The Automation Imperative in the Age of Programmatic
Programmatic advertising offered the promise of having systems of processes govern media buying, to ultimately allow for time and resource efficiencies. This would naturally increase innovation in a growing industry and give way for more opportunity.
The goal was advanced automation. Or, in simpler terms, to make programmatic advertising … well … more programmatic.
According to a recent report from CtrlShift, 28.5% of traders surveyed said they completed 80% of their reports manually. However, the lack of automation in the day-to-day lives of programmatic traders goes beyond just building reports. Increasingly, their time is spent on mundane and arduous tasks, when time could otherwise be spent on campaign performance, and more strategic endeavors. Finding ways to remove manual workflows should be the focus for every programmatic advertiser.
It’s a common trend that programmatic traders operate five or more platforms regularly, and are tasked with setting up highly complex campaigns across multiple regions for multiple advertisers.
But, as programmatic advertising has matured, many traders are still operating with older and more manual workflow systems. Increasing efficiency and reducing manual work through automation will soon be one of the most significant attributes of client retention. The phrase “work smarter, not harder” may be overused, but automation has made it more applicable than ever in the digital advertising space.
Certain mundane tasks — bulk uploading creative tags, report building, all of the duplicative operations work — take up valuable hours that could be spent optimizing campaigns and increasing performance for efficiencies that help maintain, grow, and innovate business priorities.
Automation Is Designed for Focused Tasks
The topic of automation inevitably starts a conversation about the risks of job loss. But automation is often a one-trick pony. It is only capable of (and designed to) handle repetitive, monotonous tasks, which means it does require human intervention.
Traders, for example, can automate their ad buying based on a certain set of rules. But that’s sometimes at the sacrifice of scale, price, viewability, or other factors.
If all advertisers care about is 70% viewability, but they’re not willing to bid over $10, the trader has to address this and make the case to the advertisers about changing the bid ceiling. The advent of machine learning, and subsets of artificial intelligence, are helping us “automate” more efficiently, but human intuition and intervention is almost always the key driver of success.
Spend Less Time on Operational Requirements
The raw setup that goes into the launch of any campaign requires a programmatic trader to set explicit budgets, per the requirements of the advertiser. For example, there may be explicit budgets per region the campaign is targeting, that calls for 1,000-plus Ad Orders (line items). These need their own creative, and each has a specific budget and targeting considerations. This kind of raw setup and duplicative work is a perfect use case for automation to reduce time spent on tedious tasks, assuming the right partner and system is being used.
When advertisers want a campaign to run with certain constraints (say, targeting Millennial women on their iPhones in New Jersey who own a red Mercedes) all of these individual conditions are often manually entered.
Programmatic traders need to be spending more hours of the day focusing on making a campaign meet the needs of the advertiser. How is this being automated? Bulk editing/upload, and advanced audience classifications are leading features that are helping traders do more with less.
Traders are tasked with both scaling and making their campaigns perform at thresholds not seen before, even given counter-productive targeting environments. Consider an example in which an e-commerce advertiser requests impression fulfillment of men ages 35 to 45 with at least 70% of the ads being in view. But, what the client is really measuring is ROAS (unbeknownst to anyone). What do you think a trader will focus on? You guessed it: in-demo viewability, which may or may not have a correlation to the bottom line. This is an all-too-common trend, where real performance is not being tracked and optimized in the system that controls media effectiveness.
It’s our collective job as marketers, traders, and technologists to focus on the outcomes that matter, and give proper direction that will allow traders to make the most of the marketing dollars they’ve been entrusted with. Start with performance outcomes that matter first, and meaningful ways to automate optimization via bid overrides, machine learning, or other means will follow.
Automation in digital advertising is not about pushing a button to “set it and forget it.” It does have to be a mix of human and machine.
It’s one thing to trust a system with good models, but it’s another to just let the machine do all of the work. Gone are the days of black box algorithms that optimize toward vanity metrics.
We’re sitting at a time in advertising technology where traders not only need automation, bulk functionality, and transparency; but they need the means to override, and redirect their time and attention to factors automation can’t yet address — context, strategy, and finite control over details that can make or break a successful campaign.