Five years ago marketers talked about chameleon consumers who were eclectic in their choices and therefore difficult to segment or to predict for market researchers and marketing managers. Today however we leave traces, willy-nilly, like a kind of consumer snail, through the choices and searches we do online or on a mobile device. In a previous post on cloaking I already indicated how Millennials increasingly react to this by hiding more and more; nonetheless companies still find an abundance of useful information to predict you as a consumer.
About 80% of the information gathered about a person by the CIA is simply available online, so software increasingly replaces secret agents. Nate Silver perfectly predicted the results of the most recent American presidential election for 50 states. Internet TV station Netflix created its own series House of Cards, based on a detailed analysis of the big data they gather about subscription preferences. The series became a big success which was predictable for 90%.
None of the Taco Bell launches in the past 5 years has failed, because the company has developed an algorithm which can estimate whether a given product can make it or not. The algorithm obtains data from till registrations (whether something sells well or not) but also from what is shared about the products on social media. Because you may buy a product but not like it. The result of the algorithm gives the go or the no-go for every new product idea. In the meantime, Twitter does not only influence the stock market; if you analyze the right tweets it can also predict it.
In this age of algorithms companies will shift from a production for the average customer to tailor-made solutions for the individual client. Wonga.com, a newcomer among British credit institutions since 2007, grants loans to its customers based on the solvency of their Facebook friends. This is how they can grant credits quicker and entirely online. The company obtains a 97% satisfaction score among customers and scores best in its market.
What one shares on Facebook reveals more about your character and positive and negative characteristics than any personality test. IBM researcher Michelle Zhou can determine your personality by analyzing 200 of your tweets. The Weather Channel can predict consumer behavior and determine which products had better be sold on which days. Even colleges now use big data to predict whether students will perform better or not.
The increased use of big consumer data and its clear usage for approaching consumers does have some disadvantages, however. As already mentioned in previous blogposts, Millennials are more and more concerned about their privacy. And right they are. Forbes already described before how the US retailer Target gave a pregnancy score to every female client, based on their purchases of given product categories, and could therefore almost predict whether a woman was pregnant and which stage of the pregnancy they were in. At a given point the Minneapolis branch was visited by an angry father of a teenage daughter who suddenly started receiving mails for baby clothing. Turned out that Target had predicted the daughter’s pregnancy before she had told her father. Since then, Target has applied the coupon program for pregnant women, by also adding coupons for products which are highly unlikely to be purchased by a pregnant woman. This is how the retailer avoids the mailings to seem too intrusive to its customers.
In the end, nothing is as boring as being predictable and being predicted. I get many reading suggestions from Amazon.com, which may be useful, but Millennials (in particular), known as stimulation junkies, want to really be surprised or experience something unusual. Which is how one trend leads to reactions, leading in their turn to new trends.
Discover 4 other consumer trends in our 5 Paradoxical Consumer Trends paper: