Many information technology startups have embraced "lean startup" management practices. Lean startups confront high levels of uncertainty about both customer problems and product solutions: the strength of demand for new solutions to prospective customers' problems is not well understood, nor is it clear how new solutions to these problems should be built. Lean startups address this uncertainty through very rapid cycles of hypothesis-driven, customer-centric experimentation. Objectives include: building, measuring, and learning at an accelerated pace; failing fast; and constantly improving a product based on nearly-immediate customer feedback. Lean startup practices often encompass: 1) launching with a "minimum viable product," that is, the smallest possible set of features that will meet the needs of early evangelists; 2) reliance on free open source software modules and "agile" software development methods in which requirements and solutions evolve iteratively through the collaboration of cross-functional teams; 3) intensive use of customer interviews, surveys and split market testing to gauge demand for new features; and 4) bootstrapping and avoiding heavy investments in customer acquisition to keep burn rates low until hypotheses about customer problems and product solutions are verified. Eisenmann's research on lean startups focuses on identifying contingencies under which different practices are economically attractive and determining which practices apply to new ventures outside the information technology sector.