(M)ad to see me?: Intelligent Advertisement Placement: Balancing User Annoyance and Advertising Effectiveness

Ngoc Thi Nguyen, Agustin Zuniga Corrales, Hyowon Lee, Pan Hui, Huber Flores, Petteri Nurmi

Research output: Contribution to journalArticleScientificpeer-review


Advertising is an unavoidable albeit a frustrating part of mobile interactions. Due to limited form factor, mobile advertisements often resort to intrusive strategies where they temporarily block the user's view in an attempt to increase effectiveness and force the user's attention. While such strategies contribute to advertising awareness and effectiveness, they do so at the cost of degrading the user's overall experience and can lead to frustration and annoyance. In this paper, we contribute by developing Perceptive Ads as an intelligent advertisement placement strategy that minimizes disruptions caused by ads while preserving their effectiveness. Our work is the first to simultaneously consider the needs of users, app developers, and advertisers. Ensuring the needs of all stakeholders are taken into account is essential for the adoption of advertising strategies as users (and indirectly developers) would reject strategies that are disruptive but effective, while advertisers would reject strategies that are non-disruptive but inefficient. We demonstrate the effectiveness of our technique through a user study with N = 16 participants and two representative examples of mobile apps that commonly integrate advertisements (a game and a news app). Results from the study demonstrate that our approach can improve perception towards advertisements by 43.75% without affecting application interactivity while at the same time increasing advertisement effectiveness by 37.5% compared to a state-of-the-art baseline.
Original languageEnglish
Article number53
JournalProceedings of ACM on interactive, mobile, wearable and ubiquitous technologies
Issue number2
Number of pages26
Publication statusPublished - Jun 2020
MoE publication typeA1 Journal article-refereed

Fields of Science

  • 113 Computer and information sciences

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