The widespread availability of broadband connections has led to an increase in the use of Internet broadcasting (webcasting). Most webcasts are archived and accessed numerous times retrospectively. In the absence of transcripts of what was said, users have difficulty searching and scanning for specific topics. This research investigates user needs for transcription accuracy in webcast archives, and measures how the quality of transcripts affects user performance in a question-answering task, and how quality affects overall user experience. We tested 48 subjects in a within-subjects design under 4 conditions: perfect transcripts, transcripts with 25% Word Error Rate (WER), transcripts with 45% WER, and no transcript. Our data reveals that speech recognition accuracy linearly influences both user performance and experience, shows that transcripts with 45% WER are unsatisfactory, and suggests that transcripts having a WER of 25% or less would be useful and usable in webcast archives.