The ARF Knowledge Center provides secondary research services for ARF and ARF-MSI members on a broad range of topics. Analysis of ARF member questions posed to the Knowledge Center in 2023 shows distinct trends and interests posed by different constituent members. As always, most questions tend to be specific to the unique business needs of each member, but there were some overarching trends, which highlight the evolving landscape of the marketing and advertising industry. This FAQ discusses these trends alongside sample member questions and Knowledge Center research reports.
On April 4, industry experts explored where out-of-home (OOH) advertising stands today, its current capabilities and its potential in the future. Attendees heard data-backed insights on how OOH has changed in the past decade, where it fits in a multi-channel campaign or media plan, and brands’ objectives in using it.
Sharmilan Rayer of Amazon Publisher Cloud discussed an approach to empowering addressability as legacy identifiers (cookies and mobile IDs) fade. This approach, called durable addressability, includes the sharing of first-party signals across publishers, advertisers and third parties. Its three pillars are first-party signal investment, secure signal collaboration and machine learning (ML) powered modeling. The Amazon Marketing Cloud is their new advertiser clean room which takes this approach. It allows advertisers to combine their first-party signals with Amazon’s publisher ones and any third-party’s in a privacy compliant way.
Key takeaways:
Durable addressability starts with each member investing in first-party data from a resource, funding and technology perspective.
Sixty percent of advertisers report planning to leverage first-party data for ad placements, and 47% of publishers say their first-party data is the answer to cookie deprecation.
The first-party data advertisers would bring to this strategy includes customer engagement, conversions and proprietary audiences.
Amazon has access to publisher first-party data across CTV, web, mobile and audio. Having access to this first-party data allows for determining which ad opportunities are best for a particular campaign.
As cookies deprecate, clean rooms will begin playing a more important role, according to Amazon.
Modeling by machine learning has increased reach 20-30% on unaddressable supply, Amazon claims.
A new product called Performance Plus combines Amazon Ads signals, advertiser conversion signals and machine learning to generate predictive segments. It has been observed boosting conversions 30-80%.
Aarti Bhaskaran – Global Head of Research & Insights, Snap
Kara Louis – Group 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.
Can YouTube help drive long-term brand building? How do you measure long-term brand building? When brands want to air strategic long-term campaigns, they typically revert to traditional media. Most people are not in need of a brand’s immediate offering, but they represent the biggest sales opportunity. Ten years ago, the IPA demonstrated that campaigns whose primary focus was emotional were the most effective. Emotions are the fuel that allow high conversion over time. Brands should tap into emotions of consumers that may not be interested in a product now but may be relevant in the future. Ipsos partnered with Google Creative Works to study the observed and declared behaviors.
Methodology: A triangulation of methods were used. They were Creative/Spark (market validated KPIs of creative impact); Ipsos Bayesian Nets (models the impact of emotion); Ipsos Emotion Framework (captures emotional responses). Ipsos Emotion Framework defines emotions as physiological changes we experience in response to the environment. These are complex emotions that are heavily driven by culture and context, and they are therefore, not universal. This complicates measuring emotions. While emotions are not universal, we can explain emotions based on valence, arousal and control. This maintains the cultural authenticity but can be compared across cultures. The experimental approach to measuring long-term brand growth included a brand relationship index (BRI), comprised of brand performance = how would you rate [brand] in terms of what you are looking for in a [category] + brand closeness = how close do you feel to [brand]?
Findings:
Valence alone explains 28% of variance of long-term brand sales growth for YouTube videos. Highly pleasant residual emotions on YouTube ads have predictive power over long-term brand growth. This works for both YouTube ad formats (skippable and forced).
Highly pleasant YouTube ads make people willing to pay more, reducing price sensitivity.
The highly pleasant emotions that correlated with valence were warmth, happiness, calmness, love, nostalgia and excitement.
Empathy and surprise become important predictors of the brand relationship change index in the long term.
To analyze how respondents group emotions when reporting how ads make them feel, a sophisticated analytic technique based on Bayesian network was applied. This method shows that ads can awaken different emotions, not just one emotional note. Empathy and surprise are more neutral by nature, and this can lead to either positive or negative emotions. They can be bridge emotions between negative and positive emotions.
Key takeaways:
Digital media like YouTube can be a prime brand building vehicle, not only for short-term tactical business objectives.
Highly pleasant emotions account for 28% of long-term brand growth. Brands should leverage this knowledge to create powerful, emotional storytelling to get closer to current and prospective clients.
Positive emotional storytelling supercharges performance. It makes people more willing to pay more for a brand.
Emotional storytelling doesn’t mean focusing on one single tone—brands can experiment with several emotions to create powerful and emotionally stirring narratives.
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 saidit 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.
Alexis Harris – Global Research & Insights Partner, Marketing Science, TikTok
Jaclyn Williams – Research and Insights Manager, NA & Global Functions, TikTok
Alexis Harris and Jaclyn Williams of TikTok explained best practices for developing successful multilingual campaigns. Their data came from a survey where bilingual Hispanic TikTok users evaluated different creative elements in Spanish, to see how best to positively influence brand perceptions and business outcomes. This group feels one hundred percent both American and Hispanic culturally. They prefer to see and hear things in both languages throughout the day, a desire not currently being met by brands. Done consistently and authentically, language resonance can transfer into long-term benefits like brand loyalty and advocacy. Voiceover was the number one creative element to lift upper and mid-funnel metrics. Importantly, Spanish voiceover did not turn off English only speakers.
TikTok partnered with NRG to conduct this 20-minute quantitative survey. It leveraged in-context ad exposure. They analyzed 32 ad variations (such as adding Spanish voiceover, music or subtitles) across four verticals: beauty, auto, QSR dining and telco. The survey was given to 1,600 monthly TikTok users in the US: 1,200 were multilingual, while 400 were English-only speakers. They found that fluency in Spanish is diverse. Researchers put respondents into three groups: English dominant, bilingual and Spanish dominant. Thirty-four percent of respondents identified completely with Hispanic culture, 31% identified completely with American culture and 17% completely with both.
Key takeaways:
Sixty-nine percent said bilingual ads made them feel seen and represented.
Sixty-three percent of bilinguals liked seeing both languages throughout their day, 59% wanted to see both languages in their social feeds and 59% wanted to encounter both English and Spanish when seeing ads.
Bilingual audiences are 2.5 times more likely to share ads that use multiple languages. They are also three times more brand loyal when advertised to in Spanish.
Seventy-one percent of respondents wanted to see more celebrities from their own culture, 66% liked ads that referenced everyday life and 63% wanted more influencers from their culture in ads.
Spanish voiceover was the most effective creative technique. It drove positive brand perceptions, brand connection, engagement and consideration. Captions were the second most effective technique, driving all but consideration. Music only drove brand engagement.
After experiencing a Spanish voiceover in an ad on TikTok:
Thirty-eight percent of bilinguals watched product reviews about the brand on the social media platform, and 57% watched more ads on TikTok from the brand.
Fifty-two percent shared the ad on TikTok, and 27% talked about it with a friend or family member.
Brand favorability was at 61% of non-Spanish speaking usersafter encountering a bilingual English-Spanish ad.
The ARF’s annual AUDIENCExSCIENCE conference highlighted the most critical audience measurement issues. Through keynotes, panels, debates and rigorously peer-reviewed research presentations, attendees learned about a wide array of new and evergreen industry topics, endemic to our industry changes. World-class thinkers joined us in NYC to share their perspectives on the future of advertising research and measurement, and how tomorrow’s technologies and data trends will impact advertising and media.
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:
Some ads achieve their desired effects with lower attention than others.
Platform attention averages mislead media selection because they leave out the effect of the creative and the effect of motivations.
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.
Prof. Rachel Kennedy – Associate Director (Product Development), Ehrenberg-Bass Institute for Marketing Science
Beginning her discussion, Rachel Kennedy (Ehrenberg-Bass Institute) noted that Artificial Intelligence (AI) and other developments in computational advertising could mean key media principles, developed for traditional advertising, no longer apply. She examined empirical evidence, primarily focused on traditional media, which validated the idea that for media to thrive, it must consistently reach category buyers with both continuity and recency. Nevertheless, she acknowledged the evolving landscape of media. Building on that notion, she detailed two field experiments using social media, conducted with Stephen Bellman and Zachary Anesbury, also from the Ehrenberg-Bass Institute. The experiments aimed to assess: (1) whether AI-based optimization outperformed simpler, evidence-based optimization methods by implementing algorithms on YouTube and Meta platforms and (2) whether bursting, compared to continuous advertising, was more effective in reaching category buyers. The experimental design considered matched cells (e.g., randomized zip codes, matched demographics, people per HH, median weekly income, monthly repayments, motor vehicles per dwelling, etc.). Additionally, there were equal budgets per cell. Rachel noted that the standing principles will likely still have a role, but the research aimed to understand which ones and how they contribute to the current media landscape. Results from the experiments tended to be uneven and varied, indicating room for improvement.
Key takeaways:
AI and ML in programmatic advertising are discovering and using new media principles that may generate results from a variety of data points, better than any human could.
Experiment 1 (platform optimizer vs. simple reach principle): AI-based optimization beat simpler, evidence-based reach optimization, considering results for impressions, clicks and reach, reported by the digital agency responsible for scheduling the media.
However,AI did not outperform the simple media principles.
These findings suggest that using traditional media placement strategies can be just as effective as AI-based strategies for certain goals.
Experiment 2: Bursting is better than continuous advertising for reaching as many category buyers as possible.
However, neither campaign performed significantly better than the unexposed control cell.
Overall results from these experiments were messy, indicating the need for improvement, particularly in tools on the platform end (e.g., inadequate capping options, high budget spending and the need for enhancements in forecasting tools).
