Big Data Driven Marketing: Boon or Bane for Customers?

There has been a lot of talk recently about what big data could mean for marketing, and analysts have observed that next-generation marketers need to be able to evaluate data accurately and consistently so that their business can target customers as directly as possible. However, it is important to avoid treating customers, in the words of Gunnar Sohn, like “mindless clicking machines.”

There is certainly something in that. Far too many companies spam existing and potential customers with ads that are more or less irrelevant instead of providing them with content they need or want and initiating a meaningful dialogue with them. But if we’re being honest, the lines are blurred here – when is content useful and when is it spam? Am I a mindless clicking machine if Amazon suggests products to me on the basis of my previous purchases or clicks, or is that just good service?

Whatever the case, Amazon is generating 30 percent more turnover than it did in the past thanks to personalized recommendations. There’s no doubt that I’m annoyed by the countless unsolicited email advertisements I receive. However, it is also clear that creating content that is informative, entertaining and genuine is much more challenging, much more resource intensive and therefore much more expensive. If “money talks” and the end of the next quarter is approaching, this is not likely to be a top priority.

Use a Scalpel Instead of a Sledgehammer

My colleague Marie Wallace summed it up nicely a little while ago when she said: “C’mon guys, let’s get serious about privacy!” Marie, an exceptional thinker in the field of analytics, called on us to finally take data protection and the private sphere seriously. She correctly noted that totally anonymizing data was just as counterproductive as complete disclosure, and that a scalpel, not a sledgehammer, was the tool required for data protection.

The name of the game has to be transparency, and businesses have to be open about what they do with user’s information in order to win their trust. To return to the Watson example above, patients are more likely to volunteer their medical information if they know it could help to provide better treatment to other patients in the future. However, there are also plenty of other scenarios where customers would definitely not want their information to be analyzed and evaluated.

Learning Opportunities

It is also clear that analytics is here to stay. Predictive analytics in particular offers enormous potential for good, and we must do all we can to harness that, especially here in Germany where we have a tendency to see the negative side of things first. Marie calls on developers to make data privacy their top priority when designing analytics solutions, even if this makes projects far more complex. I wholeheartedly agree with her and would like to see what she has devised for data scientists and IT architects working in marketing.

We marketers need to make protecting customer data our number one priority. Data protection is not just about safeguarding our customers’ privacy. Above all, it is about respecting our customers and people in general. 

Title image by Balefire (Shutterstock)

Editor's Note: Read more from Stefan in Do Employees Need Rewards to be Active on Social Media?