Matching Ads With Emotional Context To Programming: Wurl's AI Approach

Wurl, a connected TV ad-tech company owned by marketing platform AppLovin, has embarked on an interesting approach to ad monetization. Partnering with BrandDiscovery with its GenAI-powered contextual targeting, Wurl is said to be able to “precisely match ads with the emotion and context of programming in real time,” according to Wurl’s vice president of business development for agencies and brands, Peter Crofut.

He explained that by aligning an ad’s emotion to the content’s emotion, brands can improve viewer memorability and campaign engagement -- which, he says, “ultimately drives stronger outcomes and performance. Our own data has shown that advertisers can experience a significant uplift in conversion of 2-3x when they find moments of emotional resonance.”

Interview has been edited for clarity and length.

Charlene Weisler: How does the AI matching component work?

Peter Crofut: Wurl uses GenAI to analyze the emotion of the content in the scene closest to the ad break. That analysis is based on Robert Plutchik’s wheel of emotions, which includes eight primary emotions at three different intensities (high, medium, and low) that can be combined to represent the full spectrum of human emotional states.



Once the emotional score for the scene is determined, it is then matched to an ad with a similar emotional score. This prevents viewers from having a jarring experience where, say, they’re crying from watching a sad scene and are then disrupted with an overly upbeat ad. When scenes and ads are misaligned -- that’s where negative attention can be created for a brand.

Weisler: What data is collected – how is the platform measured?

Crofut: To determine the emotional segments of the content for BrandDiscovery, we leverage GenAI to view and analyze content from a variety of different sources including images, sound, and text. From there, BrandDiscovery assigns, at a scene level, the corresponding emotional value as determined by the AI.

Notably, with GenAI, we offer scene-level targeting through BrandDiscovery as opposed to categorizing an entire program, series or channel under any one contextual category. Equally, BrandDiscovery’s targeting is free – we don’t charge any data fees for emotional segments. In terms of measurement, we work with independent partners like EDO and Kantar to look at things like campaign effectiveness, brand awareness, brand favorability, and purchase intent for BrandDiscovery campaigns.

Weisler: How does scene-level analysis work?

Crofut: BrandDiscovery was born out of a curiosity to consider whether or not ads that were emotionally aligned with content perform better. During initial testing, we discovered that the most significant correlation with ad engagement took place when the emotions depicted in the scene just before the ad break aligned with those portrayed in the ad creative.

As a result, Wurl developed its own GenAI models trained against millions of assets to analyze content in real time.

Weisler: Can you give an example of what a campaign looks like?

Crofut: We recently partnered with Media.Monks, tasked with executing a CTV campaign for a financial services client. Using BrandDiscovery’s emotion-based targeting to run CTV ads across Wurl’s network of premium content publishers, Media.Monks was able to bolster the resonance of its client’s brand messaging and optimize targeting for more impactful brand engagements. The client saw a 7x lift in aided brand awareness and 2x lift in purchase intent.

Weisler: What are the opportunities here?

Crofut: CTV offers massive potential for brands to connect with audiences in meaningful ways, especially as the biggest screen in the home. And, while contextual targeting on CTV certainly isn’t a new concept, we’re confident in the idea that emotions-based targeting is truly reshaping how we think about this approach today. By aligning ads based on the emotional context of the scene right before the ad break, brands can meet audiences where they already are and not just increase attention, but increase positive attention among viewers.

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