This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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105
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Type:
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Invited
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and Marketing
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| Abstract - #306236 |
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Title:
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Randomized Experiments for Measuring Display Advertising Effectiveness
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Author(s):
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Taylan Yildiz*+ and Nicolas Remy
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Companies:
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Google and Google
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Address:
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, , ,
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Keywords:
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display advertising ;
randomized experiments ;
split testing ;
optimization ;
koopman lift estimator ;
site effectiveness
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Abstract:
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Measuring effectiveness of display ads requires more than tying impressions to conversions as we would like to know what the users would have done had they not seen the ad. The gold standard for quantifying the impact of a campaign above and beyond the user's innate propensity to convert is through randomized experiments, where users are split into treatment and control groups. While the treatment group is exposed to campaign ads, the control users see public display announcement ads. Quantifying the lift requires some statistical care as the very low conversion rates require asymmetric confidence intervals that are bound by zero. We also built a model to understand the relationship between the conversion probability and the distribution of impressions across sites.
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