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Advertising Experiments at the Campbell Soup Company

Author

Listed:
  • Joseph O. Eastlack, Jr.

    (Campbell Soup Company)

  • Ambar G. Rao

    (New York University)

Abstract

In the mid 1970's, 19 controlled experiments in the marketplace were conducted by the Campbell Soup Company to evaluate the sales impact of advertising changes for various well established packaged food brands. Changes evaluated included: budget levels, seasonality, media type and mix, creative strategy and audience targeted. Markets defined by Selling Areas Marketing Inc. (SAMI) were used as the experimental units. One of the main findings that emerged when the experiments were viewed as a whole was that budget levels, given existing creative executions, generally had little or no impact on the sales of these well established brands. However, changes in copy strategy, media selection, media mix and targeting often produced a substantial payout. These findings had a significant influence on advertising strategy at Campbell Soup Company and led to: (a) Greater emphasis on strategic development and evaluation of copy. (b) Evaluation of a larger number of (sometimes unconventional) media. (c) Implementation of much greater differences in advertising weight in budget level tests.

Suggested Citation

  • Joseph O. Eastlack, Jr. & Ambar G. Rao, 1989. "Advertising Experiments at the Campbell Soup Company," Marketing Science, INFORMS, vol. 8(1), pages 57-71.
    • Handle: RePEc:inm:ormksc:v:8:y:1989:i:1:p:57-71
    DOI: 10.1287/mksc.8.1.57
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    Citations

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    Cited by:

    1. Navdeep Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    2. Buil, Isabel & de Chernatony, Leslie & Martínez, Eva, 2013. "Examining the role of advertising and sales promotions in brand equity creation," Journal of Business Research, Elsevier, vol. 66(1), pages 115-122.
    3. Brett R Gordon & Kinshuk Jerath & Zsolt Katona & Sridhar Narayanan & Jiwoong Shin & Kenneth C Wilbur, 2019. "Inefficiencies in Digital Advertising Markets," Papers 1912.09012, arXiv.org, revised Feb 2020.
    4. Boonchai Hongcharu, 2019. "Effects of Message Variation and Communication Tools Choices on Consumer Response," Global Business Review, International Management Institute, vol. 20(1), pages 42-56, February.
    5. Garrett A. Johnson & Randall A. Lewis & David H. Reiley, 2017. "When Less Is More: Data and Power in Advertising Experiments," Marketing Science, INFORMS, vol. 36(1), pages 43-53, January.
    6. Stefano DellaVigna & Matthew Gentzkow, 2010. "Persuasion: Empirical Evidence," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 643-669, September.
    7. Becker, Maren & Gijsenberg, Maarten J., 2023. "Consistency and commonality in advertising content: Helping or Hurting?," International Journal of Research in Marketing, Elsevier, vol. 40(1), pages 128-145.
    8. Randall Lewis & David Reiley, 2014. "Online ads and offline sales: measuring the effect of retail advertising via a controlled experiment on Yahoo!," Quantitative Marketing and Economics (QME), Springer, vol. 12(3), pages 235-266, September.
    9. Navdeep S. Sahni & S. Christian Wheeler & Pradeep Chintagunta, 2018. "Personalization in Email Marketing: The Role of Noninformative Advertising Content," Marketing Science, INFORMS, vol. 37(2), pages 236-258, March.
    10. Nordfält, Jens & Lange, Fredrik, 2013. "In-store demonstrations as a promotion tool," Journal of Retailing and Consumer Services, Elsevier, vol. 20(1), pages 20-25.
    11. Campbell, Colin & Runge, Julian & Bates, Kenneth & Haefele, Stacey & Jayaraman, Neeraj, 2022. "It’s time to close the experimentation gap in advertising: Confronting myths surrounding ad testing," Business Horizons, Elsevier, vol. 65(4), pages 437-446.
    12. Kurt P. Munz & Minah H. Jung & Adam L. Alter, 2020. "Name Similarity Encourages Generosity: A Field Experiment in Email Personalization," Marketing Science, INFORMS, vol. 39(6), pages 1071-1091, November.
    13. Navdeep S. Sahni, 2015. "Effect of temporal spacing between advertising exposures: Evidence from online field experiments," Quantitative Marketing and Economics (QME), Springer, vol. 13(3), pages 203-247, September.
    14. Frank M. Bass & Norris Bruce & Sumit Majumdar & B. P. S. Murthi, 2007. "Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship," Marketing Science, INFORMS, vol. 26(2), pages 179-195, 03-04.
    15. Philippe Aurier & Anne Broz-Giroux, 2014. "Modeling advertising impact at campaign level: Empirical generalizations relative to long-term advertising profit contribution and its antecedents," Marketing Letters, Springer, vol. 25(2), pages 193-206, June.
    16. Kirthi Kalyanam & John McAteer & Jonathan Marek & James Hodges & Lifeng Lin, 2018. "Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com," Quantitative Marketing and Economics (QME), Springer, vol. 16(1), pages 1-42, March.
    17. Daniel Zantedeschi & Eleanor McDonnell Feit & Eric T. Bradlow, 2017. "Measuring Multichannel Advertising Response," Management Science, INFORMS, vol. 63(8), pages 2706-2728, August.
    18. Manganaris Stefanos & Bhasin Ruchi & Reid Michael & Hermiz Keith B, 2010. "Analyzing Causal Effects with Observational Studies for Evidence-based Marketing at IBM," Review of Marketing Science, De Gruyter, vol. 8(2), pages 1-21, July.
    19. Randall Lewis & David Reiley, 2014. "Advertising Effectively Influences Older Users: How Field Experiments Can Improve Measurement and Targeting," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 147-159, March.
    20. Lynne Pepall & Joseph Reiff, 2017. "Targeted Advertising and Cumulative Exposure Effects: The Impact of Banning Advertising to Children in Quebec," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 51(3), pages 235-256, November.

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