Comparison
Which to choose: a conversation analysis platform or just transcription?
The short answer: transcription turns audio into text and stops there. A conversation-analysis platform takes that text as raw material and builds everything else on top: metrics for every call, topics and tags by meaning, quality scoring against your criteria, search by meaning, automations and dashboards. If all you need is the transcript text, take transcription — it's cheaper and simpler. If you need an answer to "what is happening in these conversations and what to do about it," a transcript alone isn't enough.
The difference isn't recognition quality but what happens afterwards. A transcript sits there as text that someone still has to read. The platform immediately tags conversations, extracts the fields you need, surfaces problem calls and rolls everything into analytics — you work with conclusions, not hundreds of pages of transcripts. Transcription lives inside the platform too: it's its first step, not the whole product.
| Analysis platform | Just transcription | |
|---|---|---|
| Audio to text | ✓ (first step: system engines + BYO key + self-hosted) | ✓ — this is the entire result |
| Metrics per call | 49 system metrics + your own (text/number/yes-no/date…) | No |
| Topics and tags by meaning | AI tags and auto-categorization by your rules | No |
| Quality control against criteria | Every call scored against your criteria | Read transcripts by hand |
| Search by meaning | Semantic search, not word-matching | Only text search over the transcript |
| Automations | Condition → action: tags, extraction, webhook, CRM, notifications | No |
| Dashboards and trends | 10 chart types, period comparison, AI series builder | No |
| Archive retro-analysis | Run rules and metrics across the whole archive | Only re-transcription |
| Cost and simplicity | More expensive: STT + AI processing + analytics | Cheaper and simpler for a one-off task |
When to choose a conversation analysis platform
When the question isn't "what was said" but "what to do about it": where deals slip, which objections recur, whether the script is followed, whether negativity is rising. The platform tags every call with metrics and topics, scores it against your criteria and surfaces problem records — you look at conclusions and trends instead of reading transcripts.
When calls come in volume, in a stream: you need search by meaning instead of scanning text, automations (extract fields, apply tags, push data to CRM, send an alert) and dashboards where the dynamics are visible. And when you need to run your criteria across the whole historical archive, not just new calls.
When transcription alone is enough
When you need the text and nothing beyond it: subtitles, the transcript of a single interview or meeting, a one-off "get a document out of this recording" task. Here metrics, tags and dashboards are overkill, and a plain transcript covers the need faster and cheaper.
When the volume is small and you'll review the calls yourself anyway, by eye. If the stream of conversations grows and the question "what's happening in them overall" appears, transcription stays as the first step and analysis is built on top — so the switch won't require changing the recognition tool.
Comparison
Frequently asked questions
Isn't analysis just transcription plus text search?
No. Text search finds words you already know, and only in the transcripts you've opened. Analysis works by meaning: it tags calls with metrics and topics, scores them against criteria and surfaces problem conversations on its own — even when you didn't know what to look for. The transcript is raw material, not the answer.
If I already have transcripts, do I have to redo everything?
No. Transcription inside the platform is its first step, so analysis builds on exactly that text. An existing archive of transcripts or recordings can be run through metrics, topics and rules retroactively, without re-recognizing where the text already exists.
When is plain transcription honestly enough?
When you only need the text: subtitles, the transcript of a single meeting or interview, a one-off task. If conversations aren't a steady stream and you don't intend to measure trends, control quality or automate processing over them, the platform is overkill and simple transcription suffices.
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