Programs that use hardware transactional memory (HTM) demand sophisticated performance analysis tools when they suffer from performance losses. We have developed TxSampler—a lightweight profiler for programs that use HTM. TxSampler measures performance via sampling and provides a structured performance analysis to guide intuitive optimization with a novel decision-tree model. TxSampler computes metrics that drive the investigation process in a systematic way. It can not only pinpoint hot transactions with time quantification of transactional and fallback paths, but also identify causes of transaction aborts such as data contention, capacity overflow, false sharing, and problematic instructions. TxSampler associates metrics with full call paths that are even deeply embedded inside transactions and maps them to the program’s source code. Our evaluation of more than 30 HTM benchmarks and applications shows that TxSampler incurs ~4% runtime overhead and negligible memory overhead for its insightful analyses. Guided by TxSampler, we are able to optimize several HTM programs and obtain nontrivial speedups.