TargetingVis: visual exploration and analysis of targeted advertising data

Di Peng, Wei Tian, Min Zhu, Yukun Ren, Xiaojian Lin, Mingzhao Li

Abstract: Targeted advertising is a dominant form of online advertising. It considers advertisers’ major concern of their customers, including the consumers’ certain traits, interests and individual preferences. To promote the effectiveness of advertisement delivery, advertising analysts need to understand advertiser delivery behavior and problems in targeting structure. However, statistical methods cannot meet analytical requirements completely, and analysts have to spend a lot of time reading countless data reports. Concretely, there is no efficient tool accomplishing analysis tasks such as exploring targeting usage at different levels, discovering useful or abnormal targeting combination patterns, finding competition from user behavior. In this paper, we design and implement an interactive visual analytics system named TargetingVis to visualize targeted advertising delivery data to face the challenges. After conducting a detailed requirements analysis with the domain experts from Tencent Inc., we design TargetingVis with four linked views: a novel chord diagram for cross-level exploration of targeting relations, a view for delving into the analysis of targeting combination patterns, an auxiliary view for displaying data indicators and a view to help gain insights into the behavior of advertisers. Finally, we evaluate the usability and efficiency through experiments based on real-world datasets. Graphic abstract