What is Conversation Intelligence?

According to Gong (a leading conversation intelligence provider), teams using conversation intelligence see a 27% increase in win rates. The improvement comes from two mechanisms: better coaching (managers can review actual conversations instead of relying on rep self-reports) and better deal intelligence (engagement patterns in conversations reveal deal health more accurately than CRM stage updates).

Conversation intelligence also solves the institutional knowledge problem. When top performers leave, their selling techniques leave with them. Conversation intelligence captures and codifies these techniques — which questions top reps ask, how they handle objections, what talk-to-listen ratio produces the best outcomes — making tribal knowledge transferable and trainable.

The competitive intelligence value is often underestimated. Across thousands of sales conversations, conversation intelligence platforms detect which competitors are mentioned most frequently, what prospects say about them, and which competitive positioning produces the highest win rates. This intelligence feeds directly into competitive battlecards and messaging frameworks.

Conversation intelligence platforms operate through a record-transcribe-analyze pipeline.

**Recording integration** connects to meeting platforms (Zoom, Teams, Google Meet) and phone systems (dialers, VOIP) to automatically record sales conversations. Recording is triggered by calendar events or dialer activity, with consent compliance managed through notification systems. Most platforms offer both audio and video recording.

**Transcription** converts recorded audio into text using speech-to-text models. Modern transcription achieves 95%+ accuracy with speaker diarization (identifying who said what). Real-time transcription enables live conversation analysis, while batch transcription processes recordings after the call.

**Topic detection and extraction** uses NLP models to identify key moments in conversations. Automated detection surfaces: competitor mentions, pricing discussions, timeline references, objection handling, next step agreements, risk phrases ("we need to think about it"), and buying signals ("can you send a proposal?"). These moments are tagged and indexed for searchability.

**Talk analytics** measure conversation dynamics: talk-to-listen ratio (top performers average 43:57 per Gong research), monologue length, question frequency, and interactivity patterns. These metrics provide coaching baselines — a rep who talks 80% of the time is not doing enough discovery.

**Deal intelligence** aggregates conversation signals across all interactions in a deal to assess health and trajectory. If conversations show declining engagement, fewer stakeholders joining calls, or increasing objections, the deal is flagged as at-risk — often before the rep recognizes the risk themselves.

**Coaching workflows** enable managers to review conversations efficiently. Instead of listening to full 45-minute recordings, managers can jump to flagged moments — the competitor mention, the pricing discussion, the objection handling — and provide targeted feedback. Some platforms auto-generate coaching recommendations based on conversation patterns.

Autobound and conversation intelligence are complementary tools in the sales technology stack. Conversation intelligence reveals what happens during meetings; Autobound improves what happens before meetings by generating signal-informed outreach that produces better conversations. The signals and personalization anchors that Autobound identifies (recent funding, technology changes, competitive dynamics) become natural talking points during the sales call.