Transactional data structures allow data structures to support transactional execution, in which a sequence of operations appears to execute atomically. We consider a paradigm in which a transaction commits its changes to the data structure only if all of its operations succeed; if one operation fails, then the transaction aborts. In this work, we introduce an optimization technique called Check-Wait-Pounce that increases performance by avoiding aborts that occur due to failed operations. Check-Wait-Pounce improves upon existing methodologies by delaying the execution of transactions until they are expected to succeed, using a thread-unsafe representation of the data structure as a heuristic. Our evaluation reveals that Check-Wait-Pounce reduces the number of aborts by an average of 49.0%. Because of this reduction in aborts, the tested transactional linked lists achieve average gains in throughput of 2.5x, while some achieve gains as high as 4x.