Thick data and Big Data are two forms of data in which marketers obtain the valuable data related to their customer. Anthropologists and Ethnographers are responsible for generating the thick data by observing the human behavior and its motivations. Big Data, on the other hand, is generated by the companies who interact with their customers using millions of touch points on their handheld smart devices till both of the ‘big’ and ‘thick’ data have been promoted and used by different types of people. And this is where the issue come up because by combining the two approaches many problems of each category can be solved which is not possible to solve by relying on the data solely from one category.
Contrasting ‘Big Data’ and ‘Thick Data’ at the low level
The strength of thick data lies in establishing the hypothesis about why people behave in a certain way. It can only answer why and certainly cannot answer how much whereas on the contrary Big Data can quantify the human behavior but cannot establish grounds for the motivation of the behavior which is, it cannot answer why.
Solution: Merge the two
The real solutions to the real time problems are possible by combining these two forms of data. As companies start combining these two forms of data they are slowly stopping to rely on customer insight programs such as focus groups and customer survey which used to focus on customer aims and attitude but in reality added very little to strategies.
In order to gather information companies mostly plays by the rules of the traditional playbooks where they engage thousands of customers into hundreds of question ranging from shopping decisions to price sensitivity and from importance of brands to importance of various occasions and festivals.
Such surveys didn’t reveal about much as price is really important as matters most but in the end many of them answers that they prefer quality even if costs them little high. So, if price matters most the customer then why they would spend more on some product when alternate is available at lower costs and this is how companies became even more confused than they were before the survey.
But such things cannot be concluded from the surveys because people in general are not loyal to any brand and your survey may hold the truth but only for the day when you conducted it because next day the same customer may choose to opt for the higher price product or may even pick the lower price product as well if, it better suits the needs of the customer. And if the customer is shopping for after office hours the last thing he would be preferred to do is to go to different supermarkets and compare the prices and discounts. So, the survey that stated that money matter and the quality is preferred over money no longer holds true and all the efforts of the survey were washed away just like that.
Drawing the insights in nutshell
As such, all the findings and conclusion about the price v/s quality things only turn out to be superficial. People are no longer simply be persuaded by the discounts and brands. It largely depends on the mood of the consumer that what he decides to buy and from where he decides to buy.
Therefore, in order to meet the consumers’ need one needs to provide an experience which is not only convenient but distinct as well, in other words: Mood.
Related: Are companies really getting the Big Data
So, the success of the company is no longer driven by money, quality and discounts but is highly driven by the consumer’s mood. Hence, apart from focusing on the prices and quality, one needs to focus largely on providing the distinct shopping experience and this how much-‘BIG DATA‘ needs to be combined with the why-‘THICK DATA‘ for providing more distinct experience.