In some embodiments, techniques for rationalizing a recommendation include determining a recommended item for a user using a first recommendation engine, wherein the first recommendation engine receives as an input first behavioral data associated with a user, and generates an identifier corresponding to a recommended item; creating a rationalization for the recommended item using a first rationalization engine, wherein the first rationalization engine receives as inputs the recommended item and second behavioral data associated with the user, and generates a rationalization, wherein the rationalization includes a constructed rationalization of why the recommended item is recommended for the user, and wherein the creation of the rationalization is not based solely on an actual reason the first recommendation engine determined the recommended item; associating the rationalization for the recommended item with the recommended item; and providing the recommended item and associated rationalization.