The measurement of attention in advertising continues to evolve, redefining how advertisers assess ad creative and media quality. In practice, the broad term “attention” encompasses direct observations of individuals noticing, focusing on, or responding to stimuli and various proxy signals that many argue represent scalable indicators of human attention. As AI becomes more sophisticated and ubiquitous, algorithms trained on massive datasets of prior direct tests now compete by providing synthetic predictions of attention.

The ARF will showcase recent attention research from the perspectives of advertisers and agencies, along with preliminary findings from Phase 3 of the Attention Measurement Validation Initiative. Practitioners and academics will discuss the latest results and debate the growing significance of attention metrics in advertising and media measurement.

Our colleagues, Graham and Kenneth will give the following presentation at 11:40-12:00.

The Value of Universal Facial Signals in Advertising and Attention Research 
Despite being one of the most widely used non-verbal methods in research to understand viewer engagement, facial coding still stirs debate. Learn about new evidence, based on analysis of the Affectiva database of 14 million face videos, which reveals universals in facial expressions and demonstrates that these expressions have predictive power concerning key advertising outcomes. Insight will also be shared about the role of context in interpreting biometric signals, to aid in the effective use of such tools by the marketing industry. 
Graham Page – Managing Director, Affectiva Media Analytics, iMotions 
Kenneth Preston – Senior Data Scientist, Affectiva Media Analytics, iMotions