Inverted files have been very successful for document retrieval, but sponsored search is different. Inverted files are designed to find documents that match the query (all the terms in the query need to be in the document, but not vice versa). For sponsored search, ads are associated with bids. When a user issues a search query, bids are typically matched to the query using broad-match semantics: all the terms in the bid need to be in the query (but not vice versa). This means that the roles of the query and the bid/document are reversed in sponsored search, in turn making standard retrieval techniques based on inverted indexes ill-suited for sponsored search. This paper proposes novel index structures and query processing algorithms for sponsored search. We evaluate these structures using a real corpus of 180 million advertisements.