The big marketing hype about Big Data is slowly coming to a standstill. What comes after this buzzword? Small Data? Brain Data? The latest findings assume that the solution lies in a cleverly applied mix of all three tools. The platform Cleanroomfuture.com – consisting of the three pillars network, campus and magazine – contributes to this. It produces and networks swarm knowledge, makes you fit for the future and contributes to the well-being of the whole world of cleanroom technology. Frank Duvernell, one of the first cleanroom entrepreneurs, initiator of the platform and CEO of Cleanroomfuture.com since January 2019, brings more than 34 years of specialist knowledge to the table. All members are invited to contribute their knowledge as early adopters or to use the knowledge of other members and experience how it grows.
Big Data – learning from the masses
“Xing is dead. Facebook anyway. Only LinkedIn is still alive.” These sentences have been falling in circles of experts for some time now. But if you look at the pure numbers, there is no death. In German-speaking countries, Xing has around twelve million subscribers, LinkedIn ten million. Worldwide it is used by more than 500 million users in more than 200 countries. And if Facebook were really dead, we would all have noticed that.
What unites these networks is the constant production – and thus also the possibility of analysis – of enormous amounts of data. A dream for every marketer or salesman. “Big Data” promised, among other things, the tapping of gigantic masses of data from which customer wishes, needs and behaviour can be extracted. The buzzword does not automatically have to be linked negatively to “1984” or “Big Brother”. Big Data Analytics is used for the benefit of the general public, e.g. in road traffic, by helping to avoid traffic jams. Sensors monitor the traffic volume, traffic jam detectors react in real time, alternative routes are created and sent directly to a navigation device.
Big Data is an excellent answer in this and other applications for the big who, what, how much and where. However, one important component of data evaluation is missing: the plausible explanation of why. When counting, measuring and weighing, the human factor – the emotional and motivational context – remains abstract and intangible. This is where the significance of small data begins.
Small Data – learning in detail for advanced learners
Martin Lindstrom, Danish bestselling author and internationally leading marketing expert, who founded his first advertising agency at the age of 14 and now advises companies such as Nestlé, LEGO and Mercedes-Benz, investigated the phenomenon in “Small Data: What customers really want – how to draw ingenious conclusions from tiny clues”. He created the U-Turn for LEGO, for example. How? With “ethnographic” visits to the target group.
LEGO was in crisis at the beginning of 2003. The games manufacturer’s marketing department was confronted with a sobering Big Data analysis. The analysis predicted that the generations of children born in 2000 and later would be so used to immediate virtual satisfaction of needs through the excessive use of modern media that no real plastic brick would stand a chance. The digital natives would also lose their creativity and joy of playing. In short: Big Data said that children would no longer be concerned with the small tokens.
As a result, it was planned to increase the size of the tokens and reduce the product range. Until Lindstrom contributed his small data knowledge. He drew it from his ethnographic visit to the nursery of a 12-year-old. The boy was an avowed LEGO and skateboard fan. When asked about his most valuable possession, he showed a pair of old sneakers sanded off from the halfpipe. He enthusiastically told about the different tricks he had practiced until they were perfect. These sneakers were his trophy. Weared out in the right places on the soles, they ennobled him in his peer group and proved that he was one of the best skateboarders in his city. Lindstrom concluded: Today’s children are just as capable of staying focused on one thing for a long time as the generations before them. Only – it must really interest them.
He recommended that LEGO pay more attention to the target group’s interests and integrate them into its product range. The company successfully implemented his advice, collaborated with other relevant brands from the children’s world such as Star Wars and Bob the Builder, offered extensive sets with numerous components and maintained the (small) size of its bricks.
As accurate as Big Data can be in correlating and linking millions of records, she is unable to predict how people will really behave.