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User Behavior Modeling in Online Display Advertising

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Date Issued:
2018
Abstract/Description:
Online display advertising intends to find the best match between advertise- ment (ad) campaigns and online users, conditioned by user specific contexts such as geographic locations, and hobbies etc. During this matching process, user behavior plays a crucial role in determining whether and when the user, who has been served the ad, will result in a conversion event. Advertisers seek to understand how users behave if they are continuously served impressions from the same campaign, as well as any noticeable patterns between campaign categorization and user behavior. This thesis carries out data analytics to investigate correlation between user behavior and campaign conversion rates (CVR), including click-through conversion rates and view- through conversion rates. We investigate campaign categorization based on both IAB categories, and campaign dfficulty level defined by effective CPA (eCPA). We carry out large scale analytics over billions of impressions from over 1000 campaigns, observing consistent patterns and significant findings.
Title: User Behavior Modeling in Online Display Advertising.
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Name(s): Van Nice, Kara, author
Zhu, Xingquan, Thesis advisor
Florida Atlantic University, Degree grantor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2018
Date Issued: 2018
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 69 p.
Language(s): English
Abstract/Description: Online display advertising intends to find the best match between advertise- ment (ad) campaigns and online users, conditioned by user specific contexts such as geographic locations, and hobbies etc. During this matching process, user behavior plays a crucial role in determining whether and when the user, who has been served the ad, will result in a conversion event. Advertisers seek to understand how users behave if they are continuously served impressions from the same campaign, as well as any noticeable patterns between campaign categorization and user behavior. This thesis carries out data analytics to investigate correlation between user behavior and campaign conversion rates (CVR), including click-through conversion rates and view- through conversion rates. We investigate campaign categorization based on both IAB categories, and campaign dfficulty level defined by effective CPA (eCPA). We carry out large scale analytics over billions of impressions from over 1000 campaigns, observing consistent patterns and significant findings.
Identifier: FA00013018 (IID)
Degree granted: Thesis (M.S.)--Florida Atlantic University, 2018.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Consumer behavior
Advertising campaigns--Data processing
Internet advertising
Held by: Florida Atlantic University Libraries
Sublocation: Digital Library
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00013018
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.