Using Big Data in Product Design
In a Southeast Asian nation where 3 main ethnics are Malay, Chinese and Indian, one cable television operator designed ethnic viewing package based solely on demographic: Malay package for Malay families, Chinese package for Chinese families, and Indian package for Indian families. This was considered safe and avoided selling inappropriate or sensitive content to the wrong target audiences.
However, this was not necessarily true when Big Data was adopted to analyse the viewers behaviours. This was done by firstly extracting the languages watched (Small Data) from the viewing logs (Big Data). It was then discovered that some Malay or Indian families were viewing Chinese content and vice versa. At first, the management did not think that the findings were right as it was not possible to sell Chinese content to Malay or Indian families. The management suspected that the demographic data was wrong. The management speculated that it could be a family of mixed marriage where the child was learning Chinese by tuning into Chinese content, or the maid was watching or any other reasons.
The study did not know why they watched the content of in another language, but it conclusively found that they watched content in multiple languages. Based on the outcome of the study, the management decided to try cross-ethnic viewing packages and the result was a huge increase in sale and revenue.
This illustrates the use of Big Data in helping a company make decision in product design.
This case study also highlights some important shifts in Big Data, especially Shift 3:
When dealing with Big Data, we move away from age-old seach for causality - a human nature to search for causes.
Instead of looking for causes, we are satisfied with patterns and correlations in the data that provide us with unprecedented insights.
The correlations may not tell us precisely why something is happening, but they affirm that it is happening.