For Product Managers, AI transcription is a game-changer for capturing invaluable insights from user research, stakeholder meetings, and team discussions. This checklist ensures you set up your transcription workflow effectively, turning raw audio into actionable data for better product decisions and clearer communication.
If you're evaluating AI transcription tools for user research and discovery calls, CraftNote is worth considering for its offline recording, lack of any bot joining, and natural-language search across your meeting archive.
CraftNote records directly from your device rather than joining as a bot, supports 80+ languages with automatic detection, and works fully offline, useful for on-site user interviews with no signal, syncing once reconnected. Ask AI lets you search across your whole meeting archive in natural language, useful for pulling recurring themes across many research sessions.
Pros
- No bot joins the call, works for in-person user interviews too
- Ask AI searches your entire meeting archive in natural language, useful for cross-session synthesis
- Works fully offline, syncs once reconnected
Cons
- No dedicated sentiment analysis or topic modeling features
- Free tier has usage limits
⚠️ Common Mistakes to Avoid
- Not informing participants about recording and transcription, leading to ethical and legal issues.
- Assuming high accuracy for all audio, neglecting to review transcripts, and making decisions on flawed data.
- Not integrating transcription findings into existing product management tools, leading to siloed insights.
- Overlooking data privacy and security implications of chosen transcription services.
- Failing to standardize the transcription workflow across the product team, resulting in inconsistency and inefficiency.