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In order to remain competitive, modern businesses must keep informed about consumers' opinions via web-based reviews or similar channels. Today, the usefulness factor in opinion mining is mainly achieved through helpful user ratings in reviews. Reviews belong to different categories and each category contains different types of information that have not yet been the focus of sentiment analysis research so far. There is useful content in each type of review that may be helpful to users as well as designers. Therefore, it is essential to classify reviews into multiple types and then share relevant information with people involved in the development of business products and services. We hereby propose a review analysis framework, which may help designers and customers to extract useful information from user-generated contents. The proposed framework aims to enable users, designers and potential buyers to enhance decision making strategies and, hence, and improve business intelligence.

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