There has been a coup d'état in media. Content used to be king, but it has been deposed and replaced. Now, "audience is king," declared Eric Shenk, Technical Director, Office of the CTO, Google Cloud Media at the recent TV Data Summit in New York City. Why have audiences taken over the prime consideration in media? Part of the answer is the primacy of data in the consumer journey. With access to first, second and third party datasets, marketers and programmers can more easily and efficiently parse who is motivated, who is engaged and who is ready to transact. But how can we know which datasets are relevant, what might be missing and how to best analyze the results? Read on for relevant takeaways from the TV Data Summit.
The Impact of Data
The availability of data has led to a seismic philosophical change in the media pipeline. The focus used to be on delivering audiences to advertisers. But now, with audiences more in control of their viewing choices, companies need to consider what triggers their choice and attention.
Radha Subramanyam, Chief Research and Analytics Officer at CBS, said her company's world class global content and brand championship in a safe environment with a passion for innovation is all tied together with cutting edge analytics supported by data. In looking at the ad marketplace today, she noted that data can be used by targeting demographics to gain mass reach and brand awareness, from data enabled TV to target optimization and addressable for one to one messaging.
"Data is everything," declared Shenk, because it touches all aspects of the media business. Currently, though, it is highly fragmented, residing in silos within companies and behind walled gardens with frenemy companies. As best as is possible, data needs to be collected, transformed, analyzed and visualized -- and then the best decisions must be made from the insights.
Consumers are in Charge
Larry Allen, Vice President Ad Innovation and Programmatic at Turner, noted the shift in focus from the client to the consumer. "TV is under siege," he warned. While advertising strives to make the experience better for the client, "what if it is alienating the consumer?" he asked. "We need to put them front and center."
He explained that the current ad model is not working because there is too much frequency, not enough relevancy and too much mass. "Really long ads can work depending on what you are trying to achieve," he asserted. "We have new customer engagement metrics to improve our understanding of what is happening. We want to put ads in front of people that make sense so they don't avoid them."
To that end, Turner embarked on consumer journey research to find out what builds affinity for content, identifying consumer content needs and the path they took to make decisions. "This can make things more contextually relevant in real time, and it can be leveraged," he said. "But it is hard to scale today, and it is a long-term horizon project."
The Challenge of Measurement
The wide possibilities that data brings to the media business are offset by some of the challenges it creates. "Measurement to business outcomes has been challenging," admitted Julie DeTraglia, Head of Research at Hulu. Tracking content across screens, calculating co-viewing on shared platforms and establishing an industry standard for cross-platform measurement are all worthy goals that require a joint industry effort between companies that often compete.
CIMM, now part of the ARF, has been focused on establishing a universal content labeling code on ads and programming. This initiative is beginning to gain traction. Jane Clarke, Managing Director and CEO, CIMM noted that there is "a lot of support for data but sometimes data produces different results because there is no national dataset. We need to understand what is under the hood."
Initiatives like OpenAP have enabled frenemy companies to work together to bind datasets together to segment audiences for sales. For Haile Owusu, Senior Vice President, Analytics, Decisions and Data Sciences at Turner, the focus is on algorithmic output. "We forecast bulk audience flows and the ability to probe intra-show behavior, identifying components of the content for additional churn," he explained. He is working on the blending of linear and digital consumption by coupling linear TV viewing with viewing on devices and to messaging on apps.
Conclusion
Data and analytics, fueled by machine learning and artificial intelligence, will make the media business more efficient and targeted. If frenemy companies can work together, the opportunities offered by data will multiply and the challenges it presents will be subtracted. The TV Data Summit put all of the innovative approaches out there. Now is the time for the industry to move forward.
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