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Recent work on argument persuasiveness has focused on determining how persuasive an argument is. Oftentimes, however, it is equally important to understand why an argument is unpersuasive, as it is difficult for an author to make her argument more persuasive unless she first knows what errors made it unpersuasive. Motivated by this practical concern, we (1) annotate a corpus of debate comments with not only their persuasiveness scores but also the errors they contain, (2) propose an approach to persuasiveness scoring and error identification that outperforms competing baselines, and (3) show that the persuasiveness scores computed by our approach can indeed be explained by the errors it identifies.