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Analytics Capability in Marketing Education: A Practice-Informed Model

Kurtzke, Simone; Setkute, Justina


Justina Setkute


As marketing continues to be transformed by technology and the explosion of big data, academic research has identified a significant need for analytics skills in marketing education. However, it is unclear whether current curriculum approaches to marketing analytics equip students with the skills employers need and prepare them effectively for data-driven marketing roles. This study identifies the knowledge and skills marketing graduates require for analytics practice to bridge the theory-practice gap and increase students’ employability. Our research reveals that a blend of knowledge, soft and technical skills is needed, and that the ability to communicate insights from data to stakeholders is critical. We offer a practice-informed model which demonstrates that conceptual knowledge, technical skills, tools skills and soft skills are required to develop holistic analytics capability for marketing practice. Actionable takeaways for how educators can embed holistic analytics teaching in marketing education are also provided.


Kurtzke, S., & Setkute, J. (2021). Analytics Capability in Marketing Education: A Practice-Informed Model. Journal of Marketing Education, 43(3), 298-316.

Journal Article Type Article
Online Publication Date Sep 13, 2021
Publication Date 2021-12
Deposit Date Sep 14, 2021
Publicly Available Date Sep 14, 2021
Journal Journal of Marketing Education
Print ISSN 0273-4753
Electronic ISSN 1552-6550
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 43
Issue 3
Pages 298-316
Keywords marketing education, data analysis skills, digital marketing analytics, analytics education, marketing practice, business schools, theory-practice gap
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Analytics Capability In Marketing Education: A Practice-Informed Model (469 Kb)

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Copyright Statement
This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed

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