Attention metrics have drawn a high degree of energy in the last few years, for many reasons, including the loss of behavioral signals due to privacy restrictions, growing frustration with ad viewability and its perceived limitations, attention metrics’ impact on the cross-platform measurement debate and that biometric technologies can now be applied “in the wild,” rather than just in labs.
The ARF’s Attention Measurement Validation Initiative aims to describe the attention measurement space in detail, illuminating this nascent sector. The Phase One findings include a comprehensive literature review and a report that maps out the vendor landscape in this increasingly diverse specialty. The report includes two sections. The first section describes what methods are being used, what these companies report and how and what they measure, be it ad creative or the media environment. The second section includes in-depth overviews of the 29 participating attention measurement companies. The Phase One Report is a must-read for anyone interested in attention metrics or what companies are operating in the space.
Rachel Gantz – Managing Director, Proximic by Comscore
Amidst heightened regulations in the advertising ecosystem, Rachel Gantz of Proximic by Comscore delved into a discussion of diverse AI applications and implementation tactics, in an increasingly ID-free environment, to effectively reach audiences. Rachel highlighted signal loss as a "massive industry challenge," to provide a framework for the research she examined. She remarked that the digital advertising environment was built on ID-based audience targeting, but with the loss of this data and the increase in privacy regulations, advertisers have placed their focus on first-party and contextual targeting (which includes predictive modeling). In her discussion, she focused on the many impacts predictive AI is having on contextual targeting, in a world increasingly void of third-party data, providing results from a supporting experiment. The research aimed to understand how the performance of AI-powered ID-free audience targeting tactics compared to their ID-based counterparts. The experiment considered audience reach, cost efficiency (eCPM), in-target accuracy and inventory placement quality.
Key takeaways:
Fifty to sixty percent of programmatic inventory has no IDs associated with it and that includes alternative IDs.
Specific to mobile advertising, many advertisers saw 80% of their IOS scale disappear overnight.
In an experiment, two groups were exposed to two simultaneous campaigns, focused on holiday shoppers. The first group (campaign A) was an ID-based audience, while the second group was an ID-free predictive audience.
Analyzing reach: ID-free targeting nearly doubled the advertisers’ reach, vs. the same audience, with ID-based tactics.
Results from cost efficiency (eCPM): ID-free AI-powered contextual audiences saw 32% lower eCPMs than ID-based counterparts.
In-target rate results: Significant accuracy was confirmed (84%) when validating if users reached with the ID-free audience matched the targeting criteria.
Inventory placement quality: ID-free audience ads appeared on higher quality inventory, compared to the same ID-based audience (ID-free 27% vs. ID-based 21%).
Representing the Alliance for Video Level Contextual Advertising (AVCA), Rohan Castelino (IRIS.TV) and Mike Treon (PMG) examined research conducted with eye tracking and attention computing company, Tobii. The research endeavor focused on the impact of AI-enabled contextual targeting on viewer attention and brand perception in CTV. Beginning the discussion, Rohan examined challenges with CTV advertising. He noted that advances in machine learning (ML) have empowered advertisers to explore AI enabled contextual targeting, which analyzes video frame by frame, uses computer vision, natural language, understanding, sentiment analysis, etc., to create standardized contextual and brand suitability segments. Highlighting a study of participants in U.S. households, the research specifically aimed to understand if AI-enabled contextual targeting outperformed standard demo and pub-declared metadata in CTV. Additionally, they wanted to understand if brand suitability had an impact on CTV viewers’ attention and brand perception. Results from the research found that AI-enabled contextual targeting outperformed standard demo and pub-declared metadata in CTV and increased viewer engagement. In closing, Mike provided the marketers’ perspective on the use of AI-enabled contextual targeted ads and its practical applications.
Key takeaways:
Challenges with CTV advertising: Ads can be repetitive, offensive and sometimes irrelevant, in addition to ads being placed in problematic context.
In addition,buyers are unsure who saw the ad or what type of content the ad appeared within. A recent study by GumGum showed that 20% of CTV ad breaks in children’s content were illegal (e.g., ads shown for alcohol and casino gambling).
Advertisers have begun experimentation with contextual targeting in CTV, as a path to relevance.
A study conducted with U.S. participants that examined the effects of watching 90 minutes of control and test advertisements, using a combination of eye tracking, microphones, interviews and surveys to gather data found that:
AI-enabled contextual targeting attracts and holds attention (e.g., 4x fewer ads missed, 22% more ads seen from the beginning and 15% more total ad attention).
AI-enabled contextual targeting increases brand interest (e.g., 42% more interested in the product, 38% gained a deeper understanding).
Research to understand if brand suitability had an impact on CTV viewers’ attention and brand perception found that:
Poor brand suitability makes CTV viewers tune out ads and reduces brand favorability (e.g., 54% were less interested in the product, 31% liked the brand less).
AI-enabled contextual targeted ads are as engaging as the show.
Generative AI (GenAI) and Large Language Models (LLMs) have reached a point in their development where they have become tools so powerful, they will quickly become too important to ignore. Proper use can drive greater efficiency, productivity, better automation and even become new revenue drivers, according to this concise, how-to guide written by Steven Millman, ARF board member and Global Head of Research & Data Science at Dynata. It describes best practices and potential pitfalls in data privacy and security, protecting IP, oversight and more.
The intention behind recent privacy regulations is to protect consumers from unauthorized use of their data. However, this Marketing Research Institute (MSI) working paper finds unintended consequences that are not good for the consumer or the marketplace. Researchers found such regulations reduce satisfaction with search results and increase search costs. The personalization in products and services is thus degraded, as many smaller and midsize firms are no longer able to provide the level of efficiency and personalization they once could. Larger firms, however, benefit from increased search activity which leads to increased purchase activity. As a result, such regulation leads to unintended market concentration.
The Attribution & Analytics Accelerator returned for its eighth year as the only event focused exclusively on attribution, marketing mix models, in-market testing and the science of marketing performance measurement. The boldest and brightest minds took the stage to share their latest innovations and case studies. Modelers, marketers, researchers and data scientists gathered in NYC to quicken the pace of innovation, fortify the science and galvanize the industry toward best practices and improved solutions. Content is available to event attendees and ARF members.
The media landscape continues to evolve, arguably at a faster rate than ever. Leading media and measurement experts presented research-based insights on how viewers use different forms of TV/video on various platforms. Attendees joined us at the Warner Bros. Discovery Studios in California and via livestream to understand the latest data and discussions of the data’s implications.
