Industry solution
Sales rep coaching on real call data
Call reviews in sales usually rest on impression and a couple of recordings: who to coach and on what skill is decided by feel. The platform breaks every conversation down into objective metrics — interruptions, speech pace, rep talk share, response delay, tone, longest monologue — and shows conversion by rep and stage. Sales coaching stands on facts, not on subjective judgment.
For a manager this changes the very mechanics of developing the team. Weak spots surface through semantic search and rep comparison on dashboards, the copilot assembles the needed sample from a plain query — for example, every call where the rep talked over the client and lost the deal — and the review runs on specific conversations. The strong patterns of top reps become visible and transferable to the rest.
Which industry pains this solves
Leads go cold on slow callbacks
By the time a rep reaches the request, the lead has already talked to a competitor. Speed of the first touch drives conversion, but there's physically no one to call everyone back at once.
Call control is a 2–3% sample
A manager or the QA team gets to listen to 2–3% of calls. What reps actually say on the other 97% and why deals fall through stays out of view.
How it works
A step-by-step scenario — the same steps as in the full use case, applied to your industry.
- 1
Every call is tagged with conversation metrics
Across 100% of recordings the platform computes objective metrics: interruptions, agent and customer talk ratio, speech pace, filler words, longest monologue, response latency, silence share and tone.
- 2
An agent profile on a dashboard
Metrics roll up into charts per agent: where they interrupt, where they pull the conversation onto themselves, where they rush. You see strengths and weaknesses, not a vague "work on yourself."
- 3
Benchmark against your best
Comparing agents and periods on one chart shows how the conversations of your strongest differ from the weakest on concrete metrics — that's the benchmark you pull everyone else up to.
- 4
Review specific moments by timecode
Metrics are tied to timecodes in the transcript: you open the exact spot where the agent interrupted or ran into a monologue. The AI copilot and semantic search find such moments by meaning for one-on-one reviews.
- 5
Progress trajectory over time
The same metrics broken down by period show whether an agent is improving after coaching: fewer interruptions, a more even talk ratio, cleaner speech. Progress is visible to the manager and to the agent alike.
Industry scenario
Why one rep's conversion is twice as high
Two reps with a similar lead flow have conversion that differs twofold, and it's unclear why. The manager opens the dashboard and compares them on conversation metrics: the lagging rep's own talk share is 70% versus 55% for the leader, response delay is higher, and there are noticeably more client interruptions. The picture clears up — he's not so much selling as talking over the client.
On request the copilot assembles a sample of that rep's calls where the client raised an objection and the rep interrupted and didn't let them finish. At the meeting they review three specific recordings with timecodes: in each you can hear the deal break right at that moment. Instead of an abstract "listen to the client more carefully," the rep gets a measurable goal — reduce own talk share and interruptions.
At the same time the leader's best calls are saved as a benchmark: you can hear how he holds a pause, mirrors the need and leads to the next step. These patterns become training material for the whole team, and the lagging rep's progress is tracked on the same metrics week over week — coaching stops being a one-off talk and becomes a managed, data-driven process.
Key facts
- What's measured
- Interruptions, talk ratio, pace, filler words, longest monologue, response latency and tone — across 100% of calls.
- Comparison
- Agent profiles on one dashboard, benchmarked against your best and across periods.
- Review
- Metrics are tied to transcript timecodes; the AI copilot and semantic search find the right moments by meaning.
- Progress
- Metric trends by period show whether an agent is improving after coaching.
- Automatic
- Metrics are computed automatically on every recording — no separate manual scoring needed.
Related scenarios for this industry
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