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Abstract Details
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Activity Number:
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220
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Type:
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Invited
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Date/Time:
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Monday, July 30, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Marketing
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| Abstract - #303701 |
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Title:
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Automated Impact Analysis Tool
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Author(s):
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Choongsoon Bae*+ and Adam Ghobarah and Jim Koehler
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Companies:
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Google and Google and Google
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Address:
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1600 Amphitheatre Parkway, Mountain View, CA, 94043,
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Keywords:
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Statistical Inference ;
Causal Modeling ;
Propensity Score ;
Selection Bias
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Abstract:
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Google has continually developed and implemented new features and services for advertisers. An important problem is whether such new features or services have positive impact, and how much. However, making proper attribution of cause-effect relationships is difficult because 1) most recommended experimental designs are not realistic, 2) other confounding factors can lead to false attribution of cause-effect. We have developed an impact analysis tool to automatically analyze the impact of launching new features, services and products on advertisers.
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