Michael Calleia is the Senior Director of Marketing at Voltari, a company that develops predictive analytical solutions for the mobile space. Voltari optimizes mobile advertising campaigns from the start, learns and improves automatically in real-time, and provides insights. Michael comes to Voltari with a background that encompasses advertising, publishing, branding and marketing on both the agency and client sides.
Modern ad technology, data science and artificial intelligence allow us to constantly improve targeting and optimization. However, it’s fascinating how rarely, even in this age of data science, we use our analytic prowess to inform and optimize the creative we serve.
We know that creative factors into performance, And we know that we cannot expect automated systems alone to correct and achieve what should be our top priorities: fostering engagement and eliminating waste. But we are missing clear methods and strategies for using data to make our creative better—more personalized, relevant and effective.
After all, creative is at the very core of how consumers perceive personalization—it’s what engages us, or falls flat, based on strength and appropriateness of images, copy and interactivity. Well-made ads served thoughtlessly to the wrong person and poorly crafted ads served to the right person result in the same things: lack of engagement and waste.
A Paradigm Shift in How We Think about Technology and Creative
For many years, buyers have relied on media research to plan campaigns based simply on how sites indexed for demographic targets—in effect relying only on publisher centric targeting, resulting in broadly defined targeting and static segments. Within this process, the creative would follow suit targeting messaging to a similarly broad audience segment defined in the creative brief. And, all the pressure remained on the placement.
Fortunately, there has been a paradigm shift. Today we are able to plan and buy media in an individual-centric way—which also benefits the creative. Because we are able to move beyond broad demographic buckets and inadequate segmentation into advanced audience models that leverage massive amounts of, we can now approach media and creative in an individualized manner. Creative teams can now tune message, call to action and visuals to more meaningful audience, and in turn insights based on audience engagement with the creative arms Strategists and Creatives with much more knowledge about the consumer.
Let’s look at a couple examples. We had an Entertainment client in the theatrical category that experienced the “opportunity” of audience discovery. Through audience-centric programmatic buying, they discovered their audience was not as monolithic as first thought. For starters, while the original target was 100%, males, it turned out that a little over 50% of those engaging were female. The campaign performed well, and theater exit polls matched our targeting. But this learning was considered not much more than an ah-ha moment, and they didn’t take advantage of the opportunity to make changes. Imagine if they had been willing to optimize a second set of creative for a female audience. They absolutely could have pushed CTR or engagement even higher. For some clients, it may pay to refocus their creative to more strongly address the originally intended audience; the data does not replace good creative, but rather can help guide good creative to become great creative.
During another campaign for a large retailer, we ran nearly identical creative twice for the client. They changed only the call to action and the CTR plummeted, while all else remained the same. With all aware that the call to action went from clear to vague—the client absolutely understood the cause. Moving forward, there was an increased focus on highly precise calls to action within the creative. This reinforces the fact that great science does not replace great creative.
However, even as marketers and their agencies move away from the direct plan/buy approaches and into programmatic, audience based planning and buying, many have been slow to realize and embrace the power of focused, aggressive creative optimization. But, we should be bullish with the knowledge that in the course of running an audience focused campaign, leveraging advanced audience models, a campaign that does not limit you by media placement or physical location of inventory, we are poised to discover new, additional, and potentially more productive audiences for our brands. With richer data in hand, you can now arm your creative team with a sharper picture of who they are targeting—even going so far as to create separate creative specifically for this new audience to maximize impact.
Success stories such as the above, of brands working in this manner remind us that we must be more nimble. Today’s media environment and creative tools absolutely allow for it. With such rich data available, creative course correction should become second nature, as it comes with the territory. It’s an opportunity to set an initial strategy and plan, audience model, test, and optimize your approach—iterating creative in a dynamic, tech supported environment and simply getting better and better over the course of the campaign—or from campaign to campaign. We all want that level of improved engagement and efficiency. These are our top priorities as marketers.