Integrating linear TV in cross-platform measurement was a challenge undertaken in a partnership between Lucid and Samba TV utilizing ACR (automatic content recognition) and STB (set-top box) data matched to survey responses. Stephanie Gall (Lucid) and Karen Biedermann (Samba) shared details on the inherent problems, potential solutions and biggest learnings from this integration.
Programming researchers are not getting the data they need to make informed decisions and Joan FitzGerald (Data ImpacX) uses streaming’s complex ecosystem to explain the conundrum facing programmers. Key insights into monetization and performance are not supported despite the inundation of new forms of data, leaving programmers without a comprehensive picture of their audience. Together with Michael McGuire at MSA, Joan outlined a methodology funnel that combined 1st, 2nd and 3rd party data to create equivalized metrics that, once leveraged, could meet critical programming research demands.
Sharing their cross-channel campaign evaluation using IRI’s household lift studies, Lisa Mulyk and Liz Ryan from IRI illustrated the strengths of purchased-based data and targeting across brand portfolios. Creative messaging and sales for “must have” and “nice to have” products were examined, comparing the broader affinity, lifestyle and demo audience against the more specific purchase-based audience.
Pete Doe (Xandr) and Caroline Horner (605) provided a case study of their partnership that derived results from alternative currency measurement with buy and sell side perspectives. Xandr’s nimble workflow method enabled 605’s shift from advanced targeting to a very specific, custom-built, “persuadable” target audience with a range between 2 to 10x increase in outcomes.
John Watts of CIMM moderated a panel examining presentations on innovations and changes in video measurement on day three of AUDIENCExSCIENCE 2022. The topics in this discussion included the decline in linear television, measuring new viewing habits, challenges created by the new viewing ecosystem and getting access to more personalized one-on-one data.
In this presentation, Justin Fromm of LG Ads discussed how ACR data can help uncover the inefficiencies of ads delivered via linear television. In this session, the speaker examined linear TV as still playing a vital role for advertisers. Additionally, he pointed to changes in consumer viewing habits, shifting towards streaming. He noted much of the advertising industry’s focus is on incremental reach when placing an ad on television. Leveraging ACR data, the speaker demonstrated how this more robust data source can help improve optimal reach and frequency, when advertising on television.
Insights across all touchpoints during the customer journey reveal an optimal allocation of the marketing budget and enables personalized messaging to specific targets. Marketers must be able to analyze the customer engagements during this journey for attribution and to maximize ROI. However, there are challenges for marketing due to GDPR, as well as U.S. privacy regulations and the cookie deprecation actions of Google and Apple. Additionally, 76% of consumers are concerned about how their data is being used. These challenges have resulted in the loss of scale and addressability, as well as targeting and measurement limitations.
In this presentation James Lamberti, CMO of Conviva, discussed opportunities for streaming platforms because of their measurement capabilities, particularly behavioral segmentation. The speaker examined the features of streaming platforms and exemplified how data gleaned from these platforms can lead to deep audience understanding, providing a more personalized and customized experience for the consumer.
In this session, Anastasia Leng of CreativeX argued that marketing and creative have the power to change things. In the face of an increased ad pool, which has gone up 6x in the last 20 years, ads now have a smaller shelf-life and need to be created in a more customized manner. In large part, technology has created this challenging landscape in marketing and advertising, but technology can now also help to address these new challenges. She pointed to computer vision technology which can help by supplying data created from “micro-feedback,” by clustering this information and fusing this feedback to create more useful macro-data to base decisions on.
Ariane Le Port of Google explored the relationship between augmented intelligence and creative effectiveness on YouTube. She noted that in the past, measuring creative was a challenge that was “so nuanced and so complex” that people tended to shy away from measuring it. In this session, Ariane pointed to a six-year experiment on YouTube video ads to help brands understand what is most effective in mobile video. In the experiment, they conducted A/B testing and took into account a variety of areas, such as framing, pacing, audio and other areas to find patterns of creative effectiveness. These experiments led to a partnership between Google and Ipsos to create YouTube’s ABCDs (Guidelines) for creative effectiveness. YouTube and Ipsos studied 17,000 ads in an effort to identify the creative elements that have a measurable impact, using a human and machine learning (ML) approach. Leveraging machine learning (ML) enabled them to look at large and robust datasets to gain a deep understanding of what elements work best in creative. Ariane discussed their augmented intelligence methodology which included data scope and collection, human and machine creative coding, metrics and data modeling and insights and commercialization.