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High fidelity website research : using a browser extension to provide a natural environment

Author(s)
Baker, Brandon H. (Brandon Herbert)
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Alternative title
Using a browser extension to provide a natural environment
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Glen L. Urban.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
People are spending ever increasing amounts of time online. As a result, companies are investing greater amounts of money into online advertising in an effort to influence their behavior. The impact and effectiveness of these ads is still an open question. One possible method of analyzing the effectiveness is through the analysis of clickstream data. However, this data may be difficult to obtain and does not measure behavioral change. Behavioral change is a change in consideration or preference. Surrogate sites can be used to study behavioral change but are difficult and time-consuming to create and do a poor job of mimicking certain classes of sites. This is particularly true of social media sites where the amount of content is impossible to fully reproduce and yet this content is the defining component of the web site. In this thesis, I present a Chrome extension that can be used for conducting high fidelity web site market research. The framework provides the opportunity to measure behavioral change and provide a natural environment almost identical to the actual sites. I detail the implementation of the extension and its use in a web-based media experiment with a sample size of 13,000. Preliminary results and learnings are discussed. Results suggest that use of the extension is feasible and is capable of producing significant changes in consumer consideration.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (page 59).
 
Date issued
2013
URI
http://hdl.handle.net/1721.1/85404
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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