Add these concerns to the existing dread surrounding fraud and transparency, and there’s a clear crisis brewing in the world of programmatic media.
A recent study by BrightRoll found that 96% of advertisers are concerned about their ads appearing beside fake news when they buy media programmatically. Traditional media channels like cable TV are also affected, as advertisers pull out of broadcast programs, such as Sean Hannity’s show, over the propagation of already-debunked conspiracy theories. Now more than ever, advertisers have the responsibility not only to avoid suspicious traffic, but also to target publishers, online and otherwise, with high quality content.
Programmatic is slightly more difficult to manage than traditional media. Buying a spot during Hannity’s show requires the media buyer to know the content, and seek it out on behalf of the advertiser. Pulling a :30 spot may take just one phone call followed by an email. The protocol might not be easily executed, but the actions required are understood and clear.
In programmatic, where audience has taken on a much larger emphasis than content, effectively avoiding fake news requires a more detailed and coordinated strategy.
White and black lists are often the first solutions advertisers turn to when they have brand safety concerns, but these are only a first line of defense in a war that requires a multi-pronged strategy.
Blacklists can help advertisers avoid really obvious land mines — they may not want to appear on dating sites or apps, for instance, and it’s relatively easy to avoid sites with illegal content. Other marketers, like wine and spirits brands, need to emphasize publishers where the majority of users are over 21 years old.
The larger question is how to avoid running ads adjacent to content that could be interpreted negatively, by both the consumer public and the advertiser themselves.
As we’re seeing, fake news is not simply confined to less-desirable sites. This phrase is now popping up everywhere, and the accusation is even applied to traditionally trusted sources. It’s no longer just an issue of avoiding gossip and rumor mill forums, so taking additional steps is now an absolute necessity for concerned marketers.
One of the next techniques brands and their agencies can turn to is keyword targeting. This strategy goes both ways: Brands can either prioritize positive results (the content they know they want) or avoid negative results (the fake news and other content they know they want to avoid).
Some may ask, if humans are confused by fake news, how can machines discern the difference? The truth is, machines actually have an advantage. They can consume (or crawl, in their case) more content than any single human could in a lifetime.
This means technology can more thoroughly spot potential word groupings associated with fake news. It can also rely on standards provided by the Interactive Advertising Bureau to scan a page and website, and determine that source’s legitimacy. If the site or app has previously been classified, it’s far easier to tell if it will provide a positive or negative brand experience. This is the same way human readers can tell if they want to return to a website after reading one article.
Like other issues facing the digital ad community, fake news will continue to evolve. If advertisers want to avoid having ads seen alongside potentially unsafe or seemingly inappropriate content, they need to take advanced steps. By actively monitoring contextual data and leveraging keyword-based targeting and machine learning, brands can keep themselves safer.
This post originally appeared on MediaPost.