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. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2018. / FAU Electronic Theses and Dissertations Collection