Mixed-media modeling may help optimize campaign recognition and brand interest: how to apply the 'Mixture-amount modeling' method to cross-platform effectiveness measurement
- Author
- Leonids Aleksandrovs, Peter Goos, Nathalie Dens and Patrick De Pelsmacker (UGent)
- Organization
- Abstract
- The current study applied a "mixture-amount modeling" statistical approach-used most often in biology, agriculture, and food science-to measure the impact of advertising effort and allocation across different media. The authors of the current paper believe advertisers can use the mixture-amount model to detect optimal advertising-mix allocation changes as a function of their total advertising effort. The researchers demonstrated the use of the model by analyzing Belgian magazine and television data on 34 advertising campaigns for beauty-care brands. The goal is to help advertisers maximize desirable outcomes for campaign recognition and brand interest.
- Keywords
- COMMUNICATION, SALES, INFORMATION, TELEVISION, STRATEGIES, PRODUCTS, ALLOCATION, PRINT, INTERNET, BROADCAST MEDIA
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-7057965
- MLA
- Aleksandrovs, Leonids, et al. “Mixed-Media Modeling May Help Optimize Campaign Recognition and Brand Interest: How to Apply the ‘Mixture-Amount Modeling’ Method to Cross-Platform Effectiveness Measurement.” JOURNAL OF ADVERTISING RESEARCH, vol. 55, no. 4, ADVERTISING RESEARCH FOUNDATION, 2015, pp. 443–57, doi:10.2501/JAR-2015-025.
- APA
- Aleksandrovs, L., Goos, P., Dens, N., & De Pelsmacker, P. (2015). Mixed-media modeling may help optimize campaign recognition and brand interest: how to apply the “Mixture-amount modeling” method to cross-platform effectiveness measurement. JOURNAL OF ADVERTISING RESEARCH, 55(4), 443–457. https://doi.org/10.2501/JAR-2015-025
- Chicago author-date
- Aleksandrovs, Leonids, Peter Goos, Nathalie Dens, and Patrick De Pelsmacker. 2015. “Mixed-Media Modeling May Help Optimize Campaign Recognition and Brand Interest: How to Apply the ‘Mixture-Amount Modeling’ Method to Cross-Platform Effectiveness Measurement.” JOURNAL OF ADVERTISING RESEARCH 55 (4): 443–57. https://doi.org/10.2501/JAR-2015-025.
- Chicago author-date (all authors)
- Aleksandrovs, Leonids, Peter Goos, Nathalie Dens, and Patrick De Pelsmacker. 2015. “Mixed-Media Modeling May Help Optimize Campaign Recognition and Brand Interest: How to Apply the ‘Mixture-Amount Modeling’ Method to Cross-Platform Effectiveness Measurement.” JOURNAL OF ADVERTISING RESEARCH 55 (4): 443–457. doi:10.2501/JAR-2015-025.
- Vancouver
- 1.Aleksandrovs L, Goos P, Dens N, De Pelsmacker P. Mixed-media modeling may help optimize campaign recognition and brand interest: how to apply the “Mixture-amount modeling” method to cross-platform effectiveness measurement. JOURNAL OF ADVERTISING RESEARCH. 2015;55(4):443–57.
- IEEE
- [1]L. Aleksandrovs, P. Goos, N. Dens, and P. De Pelsmacker, “Mixed-media modeling may help optimize campaign recognition and brand interest: how to apply the ‘Mixture-amount modeling’ method to cross-platform effectiveness measurement,” JOURNAL OF ADVERTISING RESEARCH, vol. 55, no. 4, pp. 443–457, 2015.
@article{7057965,
abstract = {{The current study applied a "mixture-amount modeling" statistical approach-used most often in biology, agriculture, and food science-to measure the impact of advertising effort and allocation across different media. The authors of the current paper believe advertisers can use the mixture-amount model to detect optimal advertising-mix allocation changes as a function of their total advertising effort. The researchers demonstrated the use of the model by analyzing Belgian magazine and television data on 34 advertising campaigns for beauty-care brands. The goal is to help advertisers maximize desirable outcomes for campaign recognition and brand interest.}},
author = {{Aleksandrovs, Leonids and Goos, Peter and Dens, Nathalie and De Pelsmacker, Patrick}},
issn = {{0021-8499}},
journal = {{JOURNAL OF ADVERTISING RESEARCH}},
keywords = {{COMMUNICATION,SALES,INFORMATION,TELEVISION,STRATEGIES,PRODUCTS,ALLOCATION,PRINT,INTERNET,BROADCAST MEDIA}},
language = {{eng}},
number = {{4}},
pages = {{443--457}},
publisher = {{ADVERTISING RESEARCH FOUNDATION}},
title = {{Mixed-media modeling may help optimize campaign recognition and brand interest: how to apply the 'Mixture-amount modeling' method to cross-platform effectiveness measurement}},
url = {{http://doi.org/10.2501/JAR-2015-025}},
volume = {{55}},
year = {{2015}},
}
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