Marketers gain a great deal of flexibility by activating data faster to make better creative decisions, but creative has become an afterthought to both brands and technology vendors, especially compared to other aspects of programmatic optimization. In an industry where performance is seen as the most important part of a campaign, marketers can no longer afford to ignore creative. It’s time to explore how to use data to deliver a greater impact through creative.
Creative tools already exist to build dynamic ads, but the problem is that very few of those tools are built alongside a media trading operation with a direct tie to a programmatic engine. A programmatic engine relies on data to improve targeting efficiency. Without ties to a programmatic engine, brands may be reaching the right consumer -- but the messaging might be irrelevant to that specific person. For instance, a consumer who recently purchased a car wouldn't be interested in seeing and ad from an automaker, but would be interested in creative that focused on service offers, tires, or accessories.
Additionally, agencies and brands select their media buying teams separately from their creative teams, resulting in each team working independently, with no strategic collaboration. Typically, ads are created by a creative agency and then handed off to media buyers who are limited in the creative optimizations that can be made from that point moving forward.
A solution to improve creative lies in the massive amount of data that programmatic provides marketers. Creative tools should access the same data that media buyers and traders use to select the appropriate channels and strategies for a campaign. Additional data can decipher which types of imagery and messages resonate with a consumer, and should be leveraged to deliver effective creative. Programmatic creative allows marketers to have success in both performance and brand impact.
A major advantage of programmatic creative is the dynamic and sequential messaging that is influenced by rich-data signals. These rich-data signals, including weather, social media data, and purchase history, are usually used to improve targeting. However, the signals can also be used to adjust creative to better fit the person viewing the ad.
For example, an ad can dynamically change based on a consumer’s past purchase data or browsing history, personalizing it for added impact. Serving an ad for a product similar to something the consumer has already researched makes it more likely to likely to attract the consumer's eye.
The goal for programmatic creative should be a successful, two-way conversation with customers through easy changes in assets that avoid lengthy approval processes and wasted budgets. Rather than continuing to isolate the buying process from the creative process, marketers should streamline the two, optimizing data for both messaging and targeting purposes.