neuro/biometrics

Predicting Attention to Advertising Through Machine Learning

Privacy regulations have served as the impetus for a renewed interest in contextual targeting. To be effective, an ad must be related to its context but different enough to stand out. This working paper from the Marketing Science Institute (MSI) at the ARF presents a comprehensive model leveraging eye-tracking data and XGBoost algorithms to forecast the effectiveness of ad placements in real time.

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ARF Attention Measurement Validation Initiative: Phase 2 Report

  • ARF ORIGINAL RESEARCH

Explore the latest findings from the ARF Attention Measurement Validation Initiative. The phase two report is a comprehensive examination of various attention measurement methods used in creative testing. It concludes with reflections on the challenges of attention measurement, as well as some suggestions for advertisers on how to choose and evaluate attention measurement providers.

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The ARF Attention Measurement Validation Initiative: Phase 1 Report Updated

  • ARF ORIGINAL RESEARCH

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.  

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Viewer Pre-Dispositions to Seeing an Ad in an Unexpected Language

Ben Cunningham Director, Ad Experience Measurement, NBCUniversal

Simran SrinivasanProduct Manager, Video Products, NBCUniversal

Ben Cunningham and Simran Srinivasan of NBCUniversal shared their research on whether ad effectiveness changes when the language of the ad and the content is not aligned. They specifically examined what was working and not working when targeting Spanish language speakers. Their methodology included a three-phase approach, starting with a qualitative study in local markets with high Hispanic populations (e.g., LA, Miami) as well as through virtual groups to better understand their tolerance for language fluidity that is happening on their connected TVs. This was followed by a quantitative phase (n=7,200) with an experimental design where participants were recruited to watch content as though they were watching on Peacock with similar ad loads. A post-exposure survey was conducted to evaluate brand effectiveness, ad effectiveness and general perceptions towards the experience. This phase was paired with biometric research where they used facial coding to track the information processing and unconscious responses. They tested Spanish vs. English language ads in English and Spanish language content. Overall, they found that people generally understand ads in a different language, it doesn’t affect the enjoyment of the show and there was not much difference on recall. Key findings: For Spanish language ads in English language content:
  • Strong visuals still carries the message: 78% generally understand the ads that were in a different language than the content even if they are English-only speakers.
  • Seventy-one percent said that it was not disruptive to their experience to see ads in a different language than the content.
  • There was only a 3pt difference in recall for English ads (46%) vs. Spanish ads (43%) seen in English language content. However, there was a 10% boost in recall among the Spanish dominant group for Spanish-language ads and a 10% decline in recall for Spanish-language ads among the English-only group.
  • There was not much loss of attention or processing power from beginning to the end of the Spanish language ads for all test groups (English only, bilingual and Spanish dominant).
For English language ads in Spanish language content:
  • Previous exposure to both English and Spanish language content is the top determinant in ad language receptivity. The group with the most exposure to both languages is the most receptive to the ad itself.
Key takeaways:
  • There is an actual opportunity to use English language content as an effective place to reach Spanish and bilingual speakers.
  • There is a need to be super careful and thoughtful about how we define audience segments as there is a loss of effectiveness when we reach the wrong person too many times.

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Tune-In to Discover What is Making Audiences Tune-Out

Travis FloodExecutive Director of Insights, Comcast Advertising

Duane Varan, Ph.D.CEO, MediaScience

Travis Flood (Comcast Advertising) and Duane Varan (MediaScience) presented research, which explored improving ad pod architecture, aimed at better engaging audiences by understanding what makes them tune-out. To provide framework to their research process, Travis indicated they started with a literature review, to understand the existing viewer experience. Focus was placed on the quantity, quality and relevance of the ads, in addition to media effectiveness studies (e.g., pod architecture, ad creative, getting the right viewers, etc.). Duane indicated that the literature review unveiled gaps, particularly in the examination of the content within the middle section of an ad pod. Based on this, the goal of the subsequent research was to understand the optimal duration of ad pods to optimize both the viewer experience and brand impact, difference in impact (e.g., more ads vs. fewer ads in the same break duration) and the impact of frequency on viewers and brands. The research included 840 participants who watched a 30-minute program with structured ad breaks. Feedback was measured using a post-exposure survey, neurometrics and facial coding. Results revealed that shorter pod length, grouping consistency in ad length and capping frequency at two to three ads per program as most effective. Key takeaways:
  • Optimal pod length: Two minutes or less leads to better results. After viewing 2 minutes of ads, recall begins to decrease. Recall is 2x higher at 2 minutes vs. 3 minutes, and after 3 minutes, recall is at its lowest point.
  • Viewers are more engaged as ads begin. Using facial coding data showed that for a heavy clutter cell, there was marginally less joy in the first 5 seconds of the ad, indicating that ad load impacts how viewers experience ads.
  • Facial coding data revealed that ad clutter can diminish how funny scenes are for viewers.
  • Consistency is key in ad lengths within a pod. Viewer testing showed that when ads had different lengths in a pod, it made the ad break feel longer compared to pods with ads of the same length.
  • Ad frequency was optimized at two per program. There was significant boost in ad recognition and purchase intent going from 1 to 2 exposures in a program. Capping frequency at 2-3 per program can positively impact recognition and purchase intent.

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EEG Illuminates Social Media Attention Outcomes

Shannon Bosshard, Ph.D.Lead Scientist, Playground XYZ

Bill HarveyExecutive Chairman, Bill Harvey Consulting

Advertising starts with attention. If gained and sustained long enough, brain engagement occurs. Once this happens, memory encoding might happen, and that is when incremental brand equity and sales occur. Attention economy has now reached a pivotal moment: What is it that drives attention and how is this related to outcomes? Is it media platforms or creative? The presenters took two approaches: the first was brand lift studies (focusing on the conscious) with 20,000 participants, 35 well-established brands, 60 ads, on social media platforms, using eye tracking and post exposure survey. The second approach was a neuro study focusing on the subconscious, with 50 participants, across 150 sessions, people exposed to over 1,800 ads. They used a combination of eye tracking and EEG, and RMT method for measuring motivations. Hypotheses:
  1. Some ads achieve their desired effects with lower attention than others.
  2. Platform attention averages mislead media selection because they leave out the effect of the creative and the effect of motivations.
  3. Higher order effects add to our understanding of what is “optimal”: motivation, memory encoding, immersion, cognition load.
By isolating the impact of the platform (same creatives across multiple channels), the research shows that platform is not the largest driver of outcomes. In only 25% of the times there is a statistical difference between media platforms. Instead, the creatives determine outcomes: in 96% of cases we see statistical difference between media platforms. Creatives present the best opportunity for behavior change. The platform might be the driver of attention, but creative is the driver of outcome. Put differently, platforms dictate the range of attention and how the consumer interacts, but it’s the creative that drives outcomes. Attention/non attention is affected by motivations and subconscious decisions (to be proven in future). Neuroscience taps into the subconscious— memory encoding, immersion (engagement), approach (attitude), cognitive load. They compiled overall averages to make inferences regarding where to place your ad. RMT methodology used driver tags to code an ad (or any piece of content) using human coders to see how many of these tags belong to the ad. This methodology was used to examine the resonance between the ad and the person. Key takeaways:
  • Attention drives outcomes—there’s a need to understand how it is related within that cycle.
  • Creative is key—there is a need to understand how much attention is needed to drive outcome.
  • Consider consumer motivation—this correlates with neuroscience metrics and allows for more nuanced understanding of the importance of creative in driving outcomes.

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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.

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Brand Safety, Social Targeting, and Who Needs Highly Creative Ads?

  • INSIDE THE JOURNAL OF ADVERTISING RESEARCH

At this Insights Studio, JAR authors in Australia, China and the U.S. presented their recently published research on topics that some in industry may consider controversial. One found evidence of brand safety risks in programmatic advertising when ads were placed in negative news environments, contradicting some industry research. Another discovered social targeting spillover effects that suggest advertisers rethink conventional targeting methods. Other work came with unexpected findings: that highly creative advertising—although important for attracting attention—can have harmful effects on familiar brands, while benefiting unfamiliar brands. In the concluding Q&A, panelists explored aspects of brand recall relevant to their research, and whether brand size and other media channels would affect their results.

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