TV

Rough Waters? Downstream Effects from the Transition to Streaming Via Smart TVs

David Tice Consultant, HUB Entertainment Research

Justin FrommHead of Insights & Thought Leadership, Samsung Ads

Justin Fromm from Samsung Ads and David Tice of HUB Entertainment Research discussed how consumer behavior is changing due to greater Smart TV penetration and usage. Streaming has become the default method of watching TV for a large swath of viewers. Streaming audiences have also increasingly become more receptive to advertising. Another important trend, Smart TV operating systems (OEMs) are constantly upgraded and made easier to use. As a result, home screen interactions continue to grow. Home screens have played a significant role in content discovery, although TV brand is a moderating factor. Home screens have even helped accelerate the rise of FAST services. In an era of constant churn, coming up in a home screen search and having an advertising model or tier have become critical to retention. Key takeaways:
  • Two-thirds of people in all TV households use a CTV to stream content.
  • Home screen usage is up 140% due to manufacturers consistently improving the user experience and helping viewers find content.
  • Nearly two-thirds of Smart TV users spend most of their time with streaming. In 2022, 70% of all viewing minutes were streamed, and 62% of viewers spent more than half of their time with streaming content.
  • In Q4 of 2023, 64% of respondents said they would rather watch ads and save money on a subscription, up 7% from Q4 of 2022. Ad tolerance has been stable over the last three years.
  • All streaming was up 22% in 2023. AVOD was up 50%, while SVOD use was down 7%. Home screen use was up 117%, and deep link use was up 59% from 2020.
  • Content discovery occurs about 50% of the time from the TV’s home screen, and 50% from an app’s home screen. This varied substantially by brand. For instance, only 38% of TCL owners (bottom of the batch) found content from the home screen.
  • While most found shows from TV promos (61%) in the last year, 17% of respondents found their favorite new show through their TVs’ home screen.
  • Advertising to at-risk audiences on the TVs’ home screen increased retention by a factor of eight.
  • In the last two years, FAST services increased 16%, which was 6% faster than the two years prior. The number one reason people used a FAST app was, they found it on their TV’s home screen (36%).

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How Streaming Release Models Impact Viewing Behaviors

Rebecca FineAssociate Director, Marketing Insights, Samba TV

Cole StrainVP, Head of R&D, Samba TV

An examination of the top H1 2023 streaming shows for household viewership found that original streaming content captures audiences, according to Rebecca Fine and Cole Strain of Samba TV. Bingeing behavior is a significant household viewership change as viewers have shifted from linear to streaming TV consumption. When given the choice, viewers prefer to binge. Seventy-two percent of U.S. adults identify themselves as binge watchers. A consistent trend across viewership for streaming program premieres was that 44% of viewers watched the program in the first four days, and 78% watched the program by day 15. Bingeable shows are more likely to be completed and have higher average retention between season premiere and finale. Forty-five percent of households will finish the whole season when the season drops in bulk, but retention drops to 35% when the show is released weekly. Netflix’s propensity for the bulk release model means that more of its shows get fully consumed. Rebecca and Cole analyzed the top 50 streaming programs and found that most platforms have a high percentage of households who only watch only one show. However, 73% of viewers watch more than one top show on Netflix. Key takeaways:
  • Households like to binge. Forty-seven percent of viewing households binged top bulk release shows in H1 2023.
  • Binge watchers are more likely to watch platforms that release content this way.
  • Seventy percent of millennials are more likely to keep a subscription to streaming services that release shows in bulk.
  • Bingeability might be more important than buzz when it comes to watching a show from the premiere to finale.

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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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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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Intent and Impact: A New Measurement for DEI

James Ambalathukal Director, Strategy & Insights, Magid

Mike Bloxham EVP, Global Media & Entertainment, Magid

Mike Bloxham and James Ambalathukal of Magid partnered with twelve networks and streaming services in a study to identify factors of cultural authenticity in drama, comedy and unscripted programs. With research into the creative elements that resonate with diverse populations from qualitative studies and online surveys, Mike and James described the importance of authenticity in how audiences relate to emotional content, how they see themselves in the content and ultimately, how they perceive the content itself. The various levels of signals that diverse audiences assess as good or bad representation include storytelling components and physical production elements, which help separate out what drives positive and negative perceptions of these shows for actionable results. Key takeaways:
  • There are different levels of expectations with different genres. Sitcoms and reality content without representation can connect to audiences if relatable character journeys and storylines are present. Projecting family and community values goes far. In dramas, applying specificity and non-verbal cultural details on the set or in a character, like authentic hair and wardrobe, even if not part of the narrative, is a driver of authentic representation. Other kinds of content like adult animated shows, news programming and sports are not viewed through a DEI lens.
  • Marginalized communities value representation but don’t want to be reduced to just the racial and ethnic parts of their identity.
  • Effective representation is strongly connected to perceptions of authenticity.
  • Authenticity isn’t just a preference; it has real impact on content engagement.
  • Story elements influencing perceptions of authenticity share similarities and differences across various cohorts.

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Forecasting & Optimizing Reach in a PII Compliant Measurement Ecosystem

Spencer LambertVP, Product & Partnership Success, datafuelX

Matthew WeinmanSr. Director, Advanced Advertising Product Management, TelevisaUnivision

Reach and frequency planning requires access to unique viewership data, which has become increasingly restricted due to identity restrictions. However, challenges exist with panel-only measurement, including the undercounting of Hispanic and Spanish language coverage, stated Matthew Weinman (TelevisaUnivision). Panel data undercounts Hispanics audiences by upwards of 20%, even for broad demographics. The benefits of big data exist across audience planning, viewership measurement and outcomes. Excessive frequency can be limited while maintaining or expanding reach, as well as improving ROAS. However, there are barriers to working with big data, including PII compliance. Additionally, the size and scale of big data leads to lengthy ID forecast times and computing costs. Spencer Lambert (datafuelX) presented details of their approach to ID-level forecasting which included their reach and frequency clustering methodology. Key takeaways:
  • Advantages of clustering methodology over identity methodology for reach and frequency:
  • Efficiency and accuracy: Delivers comparable accuracy metrics
  • Lower error rates: Seven percent for cluster reach forecasts vs. 20% error rate on identity-scaled reach forecasts
  • Cross-platform reach and frequency: By scaling cluster assignments to digital IDs, this methodology can empower cross-platform management and optimization
  • Lower compute time and costs
  • PII compliant: Preserves the use of identity-level planning

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Mapping the Impact: When, How and Why TV Commercials Work Best

Jeff BanderPresident, eye square

Sandra Schümann Senior Advertising Researcher, RTL Data & Screenforce

Marvin VogtSenior Research Consultant, eye square

Screenforce conducted a series of studies beginning in 2020, examining reach, success, mapping moods and impact in relation to attention. They mapped the impact by investigating when does which type of communication work best and why? There were 8,304 ad contacts in-home, 285 participants in a natural way (living rooms). They also examined 64 brands in three countries. The largest media ethnographic study in Europe examined usage situations and scenarios. There were four different scenarios: 1) Busy Day scenario (2-6PM Mon-Fri, people are distracted and focused on other things), 2) Work is Done (after 6PM, first lower part of concentration, seeking for better mood), 3) Quality Time (8-10PM, prime time, high activation of quality time, “Super Bowl moment,” high focus on screen), 4) Dreaming Away (10PM-1AM, typically alone, before sleep, dreamlike situation). Each of the 64 ads was tested in all four scenarios. The study included a technical objective criteria, subjective feeling and creative approaches. Eye square found a way where no additional material is needed other than an instruction book, webcam and GSR. Key findings:
  1. Visual attention is highest at late night (86%). Recall for ads works best in evening (75% Quality Time and Dreaming Away). However, advertising is shown to fit better earlier in the day.
  2. Characteristics per scenario: spot liking rises when using brand jingle (audio) in Busy Day scenario. This is because during the Busy Day scenario people are distracted and the jingle can help retain their focus.
  3. On a Busy Day, use strong brands with strong branding. When work is done, use ads to create a good mood. During Quality Time, it’s time for the big stories. During Dreaming Away, less is more.
  4. In sum, it is possible to find out which scenario works best for the spot and optimize the ads and find the best possible time and spot to air the ad.
Key takeaways:
  • TV ads have a strong effect, but there are ways to improve this impact.
  • Usage scenarios of audience has impact on ad effectiveness.
  • TVs can achieve a higher effect if they take the usage scenario into account.

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Optimizing Big Data + Panel Measurement Through Calibration

David KurzynskiSVP, Data Science, Nielsen

Kyle PoppieVP, 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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