Council Post: Can Advertisers Balance Scale And Quality?
Can Advertisers Balance Scale And Quality?
Founder and CEO of Taykey, a real-time audience data company.
In the wake of several high-profile cases of large advertisers appearing next to terrorist videos, the issues of inventory quality and safety are once again top of mind for the advertising industry. We’re seeing a renewed flight to manually vetted solutions such as private ad exchanges, predefined publisher whitelists and traditional direct media deals where marketers run exclusively on hand-selected publishers.
Unfortunately, advertisers also pay the price in the form of reduced scale, efficiency, and the ability to reach and engage their consumers most effectively. While the appeal of these manual approaches is understandable, their trade-offs are often unnecessary based on the advertiser’s objectives. Increasingly, whitelisting and private exchanges are being used as a crutch for bad data and inaccurate targeting rather than a proactive strategy.
The primary challenge is consumer behavior itself. More than 30% of web traffic is driven by social media. Millennials check their phones more than 150 times per day, jumping from social platforms to articles to videos. Most of this phone time is “life in the feed,” where discovery reigns supreme and social conversation is driving consumption. As a result, the new prime time looks less like "M*A*S*H*" and more like Joseph Garrett (aka Stampy), who makes humorous Minecraft videos in his basement in the U.K. and has amassed more than 8.4 million global followers.
But that isn’t typically how content targeting is approached when humans take the wheel. It’s driven by broad category-level approaches and the gut instinct of the buyer rather than real-time consumer insight. Still, every advertiser has a right not to run next to ISIS videos. But most things aren’t ISIS. They’re Bill O’Reilly, Kendall Jenner and PewDiePie -- safe territory that has suddenly become toxic -- and manual targeting approaches will leave you chasing your tail here, too.
Luckily, with the right tools, the massive and growing volume of conversation data across social platforms and websites can be mined via natural language processing (NLP) to tell advertisers exactly what content consumers do care about in the moment, repeatedly and at massive scale. Speaking of Kendall Jenner and Bill O'Reilly, the same NLP technology would have automatically flagged these topics as controversial (based on sentiment detection) and instructed automated buying systems to avoid them as soon as the controversies erupted. The right tech can actually turn the challenge of consumer fragmentation into an opportunity, by leveraging the growing volume of social conversation to map consumer interests and align targeting accordingly.
In fact, we recently developed a product offering that connects NLP directly to real-time media buying decisions. We've seen this capability become increasingly valuable as audience attention continues to become more dynamic and unpredictable. For example, a men's magazine recently did an exclusive interview with Brad Pitt that went viral with women 25-49. Even though advertisers were not initially aligned with the content, the system used context and conversation patterns to understand the who, what, and why and shift media dollars in real time.
Accurate real-time alignment with relevant topics can be an effective way to proactively address both quality and safety concerns without locking down scale and flexibility. After all, do we believe that soccer moms were consuming ISIS videos, or were those consumer-packaged-goods ads just poorly targeted in the first place? If soccer moms were talking about these videos, it’s highly likely that the sentiment wouldn’t be positive.
That said, automatic blacklisting of problematic keywords and categories (e.g., terrorism) is a sensible safety layer that's worthy of investment. But completely reverting back to manual buying techniques does more than hurt scale and efficiency. It runs counter to the realities of consumer content consumption and will eventually leave marketers unable to achieve prime-time level scale and engagement online.