Online marketplaces have transformed how consumers search and match in the labor, housing, and dating markets through technologies such as search engines, reputation systems, and mobile apps. Not only have these platforms reduced the cost of search but, for transactions such as short-term apartment rentals (Airbnb), cross-border professional services (Odesk and Freelancer), and rides (Uber and Lyft), they have greatly expanded the size of their respective markets. However, little is known about how matches form on these platforms, the role of technology in creating those matches, and the potential for making matching more efficient through better marketplace policies. Furthermore, although search and matching plays a pivotal role in theories of market failure, data on this process has historically been scarce and often incomplete. The comprehensive data regarding browsing, communication, and transactions collected by these marketplaces allows for novel tests of search and matching theories. This project uses this type of data from Airbnb, as well as new models of search, to study the role of technology in making the search and matching process in this marketplace more efficient.