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Home » MarketCast Launches Hybrid AI and Human Advertising Research Solution
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MarketCast Launches Hybrid AI and Human Advertising Research Solution

Paul E.By Paul E.September 26, 2024No Comments2 Mins Read
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Marketing research and intelligence company MarketCast has announced MarketCast Ad Effect Express, an innovative new ad testing solution that combines the power of human research with AI to more accurately predict the performance of TV, CTV and digital ads across different audience segments.

Typical ad testing is either survey-driven, where people see ads and answer researchers’ questions, or leverages AI models to predict human responses with little to no human intervention. Human surveys are in-depth but often expensive and time-consuming, and AI models are fast but often built on narrow, outdated research and overly broad audiences. MarketCast Ad Effect Express combines the best of both worlds, delivering cost-effective speed, scale, and accuracy.

“Many of today’s AI-powered ad testing solutions sacrifice quality for speed by removing humans from the process,” said John Batter, CEO of MarketCast. “At MarketCast, we believe AI should amplify the consumer voice in ad research, not replace it. That’s why MarketCast Ad Effect Express gives advertisers a smarter, faster, and more cost-effective way to test their ads without losing the power of the human connection.”

Taking a closer look, MarketCast Ad Effect Express is powered by MarketCast’s proprietary Audience AI, which uses the latest research data to train AI models and scale audiences to predict how real people will respond to ads, allowing advertisers to capture nuances of human opinion that AI solutions alone would miss, while also allowing them to access hard-to-reach audiences without the significant costs associated with acquiring audience samples.

MarketCast Ad Effect Express delivers ad testing studies within 24-48 hours of submission, with face and eye tracking to pinpoint emotional responses to ad creative down to the second. Plus, it allows for answering open-ended questions, providing more context on ad predictions so brands can learn why their ad creative is performing (or not) when it’s in front of consumers.

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