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

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Authors: Buhalis, D. and Volchek, K.

http://eprints.bournemouth.ac.uk/34765/

Journal: Int. J. Inf. Manag.

Volume: 56

Pages: 102253

This data was imported from Scopus:

Authors: Buhalis, D. and Volchek, K.

http://eprints.bournemouth.ac.uk/34765/

Journal: International Journal of Information Management

Volume: 56

ISSN: 0268-4012

DOI: 10.1016/j.ijinfomgt.2020.102253

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.

This data was imported from Web of Science (Lite):

Authors: Buhalis, D. and Volchek, K.

http://eprints.bournemouth.ac.uk/34765/

Journal: INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT

Volume: 56

eISSN: 1873-4707

ISSN: 0268-4012

DOI: 10.1016/j.ijinfomgt.2020.102253

The data on this page was last updated at 05:25 on April 19, 2021.