Abstract Details
Activity Number:
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582
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Type:
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Invited
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Date/Time:
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Wednesday, August 12, 2015 : 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 #314598
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View Presentation
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Title:
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Performance of Marketing Attribution Models
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Author(s):
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Stephanie Sapp* and James Koehler and Jon Vaver and Neil Bathia and Minghui Shi
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Companies:
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Google and Google and Google and and Google
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Keywords:
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Abstract:
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Attribution models allocate credit to marketing channels for cross-channel marketing campaigns. We present a process for evaluating the efficacy of attribution models using simulation. The proposed simulations generate user-level activity streams using a non-stationary Markov model. The transition matrix in this model is modified by the appearance of advertising impressions, which are injected into the activity stream with a specified probability. By increasing or decreasing this probability of an ad impression, it is possible to run virtual experiments to measure ad effectiveness. The results of these experiments are used to evaluate a set of commonly used attribution models.
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Authors who are presenting talks have a * after their name.
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