Abstract

Real-time bidding (RTB) is a big-data analysis process supported by technology and algorithms intended to deliver the right digital advertisement to the right consumer at the right time. It is characterized by extreme personalization and behavioral retargeting and is gaining in popularity among brands and advertisers. However, while RTB advertising is gaining popularity among incumbent brands and advertisers, webpage publishers and advertisers are investing heavily in RTB technology platforms and processes without understanding the RTB ad experience for the user. To address this gap, this paper employs both qualitative and quantitative methods to first identify key attributes of the RTB ad experience, and then build a predictive model to focus on RTB click-through, a key ad effectiveness indicator. Our model analysis results show that an RTB ad triggers both surprise and irritation in internet users, which affects the intention to click the ad. Furthermore, the results indicate that relevance is a key attribute of a successful RTB ad. With these findings, we offer insight in the RTB process and its effect on Internet users.