Abstract: In the current era, product differentiation is increasing; it is often fueled by big data and artificial intelligence (AI). Whereas product differentiation is generally welfare enhancing when consumers are informed and fully rational, such differentiation might reduce welfare when consumers suffer from misperceptions, either because of a lack of information or because of behavioral biases. We show that the positive and normative implications of product differentiation depend on whether consumers over-or underestimate the benefits from some products. In particular, over-estimation of the benefits is a potential source of significant welfare losses. We also study sellers' incentives to promote, or combat, misperception. Our analysis can inform policymakers who are debating regulation that can make product differentiation more difficult (or easier), especially when the differentiation is instigated by AI algorithms powered by big data.