Using of Social Media Data Analytics for Applying Digital Twins in Product Development

Product development as an iterative combination of different disciplines like design, process planning, engineering, manufacturing, logistics, marketing and sales is a challenging issue. Researchers have argued that high product mortality rate, is not only down to factors related with the design of a certain product, but also the fact that consumer engagement and customer behavior are decisive in the product development stages. Dealing with consumers is a big challenge due to the enormous variety of feedback data and qualitative aspects of them. Mostly, the communication channels with consumers are through Social Media (SM) which are usually unstructured and hard to be analyzed. This research has investigated the importance and influence of the emotional behavior of users in accepting new products through a social media analytical approach. The paper has developed a framework to relate the user emotions and new product feature development plan through SM platforms such as Twitter. It is discovered that emotions can be considered as one the important elements for identifying the subjective nature of product attributes. The paper shows that diverse emotions and their role in New Product Development (NPD) processes, specifically in prelaunch phase. A case study has been designed to show the capabilities of the proposed framework in this research. The pre-launch and post-launch emotion Comparisons indicate the possibility of shifting users’ behavioral focus for the new product while considering the required market indicators.