Social Media Analytics Based Product Improvement Framework
Chuan‐Jun Su, Yinan Chen · 2016
In the traditional world, marketing studies managed to employ various techniques to explore customers' consensual experiences toward products with limited information available. The uses of surveys, focus groups or regular individual interviews are some of the frequently used methods by marketers. We are now entering in the era of Big Data. The explosion and profusion of the unprecedented scale of heterogeneous data available in this new era allow us to acquire further insights and knowledge about the market for improving the quality of products. In this paper, we present a Social Media-based Product Improvement Framework (SM-PIF) which is capable of deriving recommendations for product improvement and subsequently increase the product's market competitiveness. The recommendation generated by the SM-PIF is expected to be more accurate and less biased than traditional methods due to its "Big Data" nature.