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Activity Number:
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210
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Type:
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Contributed
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Date/Time:
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Monday, August 7, 2006 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and Marketing
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| Abstract - #306805 |
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Title:
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Uplift Modeling in Direct Marketing
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Author(s):
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John Lin*+ and Qizhi Wei
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Companies:
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Epsilon
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Address:
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601 Edgewater Drive, Wakefiled, MA, 01880,
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Keywords:
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uplift ; incremental ; direct marketing (DM) ; ROI ; predictive model
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Abstract:
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In the past, predictive models were evaluated based only on the ability to generate additional responses/sales compared to randomly audiences. With growing demands for marketing accountability, statisticians are increasingly being asked to build uplift models that identify consumers who are most positively influenced by DM campaigns and show the incremental impact of DM programs so that ROI can be more accurately measured. This in turn leads to better decisions about how marketing dollars are spread across channels as well as better decisions about overall marketing budgets. This article discusses the pros/cons of different approaches to build and validate the uplift models. In-market results will be used to illustrate how models can be enhanced. We will also propose a new method to implement the uplift models, which has been applied to a recent marketing campaign with great success.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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