Lenient return policies enable consumers to return or exchange products they are unsatisfied with, which boosts sales. Unfortunately, they also increase retailer costs. We develop a search framework where consumers sequentially learn about products’ true value and evaluate whether to keep, exchange, or return them. Our formulation results in a tractable attraction demand model that can be used for optimization. We show that when pricing is not a decision, the assortment problem does not have a simple structure, but we provide an approximation algorithm to solve it. When prices and assortment can be controlled, the optimization becomes tractable: product prices can either be set so that potential return costs are added to the product price, be reduced to ensure that consumers choose to evaluate them after an exchange, or be set so high so that the items are effectively excluded from the assortment. We find that when prices and assortment can be jointly optimized, assortment size always increases when consumers pay a higher share of the return cost. Finally, retailers prefer to pass all return costs on to the consumers, which not only improves social welfare but also can raise consumer surplus.