research methods

Optimizing Big Data + Panel Measurement Through Calibration

Optimizing Big Data + Panel Measurement Through Calibration

David Kurzynski – SVP, Data Science, Nielsen

Kyle Poppie – VP, Data Science, Nielsen

It is challenging to measure the smaller audiences of local TV and measurement challenges include false zero audience metrics and instability. Kyle Poppie (Nielsen) reviewed the evolution of local TV measurement, and this presentation demonstrated how Nielsen’s approach enables accurate measurement. Calibrating big data to a probabilistic panel controls for biases in the big data population that cannot be accounted for by weighting alone. The panel provides accurate and unbiased measurement at aggregate levels while big data provides greater coverage of granular behavior. An example demonstrated how the calibration of panel data and big data resulted in a more accurate weighted audience size. David Kurzynski (Nielsen) presented a case study that applied calibration to live data from a secondary station in New York. The improved result included fewer zero ratings and smoother trends. Key takeaways:
  • The goal of calibration is to achieve local TV measurement that provides accuracy and stability for audience levels and audience flows.
  • Both big data and panel data are critical as inputs to calibration to achieve these goals. Audience levels are informed by both big data and panel homes, and audience flows are influenced by big data.
  • Relative and total errors decrease as a result of calibration compared to panel-only currency.

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

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

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%).

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CTV Ads: Viewer Attention & Brand Metrics

CTV Ads: Viewer Attention & Brand Metrics

Rohan Castelino – CMO, IRIS.TV

Mike Treon – Programmatic 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.

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Inside the Journal of Advertising Research: Sonic Branding, ASMR Engagement, and Who Wins in Activist Messaging?

Inside the Journal of Advertising Research: Sonic Branding, ASMR Engagement, and Who Wins in Activist Messaging?

  • JOURNAL OF ADVERTISING RESEARCH

At this Insights Studio, researchers in Europe, the U.K. and the U.S. presented work in relatively new fields that have high-impact potential for the advertising industry. Starting with a forthcoming paper on sonic branding, the authors described their ground-breaking framework for measuring the implicit effects of sonic branding using music to manipulate visual scenes in video, film and TV. Next, a deep dive into autonomous sensory meridian response (ASMR)—a sensory-inducing device in ads—included strategies for helping brands collaborate with successful ASMR influencers. Lastly, a preview of an article to be published in the March Prosocial Advertising Special Issue showed how brand activism influences attitudes and purchase intentions, revealing a credibility gap between established activist brands and brands emerging in that space. Taking questions from Paul and from attendees, panelists in the concluding Q&A explored links between sonic branding and ASMR, the demographics of ASMR followers, ways for emergent activist brands to close the credibility gap with established activist brands, and future research possibilities.

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Minimizing Risk and Inspiring Innovation When Using GenAI and LLMs

Minimizing Risk and Inspiring Innovation When Using GenAI and LLMs

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.

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The ARF Handbook for Using AI in Advertising Research

The ARF Handbook for Using AI in Advertising Research

Significant developments in AI have occurred in the last two years, allowing it to be used in various places in the advertising industry. One area that has received little attention however is advertising research. Recognizing this, the ARF has conducted a significant number of its own research. The product of this effort is an AI handbook that offers practical advice in several key aspects of using AI for advertising research. Moreover, an interactive function allows experts to leave comments that, once verified, will be integrated into the report, making it a living, breathing document that continues to evolve as AI advances.

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2023 Attribution & Analytics Accelerator

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.

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Navigating the Evolving Media Landscape

Navigating the Evolving Media Landscape

  • OTT 2023

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.

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