Abstract Details
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Activity Number:
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272
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Type:
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Roundtables
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Date/Time:
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Tuesday, August 6, 2013 : 7:00 AM to 8:15 AM
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Sponsor:
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Section on Statistics in Marketing
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| Abstract - #308359 |
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Title:
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Making Causal Inferences from Observed Web Visits
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Author(s):
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Stephen Iaquaniello*+
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Companies:
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SapientNitro
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Keywords:
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Marketing Mix Modeling ;
Web Analysis ;
Granger Causality ;
Cross-Channel Mix Modeling ;
Factor Analysis
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Abstract:
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Given weekly (for instance) offline sales data and weekly visits to the various pages on the company website, how can sales be best associated to web traffic? Because the data are observational, strong causal inferences are difficult to make. This has been my task for the past two years. I would like to discuss ways I have used, from Granger causality to factor analysis to cross-channel marketing mix models, to try and solve this problem. I also would enjoy hearing from others in the discussion and finding out other ideas that they may have to relating observed web traffic with sales and other measures of success.
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Authors who are presenting talks have a * after their name.
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