In an e-commerce site, reviews help augment basic product descriptions with detailed user experiences and opinions on the product. These reviews greatly influence the purchase decisions of oncoming customers. Since these reviews are haphazardly presented, they call for befitting review exploration techniques. We propose a novel view based review exploration system that can be used to control the depth and content of the retrieved reviews. We propose three views depending on the depth personified by them: the Bird-eye view, the Unidirectional view, and the Microscopic view. The views present a ranked list of relevant reviews that meet the view criteria. The proposed view based exploration recorded precision as high as 0.85. © 2021 ACM.