The emergence of Big Data has allowed for a number of astonishing breakthroughs, both in the business world and further afield in humanitarian causes. Analysing behavioural patterns is no longer a difficult task for those who have the means, and whilst the public may not be completely satisfied with their data being used to aid the profitability of major corporations, data collection has made many things much easier.
Big Data is all about giving companies a platform to predict, a task that it's very good at in the main. But what happens when we want to know exactly why something happened?
The main issue is that Big Data analysts can become number obsessed, they look at graphs and reams of numbers to decipher what their customers might want, without really factoring in how important it is to look at everything in terms of human emotion. Often, this means that they lose the ability to understand how their customers actually interact with their products and brands.
Thick data is a relatively new concept, but one which promises to have a substantial impact on the effectiveness of Big Data. It allows companies to research deeper into the day to day lifestyle choices of its consumers through the implementation of a number of primary and secondary research methods, including, questionnaires, focus groups and customer interviews.
In essence, it's about adding a personal touch to Big Data by supplementing it with qualitative insights that help put meaning to the numbers. The best case example of this was seen with Samsung. The Japanese technology giant wanted to answer the question 'What does the TV mean in the modern household?' as they felt that the design of their televisions was causing their sales to dip.
By conducting hours of research it was discovered that most people see the TV as a piece of furniture, not electronics. With this in mind, they redesigned their TVs to be more in line with what a piece of furniture should actually constitute.
Therefore, by looking at 'thick data', that is the market research they carried out, they were able to put a 'why' to the data. The use of thick data gave them an accurate reason by which to plan their new market strategy and meant that they were able to make real improvement to their profitability, when solely quantitative data might have let them down.