attention

The Power of AI for Effective Advertising in an ID-free World

Rachel GantzManaging 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%).

Download Presentation

Member Only Access

CTV Ads: Viewer Attention & Brand Metrics

Rohan CastelinoCMO, IRIS.TV

Mike TreonProgrammatic Lead, PMG

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 drives brand metrics (e.g., 2x higher unaided recall and 4x higher aided recall).
    • 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.

Download Presentation

Member Only Access

How Attention Measurement Optimizes Marketing Campaigns for Success

Neala BrownSVP of Strategy and Insights, Teads

Laura ManningSVP of Measurement, Cint

This presentation focused on the intersection of attention and brand lift. The partnership between Teads and Cint relates to the challenge of scalability, access to data and insights, and collaboration and innovation. They used normative data sets in order to examine the performance. Beyond viewability, in partnership with Adelaide who uses AU—an omnichannel metric that predicts the probability of placement to capture attention and drive subsequent impact— they conducted 17 studies in 2023. There were variance in results, in statistical significance, outcomes, etc. Results: #1 case study—media that scored highly attentive showed higher product familiarity and favorability; #2 case study—for a flat and neutral campaign, higher attention drove higher brand lift across every brand funnel metric. In terms of applicability, from a media planning perspective, this learning can be leveraged toward outcomes. When aggregating across all 17 case studies, frequency matters—lower frequencies require more AU to move metrics. People who are already familiar react to lower AU media. For favorability—more “energy” or AU is needed to move people here, it’s easier to move people with high level of familiarity. For ad recall—even at higher exposure levels, the ad needs to be high quality and needs more attention. Notably, these case studies can be replicated. Key takeaways:
  • Frequency matters: lower frequencies require more AU to move metrics.
  • Familiarity reacts to lower AU media.
  • Favorability: it’s easier to move people with high level of familiarity.
  • For ad recall, the ad needs to be high quality.

Download Presentation

Member Only Access

Retail Media Networks, Generative AI Top JAR’s Industry-Informed Research Priorities

  • JOURNAL OF ADVERTISING RESEARCH

Retail media networks, generative AI across creative, market research and trust, ad effectiveness and attention: These are among the topics highlighted on the Journal of Advertising Research’s list of 2024 research priorities. The list is a result of one-on-one interviews with advertising professionals by Editor-in-Chief Colin Campbell, who asked: "What are your biggest needs and challenges?"

Member Only Access

Too Much Attention?

One expert argues that attention alone does not bring ad success and that we should not forget the other important levels of the “ARF Model.”

Read more »

Cross-Platform Measurement Options from an Agency Perspective

Audience measurement is changing at an unprecedented rate. Concurrently, identifiers such as cookies are fading, and traditional models and incumbent suppliers are being questioned. In reaction to all these happenings, new measurement initiatives and a new Joint Industry Committee (JIC) have risen to establish a path toward a new video measurement framework. In 2023, the Online-Offline Metrics Working Group, within the ARF Cross-Platform Measurement Council, conducted anonymous, in-depth-interviews (IDIs) with eight key decision-makers from major agency holding companies. The IDIs focused on three major issues involving the metric situation confronting the advertising industry. This report summarizes the learnings from those interviews.

Member Only Access

Super Bowl Ads Revisited

As all media are full of analyses, polls and commentaries, with this year’s Super Bowl ads, it is worth looking at research insights from past Super Bowls.

Read more »

AI’s Impact on Marketing

Arguably, this emerged only in 2023 as a top research issue. AI is likely to play a major role in many of the topics discussed below, such as research quality, marketing strategies, measurement and attention metrics. 

Read more »

2023 Attribution & Analytics Accelerator

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.

Member Only Access