Role of Online Product Reviews and Text Mining in Development of New Generation Products

In the era of Big Data, with the advances in e-commerce, users, rather than producers, tend to pioneer to express to-be-improved product features with online product reviews. Although there are many conventional methods for determining users' opinions about available products, these methods are costly, non-voluntary, applied with a limited group, and have the risk of including much bias. Reviewing user-generated product reviews has distinct advantages over traditional methods. On the other hand, extracting high-value data from online user reviews is challenging than interviews and market research. We introduce a framework that helps extract useful data from online customer feedback using accessible and handy tools to create pattern models in terms of clarification, comparability, and validity. This article provides a business case which allows the decision-makers to recognize the summarized and visualized review trends and their potential triggers that could be considered for future product decisions.