The news: FreeWheel has introduced a Contextual Marketplace in a bid to transform how streaming TV advertisements are targeted. Instead of relying on personal user data, the tech partners with KERV.ai and Proximic by Comscore to analyze the content of videos to place relevant ads.
- The system enables precise ad placement - for example, an automotive advertiser can target driving scenes while avoiding accident content, or a mortgage company can reach house hunters while steering clear of foreclosure coverage.
- The technology's effectiveness relies heavily on seamless ad delivery—an area where FreeWheel's research shows that technical issues like latency and poor ad placement can hurt viewer experience and brand perception.
How it works: KERV’s neural networks recognize sensitive visual and auditory content.
- That info is then mapped to IAB’s content taxonomies, brand safety taxonomies developed by GARM, as well as custom visual taxonomies.
- KERV then classifies the content by brand safety and suitability, allowing it to distinguish the cooking use of a knife on “Top Chef” versus a crime use in “Law & Order.” It also treats different types of advertisers (say, a spirits brand versus a toy company) differently.
- KERV’s video analysis can analyze both VOD and live content in actual real-time (within the curse delay) and adjust the ad placement for the very next pod, so if breaking news interrupts previously scheduled programming, KERV’s tech can swap advertisers ahead of the very next commercial break.
Why it matters: The timing is particularly significant given increasing privacy regulations and the decline of traditional tracking methods. Thirty-five percent of B2C marketers are turning to contextual advertising to replace third-party cookie approaches.
Zooming out: The push for better contextual targeting is gaining momentum across the industry, with Gracenote launching additional contextual categories to enable more precise ad placement.
Our take: While contextual targeting offers significant advantages, it works best as part of a comprehensive targeting strategy. Combining contextual signals with privacy-compliant deterministic data helps satisfy both consumer privacy preferences and advertiser performance demands. This layered strategy can substantially improve campaign efficiency.