TV

Key Takeaways

• The geo-based experiment addressed the understanding of changing behavior in the physical stores for Burger King, through increased sales related to media spend. This technique gave the ability to measure the uplift between control and treatment to understand media impact. The geo-experiment focused on three KPIs: store sales, store transactions and deal take rate (promotion featured in the ad).
Results from the geo-experiment indicated:
• Store sales generated by linear TV were flat but store sales increased in views from YouTube.
• Store transactions generated by linear TV decreased while YouTube views increased store transactions.
• In terms of the deal take rate (deal shown in the ad) the take rate was higher generated by linear TV, though it still generated positive returns from YouTube.
• Audience incrementality testing was conducted by Comscore (3rd party incrementality validation). Through this process, they wanted to understand if they were reaching a new target audience and if their message was reaching anyone that may not have heard their message on linear TV alone.
Audience incrementality testing resulted in the following:
• Accounting for the target audience of adults 18-49 was critical in the short and long term.
• YouTube reached 78 million adults ages 18-49. In addition, 34 million of the viewers were YouTube-only, unique viewers.
• There were 43,365,489 cross-platform unique viewers.
• 20,680,526 were unique linear TV-only viewers with 64 million total linear TV viewers.

Key Takeaways

• From the mildest episodes to the most violent, viewer attention remained stable. Attention to high risk episodes measured in at 51.5%, with attention to low-risk episodes at 51.4%.
• Viewers don’t attribute blame to advertisers. “There’s more reward than risk,” according to Emily. Viewers tend to enjoy brands that are sponsoring the content they love, controversial or not—8 in 10 agree that they don’t distrust brands that advertise in graphic TV shows.
• Several rare cases where gratuitous violence immediately preceding an ad break did carry negative sentiment into the first seconds of the ad.

Key Takeaways

• It is essential for advertisers to measure the reach and effectiveness across multiple avenues of ad exposure rather than consider exposures in platform silos. The importance of this approach will increase as media consumption continues to evolve and cross-platform consumption grows.
• Understanding which targets can not only be reached but also activated by various platforms results in more effective campaign planning.
• Based on this knowledge clients can shift dollars between channels to better optimize their campaigns in real time and prior results can be used to inform future work.
• Marketers can sub-target their campaigns by creating multiple targets, based not only on media consumption, but also media responsiveness to improve each targets’ projected ad effectiveness.
• An effective causal multi-touch attribution (MTA) approach should provide stable, reliable results that have been researched and tested across hundreds of real campaigns and simulated data to ensure that the approach is yielding accurate results.

Key Takeaways

• Forecasting should always be done based on content.
• In reviewing the accuracy of predicting exact programming, the forecast to actuals had a 71% program match. In predicting programming type, there was 94% accuracy.
• Results for the long-term audience forecasts had 42% MAPE (mean absolute percentage error) improvements overall using big data sources.

Key Takeaways

• New tool that captures emotional engagement through skin response.
• Three fundamental metrics are validity, reliability and predictability.
• Generated macro insights through a robust taxonomy. Power of premium video content yield strong emotional engagement (EE).

Key Takeaways

• The number of connected devices per household has increased from 9 to 12 since the pandemic, creating a more complex path in which to reach consumers.
• Despite being separate platforms (e.g., linear TV, social media, online video, etc.) media is “inextricably commingled together,” leading to "context switching and about getting the right content to the right consumer."
• In terms of long-form video, "Linear television is still the juggernaut in the room at 205 billion [viewing] hours." Total video across linear, CTV and digital grew 5% year-over-year in the U.S. CTV viewing increased by 14% of the total hours watched.
• Short-form video continues to rise in popularity through Instagram Reels, TikTok and YouTube Shorts. This trend in short-form video consumption is growing in double-digit percentages and redefining video consumption across mobile and connected TV screens.
• The emergence of Generation Z is changing the marketer approach to brand love and establishing loyalty and building long-term value as their consumer behavior is in contrast to previous cohorts. This is specific to their lack of brand loyalty.
• In terms of media consumption, Generation Z are heavy movie watchers (37%), preferring dramas (29%) and cooking shows (23%). Additionally, they expressed interest in local news and documentaries.
• Social media is still growing (11%) but there are fewer linear TV households (-9%) as people are consuming media elsewhere and CTV has increased substantially (32%).
• Though there was a clear decline in linear TV viewership, linear TV remains supreme regarding total viewership for one channel.
• In terms of incremental reach over the length of a campaign, linear TV reached a lot of viewers in the early part of a campaign, but over time the study indicated "reaching incremental people on CTV and digital more often." This finding acknowledged the advantages of a cross-screen campaign in terms of optimizing reach.
• Adding screens in a campaign improved brand lift but the variability of results also increased. Additionally, results for ad recall and other variables followed a similar pattern. It was noted that the optimal platform mix depended on the target audience.

Key Takeaways

• The struggle that the advertising and marketing industry is currently having is that "there is no universal definition of content quality that is easily measurable in cross-media systems."
• "Content quality is being used as this proxy for content impact." For example, "What is the impact of the content on my brand equity, my campaign objective, by marketing or business objectives?" All of these factors are specific to the marketer, the brand and the campaign.
• When it comes to exposure metrics, advertisers and marketers should be consistently counting impressions across all channels, "because you need to count things to value them."

Key Takeaways

• Reach measurement has drawbacks: even though it acknowledges audience size, it does not measure ad impact. Reach measurement treats all impressions as equal regardless of the content, and while platform and the quality of the content matter, their impact cannot currently be proven.
• Ten percent of respondents to a recent MarketCast survey found that in a digital environment, ads associated with premium content (professionally produced vs. user-generated content (UGC)) had more credible messaging.
• Sixty-two percent who watched a premium clip remembered the ad and the brand correctly versus 49% of those who viewed a UGC clip. In addition, 56% of premium clip viewers thought the ad spoke directly to them, versus 43% who said an ad in a UGC clip spoke to them.
• The resonance score is built from CTV/streaming ACR data, opportunity to see (OTS) surveys for linear TV, tags on digital ads (known exposure) and on social—OTS through memory triggers and surveys.
• Using the always on approach, they survey people about ads they have seen on TV, CTV or social within a 24-hour window. The big pool of participants is used to normalize all other factors, so to see what network or platform would best suit a client’s ad.
• Ad resonance rating is meant to become an interoperable metric that complements traditional reach and frequency measures and other currency metrics.

Key Takeaways

• Brands that increased their spend in non-premium digital lost sales and market share, much of it due to misallocation of advertising spend. There are opportunities for 20-40% ROI increases by reallocating non-premium digital dollars to TV.
• TV has 2.6x the sales effect of non-premium digital. There is a 14.6% incremental sales lift added by advertising, on top of the baseline 85% sales without advertising. TV generated 69% of the added 14% across the combined three verticals, with non-premium digital at 27%. In all three verticals studied, broadcast entertainment still has a good amount of headroom—increasing share of ad spend will increase sales effects.
• Buyer focus on CPM and rush to oversaturated lower-priced media and non-premium digital inventory has served to suppress the sales effects of overall campaigns.
• Focusing on ROAS instead of reach, and using standard multiple regression analysis gives advertisers an advantage over slower-moving competitors.
• For impressions quality, context still matters.