Skip to main content

Real-Time Television ROI Tracking Using Mirrored Experimental Designs

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7867))

Abstract

Real-time conversion tracking is the holy grail of TV advertisers. We show how to use thousands of tiny areas available via commercial cable and satellite systems to create low cost tracking cells. These areas are created as “mirrors” of a national campaign, and run in parallel with it. With properly controlled areas, it is possible to calculate national effects due to TV using statistical methods. We show performance of the method on a large-scale TV advertising campaign where it was used successfully to maintain a real-time CPA target of $60 for 179 days.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Angrist, J., Pischke, J.: Mostly Harmless Econometrics. Princeton University Press (2010)

    Google Scholar 

  2. D’Agostino, R.: Tutorial In Biostatistics: Propensity Score Methods for Bias Reduction in the Comparison of a Treatment to a Non-Randomized Control Group. Statistics in Medicine 17, 2265–2281 (1998)

    Article  Google Scholar 

  3. Duda, R., Hart, P., Stork, D.: Pattern Classification, 2nd edn. Wiley (2000)

    Google Scholar 

  4. Hanssens, D., Parsons, L., Schultz, R.: Market Response Models: Econometric and Time Series Analysis. Kluwer Academic Press, Boston (2001)

    Google Scholar 

  5. Hu, Y., Lodish, L., Krieger, M.: An Analysis of Real World TV Advertising Tests: a 15 year update. Journal of Advertising Research 47(3), 341–353 (2007)

    Article  Google Scholar 

  6. Johansson, J.K.: Advertising and the S-Curve: A New Approach. Journal of Marketing Research 16(3), 346–354 (1979)

    Article  Google Scholar 

  7. Joo, M., Wilbur, K., Zhu, Y.: Television Advertising and Online Search, SSRN Working paper (2012), http://ssrn.com/abstract=1720713

  8. Kitts, B., Wei, L., Au, D., Powter, A., Burdick, B.: Attribution of Conversion Events to Multi-Channel Media. In: Proceedings of the Tenth IEEE International Conference on Data Mining, December 14-17 (2010)

    Google Scholar 

  9. Kitts, B., Au, D., Burdick, B.: Television Conversion Tracking using Anonymized Set Top Box Data (unpublished, 2013)

    Google Scholar 

  10. Kokernak, M.: What’s Television’s Next Business Model? Media Post Daily News, March 17 (2010)

    Google Scholar 

  11. Lambert, D., Pregibon, D.: Online effects of Offline Ads. In: Proceedings of the Second International Workshop on Dataa Mining and Audience Intelligence for Advertising. ACM Press, New York (2008)

    Google Scholar 

  12. Leaders. In: Praise of Television: The great survivor. The Economist (April 2010)

    Google Scholar 

  13. Lewis, R., Reiley, D.: Down-to-the-Minute Effects of Super Bowl Advertising on Online Search Behavior. Working Paper (2010), http://davidreiley.com/papers/DownToTheMinute.pdf

  14. Lewis, R., Rao, J.: On the Near Impossibility of Measuring Advertising Effectiveness, Yahoo! Research working paper (2011), http://justinmrao.com/lewis_rao_nearimpossibility.pdf

  15. Little, R., Rubin, D.: Causal Effects in Clinical and Epidemiological Studies Via Potential Outcomes: Concepts and Analytical Approaches. Annual Review of Public Health 21, 121–145 (2000)

    Article  Google Scholar 

  16. Lodish, L., Abraham, M., Kalmenson, S., Livelsberger, J., Lubetkin, B., Richardson, B., Stevens, M.: How T.V. Advertising Works: A Meta-Analysis of 389 Real World Split Cable T.V. Advertising Experiments. Journal of Marketing Research 32(2), 125–139 (1995a)

    Article  Google Scholar 

  17. Lodish, L., Abraham, M., Kalmenson, S., Livelsberger, J., Lubetkin, B., Richardson, B., Stevens, M.: A Summary of Fifty-five In-Market Experimetns on the Long-term Effect of TV Advertising. Marketing Science 14(3), 133–140 (1995b)

    Article  Google Scholar 

  18. Nelson-Field, K., Riebe, E., Sharp, B.: What’s Not To Like?; Can a Facebook Fan Base give a Brand the Advertising Reach it needs? Journal of Advertising Research (2012)

    Google Scholar 

  19. Rosenbaum, P., Rubin, D.: Constructing a Control Group Using Multivariate Matched Sampling Methods That Incorporate the Propensity Score. The American Statistician 39(1) (1985)

    Google Scholar 

  20. Rubin, D.: Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies. Journal of Educational Psychology 66(5), 688–701 (1974)

    Article  Google Scholar 

  21. Simon, H.: Price Management. North-Holland Publishing Company, Amsterdam (1989)

    Google Scholar 

  22. Simon, J.L., Arndt, J.: The Shape of the Advertising Response Function. Journal of Advertising Research 20(4), 767 (2002)

    Google Scholar 

  23. Sinnott, R.: Virtues of the Haversine. Sky and Telescope 68(2), 159 (1984)

    MathSciNet  Google Scholar 

  24. Vakratsas, D., Feinberg, F., Bass, F., Kalyanaram, G.: Advertising Response Functions Revisited. Marketing Science 23(1), 109–119 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kitts, B., Au, D., Burdick, B. (2013). Real-Time Television ROI Tracking Using Mirrored Experimental Designs. In: Li, J., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2013. Lecture Notes in Computer Science(), vol 7867. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40319-4_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40319-4_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40318-7

  • Online ISBN: 978-3-642-40319-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics