Abstract Details
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Activity Number:
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28
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Type:
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Topic Contributed
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Date/Time:
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Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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| Abstract - #310089 |
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Title:
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Randomized Experiments for Measuring Brand Effectiveness of Online Video Ads
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Author(s):
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Lu Zhang*+ and Tim Hesterberg and Philip Clarkson and Sheng Ma and Taylan Yildiz
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Companies:
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Google and Google and Google and Google and Google
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Keywords:
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Brand effectiveness ;
Randomized experiments ;
bias correction ;
online video ads ;
survey
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Abstract:
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Collaborator: Tim Hesterberg, Philip Clarkson, Sheng Ma, Lu Zhang, Taylan Yildiz
How effective are online video ads on the web? Do they make people aware of, and like, brands? Are they still effective even if people do not finish watching them? We quantify brand effectiveness through a combination of randomized experiments, where the treatment group sees surveys from an ad campaign and the control group sees alternate ads, with online surveys. We discuss measures to reduce and correct for different kinds of bias, and how we provide actionable insights by slicing and dicing brand effectiveness by features like age, gender, and whether people finished watching the video ads.
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Authors who are presenting talks have a * after their name.
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