How Zefr Uses Humans to Help YouTube's Less-Than-Perfect Targeting

It's an approach that drives clicks and conversions

When it comes to brand safety, brands might be better off relying on humans, rather than machines.

According to new research out today co-produced by L.A.-based contextual data company Zefr and the advertising analytics outfit Magna, media buyers could get better bang for their buck by including humans in their content-review process, rather than relying on preset white- or blacklists. Zefr—which patented its “human in the loop” brand-suitability algorithm that guides machine learning models using human review—found that the resulting ads turned out to be more relevant, reached consumers that were more likely to be in-market and were more likely to convert as a result.

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