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SeeHer and Horowitz Research’s Gen Z Vibe Check

SeeHer and Horowitz Research’s Gen Z Vibe Check

Tarya Weedon – Cultural Insights Strategist, Horowitz Research

Yatisha Forde – Senior Director, Insights & Thought Leadership, ANA

Tarya Weedon of Horowitz Research and Yatisha Forde of the ANA discussed how to connect and create trust with Gen Z through accurate representation, authentic allyship and honest dialogue. This generation is redefining American culture with their views on gender, sexuality and fluidity. Champions of gender equality, they are a vocal cohort at the forefront of reversing the negative effects of traditional gender rules and stereotypes. Gen Z are hyperaware of when a campaign’s message is inauthentic or a brand does not “walk the walk.” Fewer Gen Z than other generations think advertising accurately reflects them. Tarya and Yatisha offered advice on how to pass the “vibe check” with this generation. Their study had two legs, a qualitative phase which was interacting over a two-week period with an online community with 70 Gen Zers in the U.S. The quantitative phase was an online survey among 800 U.S. respondents ages 14-to-24. Key takeaways:
  • Forty percent of Gen Zers said labels should be chosen by the individual, not society.
  • Over 50% said both male and female identifying people can do anything from using makeup to doing manual physical labor, and from being emotional to being in STEM.
  • Eighty-eight percent disagree that increased acceptance of non-traditional ways about gender and sexuality is bad for society.
  • Half of Gen Z self-identify as gender non-binary, and 64% identify as sexually fluid.
  • Forty-six percent said claiming support wasn’t enough. To be seen as trustworthy, a brand needs to show its support in action.
  • Forty-seven percent said it felt like pandering when an ad highlighted a cause that they’re not involved in.
  • Although respondents thought that all brands have a responsibility to influence perceptions about gender and sexuality, they felt some types of brands have a bigger responsibility than others. The biggest responsibility came to beauty/self-care brands (50%), clothing (49%), pharma/health (20%) and food/beverage brands (18%).
  • Just 47% of respondents felt like advertising accurately reflected their generation.
  • Recommendations included making diversity part of the brand ethos, reimagining gender and sexuality in advertising content, leveraging SheHer guides and GEM best practices, including more diversity and aspects of intersectionality in advertising and finding ways to open dialogue that is inclusive and without judgment.

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Linear vs. Streaming: Current State of Creative and Media

Linear vs. Streaming: Current State of Creative and Media

Nicole Lawless DesJardins, Ph.D. – Sr. Director Data Science, iSpot.tv

Leslie Wood, Ph.D. – CRO, iSpot.tv

Leslie Wood and Nicole Lawless DesJardins, both of iSpot.tv, provided an overview of advertising trends in linear and streaming over the last two years in terms of ad creative, campaign and measurement. They defined linear as any content purchased on a national schedule and noted that variations exist across industries. Among their findings:
  • Streaming creatives outnumbered linear 2:1 during 2022 and 2023, and the share of streaming creatives increased in 2023.
  • In terms of creative rotation, linear creatives were on air five times longer during 2022 and 2023 than streaming creative. On linear, a smaller set of creatives will rotate on and off for over a year while on streaming, there are many creatives and each creative runs for two months.
  • The majority of impressions are on linear, but there has been a 24% year-over-year increase in streaming impressions. There are also variations depending on seasons and industries.
  • During 2022-2023, the vast majority of the campaigns in both years were linear only or linear first; however, streaming only, streaming first and mixed campaigns saw significant growth year-over-year.
Key takeaways:
  • Ad creative: Creatives ran for a shorter period of time on streaming compared to linear platforms during 2022-2023.
  • Campaign: Across industries, brands were increasingly leveraging streaming on top of traditional linear TV buys. Linear-only campaigns have declined and there have been increases in mixed and streaming-first campaigns, along with the emergence of streaming-only campaigns.
  • As much as 57% of a campaign’s audience is exposed to the campaign on both streaming and linear TV.
  • Measurement: Linear generated higher reach and frequency per campaign compared to streaming.
  • In 2023, linear’s reach surpassed streaming’s reach across industries, and average frequency is nearly 2.5x higher on linear.
  • The sweet spot of frequency on streaming is approximately four and is less variable than linear due to better targeting and frequency control within the streaming environment.

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

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

Ben Cunningham – Director, Ad Experience Measurement, NBCUniversal

Simran Srinivasan – Product 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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OOH Measurement’s Game Has Changed

OOH Measurement’s Game Has Changed

Christina Radigan – SVP, Research & Insights, Outfront

Christina Radigan of Outfront explored the advantages of out-of-home advertising (OOH) and discussed advancements in its measurement techniques. Christina noted that with the loss of cookies and third-party data, contextual ad placement will see a renewed sense of importance, and in OOH, location is a proxy for context, driving content. She further indicated the benefits of OOH citing a recent study by Omnicom, using marketing mix modeling (MMM), which found that increased OOH spend drives revenue return on ad spend (RROAS). This research also highlighted that OOH is underfunded, representing only 4% to 5% of the total media marketplace. Following up on this, Christina pointed to attribution metrics, measuring the impact of OOH ad exposure on brand metrics and consumer behaviors, to demonstrate OOH's effectiveness at the campaign level. Expanding on their work in attribution, she noted changes stemming from the pandemic: Format proliferation and greater digitization, privacy-compliant mobile measurement ramping up (opt-in survey panel and SDK) and performance marketing and measurement becoming table stakes for budget allocations. New measurement opportunities from OOH intercepts included brand lift studies, footfall, website visitation, app download and app activity and tune in. Finally, she examined brand studies conducted for Nissan and Professional Bull Riders (PBR), showcasing the effectiveness of OOH advertising in driving recall, ticket sales and revenue. Key takeaways:
  • MMMs return to the forefront, as models become more campaign sensitive and are privacy compliant (powered by ML and AI).
  • A study from Omnicom, using MMM, found that optimizing OOH spend in automotive increased brand consideration (11%) and brand awareness (19%). In CPG food, optimizing OOH spend increased purchase intent (24%) and optimizing OOH spend in retail grocery increased awareness (9%).
  • OOH now represents a plethora of formats (e.g., roadside ads, rail and bus ads, digital and print) and has the ability to surround the consumer across their journey, providing the ability to measure up and down the funnel, in addition to fueling behavioral research.
  • Key factors for successful measurement in OOH: feasibility (e.g., scale and scope of the campaign, reach and frequency), the right KPIs (e.g., campaign goal) and creative best practices (Is the creative made for OOH?).
  • OOH advertising is yielding tangible outcomes by boosting consumer attention (+49%). Additionally, there has been a notable surge in advertiser engagement (+200%).
  • Ad recall rates in OOH continue to increase (e.g., 30% in 2020 vs. 44% in 2023).

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The Power of Radio Through the Lenses of Emotional Engagement

The Power of Radio Through the Lenses of Emotional Engagement

Pedro Almeida – CEO, MediaProbe

Pierre Bouvard – Chief Insights Officer, Cumulus Media | Westwood One

The presentation focused on determining the emotional impact of AM/FM radio ads. MediaProbe was retained by Cumulus Media to measure second-by-second electrodermal activity (EDA)—a measure of the sympathetic nervous system, to see when it is activated, whether listeners were excited by the stimulus they heard. This is termed Emotional Impact Score (EIS)—an impact metric that can help understand how excited people are on a second-by-second basis and what are the elements that drive this emotion. This is an objective way of quantifying emotion in media and advertising content, capturing the emotional implicit data (what people feel). Throughout the session, participants can also dial those moments that they like/dislike—the conscious explicit capture of likes and dislikes, and are asked pre and post session questions to learn more about recall and purchase intent. Methodology: 36 AM/FM radio ads, in a simulated broadcast of 30 minutes across four genres (urban, news, adult contemporary and rock/oldies). Each “broadcast” had three ad breaks and the average commercial break had three ads. Also, 227 people participated. Each “broadcast” had a sample size of 75 people and consumers listened to at least three of the four broadcasts. Each ad was exposed to 225 people. Findings:
  1. AM/FM radio programming outperforms MediaProbe’s U.S. TV norms by 13%. Put differently, the emotional impact score is higher when listening to radio.
  2. Carry over effect: radio advertising commercial pods receive 12% higher Emotional Impact Score over TV advertising commercial pods, making radio a premium platform.
  3. Across genres, people are more engaged when listening to news—people are processing what is being said, they are paying attention. There is no valence contamination between what is being said on the news and the emotional engagement to ads.
  4. People are more engaged during radio advertising—4% more than radio content.
  5. Looking at 32 individual MediaProbe ads, there is on average a 5% higher emotional impact score in comparison to 4,670 individual MediaProbe TV ads. This research is consistent with other lab-based studies.
  6. MediaProbe also conducted a physical feature analysis of the creative to find that: 1) higher pitch contrast between programming content and ads leads to higher impact. If the content has low pitch, ads should be higher pitch and vice-versa; 2) louder ads lead to higher impact.
  7. Using a regression analysis, MediaProbe found the following best performing creative in radio ads: 1) female voiceover; 2) with jingles/with background music; 3) five brand mentions are optimal; 4) no disclaimers. This too is consistent with other research.
Key takeaways:
  • AM/FM radio programming is more engaging than TV, according to MediaProbe
  • They also found that AM/FM radio advertising outperforms TV advertising.
  • News is the most impactful genre as a high-quality contextual environment for advertising.
  • Sound contrast between radio programming and ads drives higher attention and brand recall.
  • Creative best practices: female voiceover, jingles, one voiceover and five brand mentions.
 

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EEG Illuminates Social Media Attention Outcomes

EEG Illuminates Social Media Attention Outcomes

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

Bill Harvey – Executive 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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Having In-Depth Research on Consumers’ Values Yields Tremendous Benefits

Having In-Depth Research on Consumers’ Values Yields Tremendous Benefits

  • ARF Knowledge at Hand, CMO Brief

In decades past, demographic characteristics were considered the strongest predictors of consumers’ values, attitudes and purchasing behavior. Over time, however, they have grown to become weak predictors and correlates. In this Knowledge at Hand report, Dr. Horst Stipp, EVP at the ARF, summarizes the latest and most impactful research to date on consumer values and how researching them carefully can help shape effective business strategies and impactful ad messages.

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

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.”
Implications:
  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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Top Topics at AxS 2024

  • Posted: March 15, 2024

Our analysis of the presentations during this year’s AUDIENCExSCIENCE conference shows which issues are marketers’ current priorities. 

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

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?"

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