20 January 2012 | Blog
A recent MediaBizBloggers.com blog post by Tom Cunniff raises the question of whether Big Data can really help us make sense of a largely unstructured world so as to be worth the cost and effort associated with plowing into reams of data in search of transformative insights. Tom takes the point of view that those who seek answers in Big Data may be short changing the value of Big Magic, his euphemism for creative ideas that are so powerful that they defy expectations as to their impact on consumers or even society. But Tom also recognizes that the power of Big Magic is elusive and unpredictable, and that even highly talented creative folks that can sometimes hit singles, doubles, and maybe even triples, may not ever hit a magical grand slam.
I agree that it is likely impossible to use Big Data to come up with a formula to generate Big Magic. However, what I really want to draw attention to is the disconnect between how creative folks perceive, misunderstand and fear Big Data relative to its potential to assist in making more effective advertising. While Big Data will not in itself help us come up with a formula for better creative, it does enable the ability to classify consumers and their detailed interactions in a manner that helps us better understand and leverage insights about specific groups or even individuals. All too often, the creative quest to get at the essence of consumer appeal results on missed opportunities to drive ad effectiveness by making campaigns more contextually relevant to specific target segments, content or even timely situations.
In direct marketing, there is general agreement that the effectiveness of campaigns depends on three key components: list, creative and offer. List refers to the various target segments associated with each particular creative and offers. It is also notable that direct marketing campaigns typically set up a matrix of control groups where portions of each target segment is exposed to each creative and each offer, which serves to better understand the relative response rates associated with each component. The relevant insights derived are then used to enhance ongoing performance of subsequent campaigns.
Fans of Big Magic may look down on direct marketing as an ugly duckling that may be okay for promotional messaging but will not likely achieve a high “buzz” factor or win major creative awards. That may be true, but there is little doubt that what direct marketing may lack in creativity, it makes up in delivering measurable outcomes and insights that help improve subsequent campaign results.
Other forms of advertising communications such as print and out-of-home campaigns also provide evidence of campaigns can adapt the creative messaging to capitalize on the context of the placement. Absolut (vodka) and BMW have effectively use such campaigns that borrow from the media placement context or geography to enhance consumer message relevance, and improve advertising effectiveness.
Yet, when it comes to TV advertising, there is still this overarching fear that focusing on anything but the power of the underlying creative idea may actually inhibit campaign results. A proof point that is sometimes offered to support this perspective is that successful campaigns are singularly focused on a powerful idea. While there is undisputable value in having a powerful underlying campaign concept, great campaigns are also said to have “legs” able to support multiple and ongoing creative execution.
So why not leverage Big Data to enlighten creative development? Data-driven insights may help identify a powerful underlying idea that may have broad target appeal, or far more likely, the data may reveal insights that can inspire various ways to express a powerful creative concept to make it more appealing and meaningful to specific consumer target segments or viewing occasions.
The next time your creative team is putting together “the next big idea”, check to see if it passes a hypothetical Big Data test. Does the concept support message differentiation based on key consumer segments? Is the big idea able to support tailoring of messages to make them more relevant based on placement or geographic context? If not, maybe it is not such a big idea after all.And if you actually have access to Big Data, or any amount of data that may be relevant to better understand your target consumers, you can begin to apply a more practical approach to your creative assessment. How does the idea stack up against specific, identified consumer segments? What can be done to make the idea more relevant to each target consumer segment, across mediums and placements? These are all questions where relevant data can help drive and refine just about any powerful campaign idea.
In the end, we will come to realize that Big Data and Big Magic are not mutually exclusive forces. Together they can be used to craft advertising that is more relevant to viewers and more effective for marketers. Big Data may not help bring on magical grand slams, but appropriately used with Big Magic, it will likely result in advertising campaigns that predictably deliver singles and doubles. And that is a game winning formula.