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Geo-Spatial Modeling of Online Ad Distributions

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Date
2013-04-25
Author
Gorecki, Mitchel
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Abstract
The purpose of this document is to demonstrate how spatial models can be integrated into purchasing decisions for real-time bidding on advertising exchanges to improve ad selection and performance. Historical data makes it very apparent that some neighborhoods are much more interested in some ads than others. Similarly, some neighborhoods are also much more interested in some online domains than others, meaning viewing habits across domains are not equal. Basic data analysis shows that neighborhoods behave in predictable ways that can be exploited using observed performance information. This paper demonstrates how it is possible to use spatially correlated information to better optimize advertising resources.
Description
Winner of the 2013 Allen Starling Johnson, Jr. Best Thesis Prize and Honors thesis for Graduation with Distinction in Economics.
Type
Honors thesis
Department
Economics
Subject
Spatial
Advertising
Online
Ad Distribution
Real Time Bidding
MaxPoint
Permalink
https://hdl.handle.net/10161/8009
Citation
Gorecki, Mitchel (2013). Geo-Spatial Modeling of Online Ad Distributions. Honors thesis, Duke University. Retrieved from https://hdl.handle.net/10161/8009.
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  • Undergraduate Honors Theses and Student papers
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Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

Rights for Collection: Undergraduate Honors Theses and Student papers


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