When people think of advertising, they imagine Don Draper pitching a Lucky Strike campaign that he thought up with his creative mind. That’s partially true, but decades beyond the Mad Men era, the industry has evolved, specifically with regards to how research and data have been integrated to fuel creative direction. Advertising is no longer just an art. It’s a blend of the intuitive creativity encouraged by art and the data-informed, process-driven functionality of science.
Think of any other traditionally creative discipline outside of advertising. Film studios will use it to determine which scenes will best resonate with audiences when given a wide release. They even use this research and data to guide what kinds of movies they should invest in. Record companies use big data to help predict what genres and songs will hit it big.
Data plays a similar role in advertising, guiding the overall direction and strategy to implement advertising and media spend.
Data Science: How It Plays into Advertising
There are massive troves of data available for advertisers. The practice of data science allows them to extract actionable insights about consumer behavior, content strategies, efficiency of how their money is allocated and much more.
Kathleen Hall, Microsoft’s corporate vice president of global advertising and media, asks it best: “The conversation has evolved to what I would like it to be about, which is what is the interaction between data and creativity? How can we use data to inform the creative in a way that makes it even better and even more impactful?”
Wired has an answer for how advertisers are implementing data: “more and more [advertisers] are taking advantage of the growing opportunity to better understand, reach and engage their brands’ potential consumers and advocates.” Thus, brands and their agencies can leverage the powerful message of their creative work, whether that’s a display ad or a television commercial, and make sure it gets in front of the right audience at the right time. This strategy can “provide guidance to not only the content of the creative product, but also its form, including the optimal media channel for delivery.”
Machine Learning in Advertising
Yes, the future is here. Artificial intelligence and machine learning are guiding business decisions with predictive analysis and automation.
Machine learning uses predictive modeling and data-driven algorithms to drive the results of a given objective. In the case of advertising, Claudia Perlich, the chief scientist of Dstillery, said machine learning can be used for six objectives:
Measuring the impact of online ads and their campaigns
How one person is interacting with multiple digital devices
Predicting consumer behaviors
Predicting responses to ads based on their messaging and placement
Insights on audience behavior throughout the internet
With this kind of knowledge, creativity can be unleashed in such a precise way that the message is adapted to the right person in the right context, as opposed to a general audience maybe latching onto the message. For example, a sports apparel company targeting physically active male millennials could ensure that audience sees a product benefit message, such as how their new line of workout clothes can enhance their performance, on a mobile sports media app while a football game is taking place. This kind of pinpoint targeting ensures the right audience receives an online creative message that resonates in the most timely and relevant manner.
Data-Driven Creativity as a Strategy
Wunderman’s chief creative officer, Lincoln Bjorkman, sums up the relationship between data and creativity best, “data provides Miles Davis’ musical foundation, but musicians and creative still need to be able to improvise or innovate solutions to produce something consumers love. Done right, there’s no opposition between the two, just a smoothly functioning band of players, intent on making magic happen.” If Miles Davis used data to fuel his creativity, it’d be wise for anyone else to, as well.