Every conversation, scored and searchable.
Traditional QA samples 2% of calls. Interaction Analytics scores every voice call, chat, SMS, and email, surfacing why churn rises before the data lands in a ticket.
My account was charged twiceBilling this month.
I can see both charges, reversing one right nowResolution.
I've been waiting twenty minutesFrustration already.
Making your case top priorityEmpathy right now.
What it answers
Questions your QA spreadsheet
has never answered, in real time.
Which topics are driving the most contacts this week?
Conversation clusters surface automatically, emerging spikes land in your digest before engineering hears about them in a ticket.
Which agents skipped the compliance disclosure?
Every call is checked against your keyword list. Misses are flagged in the agent's record and the supervisor's daily alert within minutes.
Where are refund conversations getting stuck?
Step-level mapping shows which phrase, channel, or moment breaks the flow, so coaching targets the root cause, not the symptom.
What patterns correlate with five-star CSAT scores?
Cross-call analysis links tone, pacing, and phrase choice to the outcomes your best agents produce every shift.
Auto-QA coverage
Every call. Auto-scored.
Not a sample. Not a weekly batch. Every interaction, scored the moment it ends.
Voice calls, chat sessions, SMS, and email are all scored through the same rubric, so QA compares apples to apples across every channel.
Scores are in the agent's record minutes after a call ends, not in next week's coaching session when the moment is already forgotten.
Topic intelligence
Topics, not just transcripts.
The engine clusters every conversation by topic automatically. Emerging spikes surface in a weekly digest, so product and CX read the same report, in the same language.
Data export
Your data. Your stack.
Scores, topic tags, and agent metrics export to the tools your team already uses. No proprietary lock-in.
Executive reporting
Reports a CFO might actually open.
Revenue from calls
Inbound interactions traced to pipeline, which conversations create customers and which ones lose them.
Cost by channel
Voice vs. chat vs. SMS, where agent minutes are spent and what each channel costs relative to the outcome.
Churn prevention
Repeat contacts, frustration spikes, unresolved issues, flagged early, before the customer decides to leave.
"We found out that 'app crash on Android' was our top contact driver three weeks before it showed up in the engineering backlog. Product fixed it. Calls dropped. That's the loop we'd been trying to close for two years."
FAQ
Questions we hear on the first call
Does it cover voice, chat, SMS, and email?
Yes. Every channel is scored through the same rubric. Filter by channel or compare across them in one dashboard.
Can we define custom scorecards?
A drag-and-drop builder lets you set which behaviours matter and at what weight. Changes apply retroactively across your archive.
How does sentiment scoring work?
A fine-tuned model reads the full conversation arc and produces a trajectory, you see where frustration peaked and whether the agent recovered.
Can we flag compliance phrases automatically?
Yes. Define keyword lists, disclosures, banned phrases, competitor names, and every call is checked. Misses surface in the supervisor's daily alert.
What happens to data after we export it?
It's yours. Structured rows land in your warehouse on your schedule. No read-back, no model retraining on your conversations.
How quickly are scores available after a call ends?
Minutes. Scores are in the agent's record before the shift debrief, not in next week's coaching session.
Explore next on letsdial
Every call, scored automatically.
Topic clusters, deal-risk signals, supervisor-ready dashboards.
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