Note
Includes bibliography.
Member of
Contributors
Publisher
Florida Atlantic University
Date Issued
2018
EDTF Date Created
2018
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.
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.
Language
Type
Form
Extent
69 p.
Subject (Topical)
Identifier
FA00013018
Additional Information
Includes bibliography.
Thesis (M.S.)--Florida Atlantic University, 2018.
FAU Electronic Theses and Dissertations Collection
Date Backup
2018
Date Created Backup
2018
Date Text
2018
Date Created (EDTF)
2018
Date Issued (EDTF)
2018
Extension
FAU
IID
FA00013018
Organizations
Attributed name: Florida Atlantic University
Attributed name: College of Engineering and Computer Science
Person Preferred Name
Van Nice, Kara
author
Graduate College
Physical Description
application/pdf
69 p.
Title Plain
User Behavior Modeling in Online Display Advertising
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.
http://rightsstatements.org/vocab/InC/1.0/
Origin Information
2018
2018
Florida Atlantic University
Boca Raton, Fla.
Physical Location
Florida Atlantic University Libraries
Place
Boca Raton, Fla.
Sub Location
Digital Library
Title
User Behavior Modeling in Online Display Advertising
Other Title Info
User Behavior Modeling in Online Display Advertising