Automation is ushering in a new age of digital advertising. In an industry so closely tied to human condition, known for creative that taps into emotion, it may seem counterintuitive to hand over critical processes to software and algorithms, but automated workflows have helped streamline advertising processes. Perhaps the most immediate application for the technology in this space is ad buying—and with the growing sophistication of artificial intelligence, these workflows stand to become more efficient and effective than ever before.
Programmatic ad buying on the rise
The concept of automated ad buying isn't new—organizations have been using programmatic ad buying strategies for the better part of a decade to streamline and optimize the purchase process while eliminating bottlenecks.
As eMarketer explained, there are two main types of programmatic advertising: real-time bidding (RTB) and programmatic direct. RTB is essentially an auction, either open to the public or held privately, where parties can bid against each other for ad placement. Programmatic direct, meanwhile, adheres more closely to traditional sales processes. There is no auction and prices and inventory can be negotiated between an advertiser and sales representative.
"AI can improve programmatic advertising software's critical decision-making capabilities."
It's easy to see why programmatic buying is only growing; automated workflows can achieve a level of efficiency and speed that are simply unattainable by an individual carrying out manual processes. As long as advertisers have faith in their ad buying software to make the best decision possible, they can both streamline ad placement and ensure they're getting value out of their budget.
But you already know all that—so what's new? Artificial intelligence can take these strategies to the next level by improving software's critical decision-making capabilities.
Making a smarter ad buyer with AI
As the advertising environment becomes more complex, with a greater need to account for both traditional mediums and newer platforms, advertisers must be able to determine the best way to allocate available spend.
A programmatic advertising tool that continually makes poor decisions about which ads to buy, who to target and where to place them will not help, even if it's streamlining those processes. AI works to make these solutions smarter, leveraging available data to get a better understanding of who your target audience should be and the best way to reach them.
Proponents of AI-driven programmatic ad buying point to Facebook and Google as shining examples of how effective these processes can be when done right. Another example to look to is IBM and its use of the Watson platform to improve ad placement decision-making.
At the recent Association of National Advertisers' 2017 Masters of B2B Marketing conference, IBM's Jon Iwata discussed the progress the company has made by applying AI to programmatic advertising.
"We had Watson analyze all of our bids, all of the data, and all of the outcomes," Iwata stated. "We achieved a 25 percent improvement in effectiveness by applying Watson to programmatic."
Looking to the future of AI-driven capabilities
As AI solutions grow more sophisticated, advertisers will see better ad performance, more efficient spending and better data about their audience.
Organizations that want to stay ahead of the curve should begin augmenting their programmatic practices with artificial intelligence. Wading into an emerging field like AI may seem seem challenging, but it's a necessity to stay competitive.
Clarity Insights has unparalleled expertise in AI and machine learning—contact our team today to learn more about our work in the advertising industry.