The reality of artificial intelligences role in media buying may be turning out very different from the dream.
Automation and AI could be used, so the theory went, for forecasting, analyzing data and ultimately improving campaign performance, so that marketers could change and reallocate budgets quickly. But despite advancements being made, AIs adoption for media buying is ending up with slightly different use cases.
The AI is there, said Jason Harrison, CEO of North America for WPPs Essence. Youre just not seeing it in the ways you would have expected.
The expectation was that AIs use for media buying otherwise known as automated decision-making would enable machines to tap data about specific audiences so as to create automated campaigns across different digital channels. And this would enable agencies to stop worrying about the minute details of media planning and buying so they could instead spend more time on strategic work and insight delivery for their clients. But so far, that hasnt been the case, as AI has led media buyers, as previously reported by Digiday, to spend added time on campaign reporting and the more difficult aspects of the job.
And AIs role in media buying hasnt been nearly as sexy as pitched: While media agencies have been able to use AI to automate campaigns (mostly for paid search advertising), it has been delivering better targeted audiences for the same amount of money as marketers previously spent and clarifying the gaps in a media plan rather than handling all the minute details.
AIs use for media buying hasnt lived up to the dream for a few reasons. For one, the effects of AIs use on media buying are generally still found in a biddable, programmatic environment where marketers have come to expect automation. And agencies, marketers and platform providers are all still testing the best ways to use AI for media buying. Without a set of standards in place, it difficult to compare marketers use of AI for media buying.
Outside of the current state of programmatic, adoption of AI isnt widespread in a systemic and systematic way across the industry, wrote William Restrepo, svp of business intelligence for Publicis Media, in an email. Different agencies and different vendors (and vendor types) are still in a trial-and-error phase determining what works and doesnt work for them.
At the same time, Facebook and Google have made advancements in the AI media buying capabilities for their platforms, making it appealing for marketers to use those platforms AI rather than continuing to build out their own.
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At least, that has been case for Orangetheory Fitness. Just slightly more than two years ago, the high-end gym chainlaunched its own AI platform, enabling the company to slice its cost per lead from $20 to $8 and end up with better leads. With those results, the chain quadrupled its media spend and focused most of those dollars on AI. But although the company once was bullish about its own AI platform, Orangetheory has since pulled the plug on it, opting instead to have its internal teams and its media agency, the Tombras Group, manage more of its media buying and planning decisions.
We were heavily relying our digital media efforts on AI two years ago, said Tammie DeGrasse-Cabrera, the global marketing director for Orangetheory Fitness. Weve shifted back and really made sure the humans on our team, [those on] our media agency, are really doing that for us. Were also using AI thats already being developed in media platforms like Facebook and Google and connecting that and marrying that to the art and science of media buying, she added.
Orangetheory Fitnesss AI journey might be a microcosm of what midlevel marketers have been experiencing when using AI for media buying. Now that Facebooks and Googles AI for media buying has become more advanced, relying on those platforms has become attractive for marketers rather than spending significant resources on building out their own. Thats especially true at this point since the promise that AI would making the job of media buying simpler has not come to fruition.
But thats not the case for larger marketers with the resources to build their own AI solution, according to media executives; they said that major marketers are still vying for custom solutions that tap AI for media buying across a variety of platforms.
We rely on automation, but we dont set it and forget it, said Doug Rozen, chief media officer for 360i, who noted that his company has made significant advancements in use of AI for media buying over the last six months although work still remains. Its the human and the robot working together almost like sometimes the automation is taking a blunt object to something thats more nuanced than just applying the overall algorithmic automation to it.
When it comes to AIs use for media buying, the complexity of whats being accomplished is at times difficult to convey to marketers. And for someone not using the platforms each day, its easy to miss the ways that AI is already changing media buying in a biddable environment. Publishers and platform providers have done a good job of externalizing the technology and interfaces to make it easy for someone to place a media buy and enter constraints, Harrison said. It becomes akin to indicating this is how much Im willing to pay; these are my bid thresholds; this is the outcome I expect; heres how much I have to spend and hitting go, he said.
Added Harrison: Behind the scenes, the work of those platforms has gotten a lot smarter; and the return, the value that advertisers get for that money, is a lot more because in theory its being targeted to the right people; its more precise and all of that is powered by AI decisioning. He said, Its not fair to [say] it hasnt gone anywhere. It has. Youre just not as explicitly seeing it.
As Luke Lambert, OMD USAs head of programmatic advertising, observed, What were really seeing is not the change in output that we were always dreaming about, that we thought AI would produce for us. He added, Instead, its taught us that theres a better way of doing things before we even give the AI a dollar to spend, which is a positive thing. Its a good thing to find process efficiencies. We just expected them to be on the other side.
Even though AIs use for media buying has not to date delivered quite what was expected, media executives are still bullish on its potential and the need for marketers to enlist it. Weve really only scratched the surface, Harrison said. The more complexity you have in the media ecosystem with the number of players, platforms and opportunities, [and] the more complexity you have in the content ecosystem, with options in the way people consume and see content, the harder it is to train machines to anticipate where the next best impression should go. He added, Thats really the challenge now to build AI that can accommodate and contemplate all of that complexity.
And despite the challenges associated with contending with all that complexity, he said, the need for AI to help media buyers manage those players, platforms and channels is clear. Humans are not going to be able to do that decision game much longer and arguably were doing it at a suboptimal way today, Harrison said. The sooner we build AI to do that job the better marketers outcomes will be.
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Dont set it and forget it: Artificial intelligences role in media buying is taking shape - Digiday
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