channel planning

The Value of “Other” Media

Given the current focus on social media and streaming services as advertising vehicles, it is worth paying attention to studies that remind us of the value of radio and Out-Of-Home (OOH). 

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The ARF Attention Measurement Validation Initiative: Phase 1 Report Updated


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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Augmented Reality – Unlock New Technology to Drive Brand Growth

Aarti BhaskaranGlobal Head of Research & Insights, Snap

Kara LouisGroup Research Manager, Snap

Aarti Bhaskaran and Kara Louis of Snap presented their amalgamation of work on augmented reality (AR) with key data and client case studies from the last two years. Showcasing the growth of the AR landscape, Aarti and Kara featured how consumers are gravitating towards AR and the expanding number of opportunities available for advertisers in reaching new audiences and utilizing within the media mix. Case studies include brands using AR try-on technology from Champs Sports and Clearly eyeglasses. Key takeaways:
  • AR usage is widespread and growing, from Boomers to GenZ. By the year 2025 there will be approximately 4.3 billion AR users across all generations.
  • Almost all marketers (91%) think consumers use AR for fun, but 67% of consumers prefer using AR for shopping over fun (53%).
  • Interacting with products that have AR experiences leads to a 94% higher purchase conversion rate, as individuals can better assess them and feel connected with brands. Certain AR applications can substitute physical shopping with different features varying across the customer journey.
  • Interactive and personalized shopping experiences reach Gen Z—92% are interested in using AR for shopping, with over half of Gen Z saying they’d be more likely to pay attention to ads using AR. Gen Zs are also twice as likely to buy items that they have experienced first using AR than those who don’t.
  • AR lenses on Snapchat outperformed all other media formats. Other platforms would need 14-20 ads to generate the same level of attention as Snapchat lenses.
  • AR not only drives short-term impact with higher purchase intent and brand preference, but it also improves brand opinion, influences implicit associations and increases likelihood to purchase and recommend.
  • The creative attributes that include logo and product branding, complexity, messaging and user experience show a significant relationship with AR performance in brand lift.

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The Value of Attention is Nuanced by the Size of the Brand

Karen Nelson-Field, Ph.D.CEO, Amplified Intelligence

This presentation discussed the importance of nuance and interaction effects and how understanding interaction effects are critical in building products. There were four use cases—campaign strategy, planning, verification, buying. Two sets of data—inward and outward facing—looked at tag-based data through tags, outward facing—device based, panel data, gaze tracking, pose estimation, etc. One is observed while the other is human. Both are valuable. Each set has limitations. Looking at actual humans has a scale issue, whereas impression data has limited ability to predict behavior. Human behavior is complex. It is also varied by platforms. Metrics without ground truth misses out on this. Three types of human-attention were measured: active attention (looking directly at an ad), passive attention (eyes not directly on ad), non-attention (eyes not on screen, not on ad). Attention outcomes and attention are not always related. Underneath how attention data works there is a hierarchy of attention—the way ad units and scroll speeds and other interaction effects all mediate with each other. It is not as simple as saying look at this ad unit and we will get this amount of attention. If products don’t include these factors they fail. Amplified Intelligence built a large-scale validation model for interaction effects and “choice” using Pepsi. They employed logistic regression using Maximum Likelihood Estimation (MLE), analyzing observations and tested critical factors—brand size and attention type, to demonstrate strong predictive accuracy with CV accuracy. They found significant interaction effects, particularly brand size and attention type as key influencers of consumer brand choice. Key findings:
  1. Passive and active attention work differently. Passive attention works harder for bigger brands, while active attention works harder for smaller brands. Put differently, small brands need active attention to get more brand choice outcomes.
  2. Attention switching (focus) mediates outcomes. The nature of viewing behavior mediates outcomes. Not just attention yes or no, and what level, but about behavior across time. This is why time-in-view fundamentally fails even though it is considered one of the critical measures of attention. Humans are constantly switching between attention and non-attention. There’s attention decay—how quickly attention diminishes (sustained attention x time). There’s attention volume—the number of people attentive (attentive reach x time).
  3. Eyes on brand attention is vital for outcomes. If the brand is not at the point when people are looking (or hearing), this impacts outcomes. When the brand is missing, we fill in the blanks, but the next generation of buyers are being “untrained.”
  1. Human attention is nuanced, complicated, making it difficult to rely merely on aggregated non-human metrics for accuracy. We must constantly train these models, just like GenAI, to ensure that all these nuances are fit into the model. A human first approach is critical.
  2. Outcomes cannot predict attention. Attention can predict outcomes but not the other way around.
  3. Attention strategies should be tailored to campaign requirements (not binary quality or more/less time). Overtime attention performance segments will start to think about other AI.
Key takeaways:
  • Human attention is nuanced. This makes it difficult to rely only on aggregated non-human metrics for accuracy.
  • A human-first approach is critical.
  • Outcomes cannot predict attention.
  • Attention strategies should be tailored to campaign requirements.

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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.

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


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?"

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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

  • 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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One Size [Does Not] Fit All Optimizing Audio Strategies for Success

What spot length works best? Audacy partnered with Veritonic to compare frequent radio listener responses to 15, 30 and 60-second ads across multiple categories such as auto, financial, retail and professional services to address this frequently asked question. Jenny Nelson (Audacy) and Korri Kolesa (Veritonic) presented the results of this study, which were measured by Veritonic’s audio score components such as attribute score, intent score and engagement score. This survey-based study of a panel of 2,400 radio listeners pointed to a variety of recommendations, such as initiating multiple 30-second ads instead of fewer 60-second ads, testing creative before launch and deploying a total audio strategy to reach omnichannel listeners.