June 28, 2018

by Nigel Hollis

Bill Pink sent me a link to this article by Steve Olenski who suggests ways to make better use of big data in marketing. But what caught Bill’s eye and caused him to send the link was a quote that gets at the elephant in the room for big data analysis.

Olenski quotes Elea Feit, assistant professor of marketing at Drexel University, as follows,

“In the end, the analytics won’t tell you the next big creative idea. It will tell you when the next big creative idea is working.”

Now before Bill steps in to correct me, I am not sure that this statement is completely fair but there is a heck of a lot of truth to it. Big data, whatever its source, be it behavioral or social commentary, is biased to the here and now. The data reflects the world people know and experience today. Patterns in that data may reveal opportunities for optimization, better steering behaviors in favor of a specific brand, but are unlikely to reveal opportunities for disruptive growth.

Why is this a problem? Because analysis of the here and now is a recipe for incrementalism. And the more I examine the brands that grow successfully the more it confirms my belief that growth is a matter of disruptive steps changes. Brands find a way to break the status quo by doing something different from the norm and gain market share as a result. Then a new status quo develops and everyone goes back to playing their incremental games.

What is wrong with incremental improvement? Why might a lot of small gains not add up over time to significant growth? Because the competition is armed with the same tools and understanding you are. They see and aim for the same opportunities. You might seize the opportunity quicker but they will fight back. And their budgets are set up to counter the incremental gains but not a big, disruptive step change.

Sure, analysis of big data can empower and stimulate creative thinking, just as can any source of information, but ultimately sustained success in marketing comes from identifying what might be not just what is. What is found might hint at a bigger opportunity but it will likely need further nurturing and development in order to achieve its full potential. We need to find the growth opportunities not readily apparent in the existing data and that means applying human insight and creativity in order to anticipate people’s unspoken needs and desires.

But what do you think? Can analysis of big data identify big opportunities for growth?

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