Kapitel 02 / INNOVATIONSMANAGEMENT & DIGITALE VISIONEN

the next

big thing is

SMALL data

FORGET

BIG DATA –

The brand whisperer: Martin Lindstrom.

Businesses are slowly drifting away from the consumer. In- stead of being in touch with real people, executives are relying on big data. But Martin Lindstrom is convinced that they are barking up the wrong tree. One of the world’s foremost branding experts explains why big data isn’t the ideal way to really understand consumers – and how small data can completely transform the way businesses are built and run.


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n 2013, after analysing billions of bytes of data, Google thought they’d discov- ered a relationship between how people searched for flu-related topics and peo- ple’s actual flu symptoms. The discovery sent shockwaves through the US health- care sector, which had been struggling with the balance between supply and de-

mand. Once an outbreak occurred, doctors were often left without enough pharmaceuti- cal products on the shelves. Suddenly, thanks to big data, Google promised them a flu- outbreak prediction four days in advance.

But this story took a surprising turn. The truth is, as the flu epidemic spread, fear spread too. People became curious to learn more. The conclusion of the Centers for Dis- ease Control and Prevention, based on data from millions of doctors? Google’s predic- tion was a two-fold overestimate.

Google had focused on correlating data, but they neglected the whole causation as- pect. We have tonnes of data, but little information. Remember Hans Christian Ander- sen’s iconic fairytale, The Emperor’s New Clothes? Afraid of appearing incompetent or intolerably stupid, everyone said they believed that the Emperor, though actually naked, is wearing the most exquisite clothes. So what people say isn’t always what they mean.

Perhaps the answer isn’t big data alone. Maybe we need a counter-balance. Could we find major insights in small data?

Recently I had a meeting with the CEO of one of the world’s biggest consumer goods companies. He shared with me some of the key headlines from a huge consumer research study involving 17,000 consumer surveys.

Independently of the study, that afternoon we had planned to visit two random consumers. Our two ethnographic interviews were hardly representative, compared with his 17,000 surveys. But the next day, at the company’s quarterly board meeting, the CEO described what he’d learned from our two interviewees, and what the company should do to address a growing trend we’d observed. He spent zero time referring to the 17,000-consumer study.

Having worked for some of the largest brands in the world, using big data and neuroscience to obtain insights about consumers, I’ve come to realise that, as valuable as big data is, small (tiny, unusual, and sometimes seemingly irrelevant) data, if interpreted the right way, can provide insights that can revolutionise an entire company.

Fifteen years ago, Lego experienced its biggest crisis ever. Screen-based entertainment was capturing an in- creasingly bigger share of kids’ time. Big data heralded the arrival of the instant gratification generation – young- sters with a zero-attention span. This was a huge chal- lenge, since children needed many hours to build a Lego castle or spaceship. Would they have the patience to use Lego’s tiny bricks? So, Lego introduced larger building blocks, enabling kids to build the same castle in minutes rather than hours. To everyone’s surprise, Lego’s toy sales kept plummeting. What had gone wrong?

The answer could be found in the bedroom of an 11-year-old German child. We asked the kid to point out what he was most proud of. To everyone’s surprise, he picked a worn-out pair of sneakers. He explained that the sneakers’ wear-and-tear proved he was the best skateboarder in town. In learning all the cool tricks, the shoes had become real-life evidence of his skateboarding talent.

Based on this brief visit, Lego drew two conclusions that defined the future of the entire company. First, toys should fuel kids’ aim to be masters of their universe; and, sec- ond, this passion for mastery means that time (and the size of the Lego brick) is irrele- vant. Spending hundreds of hours perfecting a skateboard slide is the same as allocating hundreds of hours to building a castle. Lego’s big-data conclusions had steered them in the wrong direction, but small data gave Lego an insight no other toy company was aware of.

If you open a box of Lego today, you’ll see that the bricks are tiny again. You’ll also notice how mastery and acquiring skills is the theme of every box. Today, Lego is the world’s largest toy company.

The most ground-breaking observations I’ve made are rarely attributed to big data. Rather, it is miniscule consumer insights, gained in the homes of consumers, that time af- ter time shape truly innovative brands.

In all honesty, I’m no longer a brand guy. I consider myself a ‘forensic investigator of emotional DNA’. I search for small-data clues that the competition rarely notices – not just because the clues are so subtle, but because the competition is too busy gobbling up data, desperately searching for correlation, and usually overlooking causation.

MARTIN LINDSTROM IN A CONVERSATION WITH SABINE SIMON

Mr Lindstrom, what is small data?

Martin Lindstrom: Seemingly insignificant observations that point to one or more unmet desires. While big data is all about correlation, small data is all about causation.

It could be said that small data explains the ‘why’ behind what big data reveals?

ML: Yes, that’s right.

Can you explain how small data can deliver more valuable insights than big data?

ML: You need to have a hypothesis before beginning the search and, most impor- tantly, before drawing conclusions. Once you have a solid hypothesis you’ll be able to verify how accurate this is by the usage of small data. Small and big data are like partners in a dance.

How can small data provide the insights needed to craft a powerful brand?

ML: Because it comes close to the reality. When observing consumers in their real lives – whether in their homes, cooking, partying or shopping – it is possible to de- tect human nuances. A smell, a sound, a ritual or minor insights that may not seem important but which, when verified, can indicate a major trend.

You say that brands still rely on a segmentation process based on demographics and not on customer needs. What should brands be doing differently?

ML: They should begin by understanding the emotions that drive consumers, which desires drive us. We’re all out of balance. It might be that I feel too overweight or feel alone. We all have hundreds of unbalanced emotions: it’s the space between be- ing in and out of balance that indicates a new need, a new desire or simply a new brand or product solution.

We have tonnes of data but no information. Is small data the foundation for break- through ideas or transformative ways of turning around brands?

ML: Absolutely, we estimate that around 65% of all major brand innovations are developed from small data research.

One of your theses is: the more senses you harness, the stronger the brand you’re likely to build in the consumer’s mind. So is it all about emotion?

ML: Without a doubt. Based on our neuroscience research, we estimate that around 85% of everything we do is irrational and only 15% rational.

In the same way that a detective collects clues in order to solve a case, you say you are an observer of society and that it is influenced by digitisation. How do you use your observations from all around the world to advise different companies and brands? And can you give us a couple of examples?

ML: I typically identify needs, rarely discussed or even detected, by spending time in consumers’ homes. That, in return, forms the foundation for imbalances and de- sires which few companies have detected before. The issue is that big data can be used by everyone. And the conclusions often tend to be used by everyone. Small data allows for that little nugget of insight which few were ever aware of.

Would you say monitoring and interpretation are more important for business leaders to understand their customers than accumulating big data?

ML: Without a doubt. To build the instinct, which in principal is an accumulation of experiences made over many years. That insight should be based on working, in- teracting and observing consumers – the better we are at walking in the shoes of the consumer, the better marketers we will be.

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