Today's online shopping systems enable consumers to sift through a vast amount of information by manipulating combinations of prede ned lters. These lters, such as travel dates, price range, and location, are objective attributes that lead to an indisputable set of answers. However, we show that users' search criteria are often subjective and experientially expressed. Hence, to provide consumers with an enhanced search experience, online shopping systems should directly support both subjective and objective search. I will describe how this is done in an experiential search engine that we are currently developing at Megagon Labs; by harnessing information \outside the box", in the text of online reviews or social media, views, and interpreting subjective queries.