Social media analytics for new product development: Case of a pizza

Abstract

The paper focuses on a new way of accessing and analyzing the users' reactions to the launch of a new product. We use Twitter data as user generated content from pre and post time span of event occurrence i.e. the launch of new product. In order to extract and analyze tweets, we used two analytical tools i.e. R (Open source) and NodeXL. Further analysis has been carried using a variety of techniques based on text mining, sentiment analysis, and network analysis. The findings show the comparative view of differences in the conversational patterns in pre-launch and post-launch data for the product. These outcomes can be extremely enlightening to recognize the early users' perceptions and their collecting judgment, including emotional perspective, about the various product aspects. Businesses can improve and refine their products and produce the next generation of products. This way of using user generated content bridges user real requirements and new products-the challenge of solving failure rate.