Owing to the inclination towards e-Commerce, the importance of consumer reviews has evolved significantly. Potential consumers exhibit sincere intents in seeking opinions of other consumers who have already had a usage experience of the products they are intending to make a purchase decision on. The underlying businesses also deem it fit to ascertain common public opinions regarding the quality of their products as well as services. However, the consumer reviews have bulked over time to such an extent that it has become a highly challenging task to read all the reviews, even if limiting to only the top ones, to reach an informed purchase decision or have an insight regarding how satisfied or not the consumers of a particular product are. Since most of the reviews are either unstructuctured or semi-structured, information classification is employed to derive knowledge from the reviews. However, most classification methods based on sentiment orientation of reviews do not detect which features of a product were specifically liked or disliked by a reviewer. This constitutes itself into another problem since most consumers are on the lookout for certain prerequisite features while viewing the products. The paper proposes a Consumer Satisfaction Rating System (CSRS) based on sentiment analysis of consumer reviews in context of the features of a product. The system aims at providing a summary that represents the extent to which the consumers were satisfied or unsatisfied with the specific features of a product.