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ThinkTV Smart Lab To Employ AI In TV Advertising Research

ThinkTV is set to investigate the performance of television advertising via its purpose-built ThinkTV Smart Lab, employing artificial intelligence technologies in its research.

The lab will undertake a two-year research program, carried out in partnership with Professor Karen Nelson-Field, University of Adelaide professor of media innovation and CEO of research joint venture Media Intelligence Co, along with Media Intelligence Co.

ThinkTV states that the research “will help advertisers and media agencies get the best out of TV by providing robust evidence and greater clarity about how multi-platform TV advertising delivers business results”.

“The purpose-built facility will examine TV’s impact on brand and advertiser performance and will use artificial intelligence technologies to remove human error and bias,” ThinkTV states.

While the lab is funded by ThinkTV, ThinkTV states that it “remains independent to ensure research rigour and credibility”, with it to “comprise an oversight committee that will include ThinkTV representatives and broader industry partners, including marketers and media buyers”.

“There has never been a more important time for the media industry to take the measurement and effectiveness of video advertising seriously, and our partnership with MIC shows just how serious Australia’s TV industry is about it,” ThinkTV chief executive Kim Portrate commented.

“Karen is a world-renowned media academic with impeccable credentials for her work and independence. The lab’s findings will play an important role in evaluating TV’s credentials for advertisers who are under more pressure than ever to spend their dollars efficiently and effectively.

“The outcomes from the Smart Lab, the first of which Karen will present at our ReThinkTV marketing forum on November 30 in Sydney, will give marketers and media buyers new and retested evidence on which to determine the efficacy of multi-platform TV advertising.”

Nelson-Field noted that “‘smart’ technology, and in particular artificially intelligent measures, will operate as the foundation of all research methodologies”.

“Where existing knowledge is dated, or where knowledge does not already exist, the Smart Lab will undertake research that includes using machine learning and new computer vision technology,” she commented.

“It reduces human error, subjectivity and bias, and data is collected passively and in real-time. It is certainly more future-ready than old-school biometrics.”

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