Products and services are heavily discussed on social media, which are conventionally used by brand owners, as well as consumers, to acquire consumer opinions. State-of-the-art opinion mining systems provide summaries of positive and negative sentiments toward a service/product and its various aspects. On a closer look, it is observed that these opinions also contain suggestions, tips, and advice, which are often explicitly sought by both brand owners and consumers. This chapter presents a comprehensive overview of the task of mining suggestions from the opinionated text on social media. Various aspects of the task are discussed, which includes an analysis of suggestions appearing in reviews, the relation between sentiments and suggestions, relevant datasets, and existing methods. The problem has been identified only recently as a viable task, and there is limited availability of existing approaches and datasets.