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Generative AI for Marketing Content Creation: New Rules for an Old Game Cover

Generative AI for Marketing Content Creation: New Rules for an Old Game

NIM Marketing Intelligence Review
Volume 16 (2024): Issue 1 (May 2024)
By: Mark Heitmann  
Open Access
|Apr 2024
References

References

  1. Brand, J., Israeli, A., & Ngwe, D. (2023). Using GPT for Market Research. Harvard Business School Marketing Unit Working Paper No. 23–062. SSRN: https://ssrn.com/abstract=4395751
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  2. Burnap, A., Hauser, J. R., & Timoshenko, A. (2023). Product Aesthetic Design: A Machine Learning Augmentation. Marketing Science, 42(6), 1029–1056.
    Search in Google ScholarBack to article
  3. Jansen, T., Heitmann, M., Reisenbichler, M., & Schweidel, D. A. (2023). Automated Alignment: Guiding Visual Generative AI for Brand Building and Customer Engagement. SSRN: https://ssrn.com/abstract=4656622
    Search in Google ScholarBack to article
DOI: https://doi.org/10.2478/nimmir-2024-0002 | Journal eISSN: 2628-166X
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Language: English
Page range: 10 - 17
Published on: Apr 25, 2024
Published by: Nuremberg Institute for Market Decisions
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
GenAI,
Marketing Content Creation,
Marketing Productivity,
Content Quality
Related subjects:
Business and economics,
Political economics,
Public finance and fiscal theory,
Business management,
Marketing, sales, customer relations,
Management, organization, corporate governance,
Business management, other

© 2024 Mark Heitmann, published by Nuremberg Institute for Market Decisions
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.

Volume 16 (2024): Issue 1 (May 2024)
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