:s0268401220314523
    DOI: 10.1016/j.ijinfomgt.2020.102253
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    Cited by:

    1. Chih-Hsing Liu & Jeou-Shyan Horng & Sheng-Fang Chou & Tai-Yi Yu & Yung-Chuan Huang & Jun-You Lin, 2023. "Integrating big data and marketing concepts into tourism, hospitality operations and strategy development," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(2), pages 1905-1922, April.
    2. Marlini Moodley & Dipolelo Fungile & Farai Nyika & Winiswa Mavutha, 2023. "Understanding Marketing Communications Strategies During and Post Covid 19: A South African Perspective," International Review of Management and Marketing, Econjournals, vol. 13(2), pages 36-46, March.

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