The real-world is coming a-calling

happy-customer

Data derived from what customers do and feel, rather than what they say, has got a lot more interesting

Big Data scepticism appears to be alive and well in Asia. I have lost count of the number of times people say to me: “There is nothing that big data can tell you that small data can’t”.

While the reasons for this “Big Data Backlash” are still unclear to me, I can only assume that many sceptics are focused on the “Big” of Big Data. That is, the volume of data that companies struggle to store, make sense of, and then use to generate growth.

What is perhaps less obvious are the other “V”s of Big Data: its velocity and variety. The potential utility of real-time and diverse data is still unfolding but clearly, social media-derived data is just the tip of the iceberg.

Even more exciting is what is now called ‘real-world’ data, that is, data based on individual behaviour as customers or prospects interact with the world around them. There is much here that businesses can get their teeth into, especially those based in Asia.

Why so? Well, Asian consumers differ from their Western counterparts in a number of ways, as highlighted by recent studies.

For example, Asian consumers tend to be less loyal. A 2014 survey by Bain and Company found that even for top-selling brands in mainland China, up to 80% of their customers were likely to be new rather than repeats. Asian consumers also complain less, thereby masking their dissatisfaction. A 2014 IPSOS survey found that 60% of Singaporeans did not complain about the poor service they felt they had received.

These findings make it even more important for businesses in Asia to understand what makes their customers tick, while staying mindful of survey fatigue and sample biases.

Many may therefore be intrigued by such real-world inventions as video software capable of detecting facial expressions and corresponding emotions. This technology analyses in real time whether individuals are happy, annoyed, confused, surprised or frustrated. When then assessed against other operational factors, such as the waiting time at a bank branch, or the service at a restaurant, this data becomes a powerful customer experience tool.

So how reliable is emotion detection software, I hear you ask? The idea is that humans betray their emotions through “microexpressions”, that is, tiny facial movements such that people are often not even aware that they have displayed an emotion. Based on machine learning of trillions of data points and billions of emotional reactions, this software is apparently customizable for different cultures and settings.

Furthermore, with emotion detection video devices and analytics recently marketed for just US$100 per device per month, this technology has become startlingly affordable for many smaller companies. Meanwhile, those serving large numbers of customers, such as airlines, shopping malls and train stations, may find the software’s ability to track across multiple faces a particular asset. Not forgetting, of course, that video cameras are an already omni-present (and generally accepted) part of daily life.

Of course, sentiment data is just one piece of the puzzle. The other pieces remain: Which customers are unhappy and why? How can businesses use positive emotion to encourage brand loyalty and advocacy? What can businesses do to improve the customer experience?

These questions can only be answered by accessing even more customer data, and then fitting all the pieces together. So whether the sceptics like it or not, there is in fact a lot that big data can tell them, that small data can’t.

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