I'm currently evaluating dedicated transcription services for our sales team's call recordings. We've narrowed the field to Sembly and Otter.ai, but I'm struggling to find objective, current data on their core transcription accuracy for sales-specific use cases.
Most reviews focus on features, but for our FinOps lens, accuracy directly impacts ROI. Higher accuracy means less manual correction time, which translates to lower total cost of ownership. We need reliable transcripts for CRM updates and training materials.
From my preliminary analysis:
* **Vocabulary:** Sales calls contain industry jargon, product names, and client names. How well does each platform handle proper nouns without extensive training?
* **Speaker Diarization:** Critical for understanding who said what in a multi-party deal conversation. Which service more consistently and correctly labels sales reps vs. multiple clients?
* **Audio Quality Realities:** We deal with varying source quality—poor cell connections, background noise in open offices, and cross-talk. How do they compare under these non-ideal conditions?
* **Accent Handling:** Our team and client base is global. Performance with non-native English accents is a key differentiator.
I'm less interested in the note-taking features or meeting assistants at this stage. My primary benchmark is word-for-word accuracy rate in a B2B sales environment. Has anyone conducted or seen side-by-side accuracy tests using real sales call audio? I'm particularly interested in:
* Quantitative error rates (WER)
* The nature of common errors (e.g., mis-transcribing key numbers, mangling product names)
* Any patterns in where one service consistently outperforms the other
Buy once, cry once.