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Turn call transcripts into actionable insights. Analyze sentiment, extract intent, measure quality scores, and identify improvement opportunities.
Paste a call transcript to see AI-powered analysis
Tip: Include speaker labels (AI:/Customer:) for better analysis
Paste a transcript and click "Analyze" to see insights
Comprehensive insights from every conversation
Sentiment Analysis
Track emotional tone throughout the call. Identify when sentiment shifts positive or negative.
Metrics provided:
Intent Detection
Understand what the customer wants. Classify intent into categories like support, sales, complaint.
Metrics provided:
Entity Extraction
Pull out important details: names, order IDs, dates, amounts, product mentions.
Metrics provided:
Quality Scoring
Rate call handling quality. Compare against benchmarks and identify coaching needs.
Metrics provided:
Conversation Flow
Analyze how the conversation progressed. Identify where things went well or poorly.
Metrics provided:
Summary Generation
Auto-generate call summaries for CRM. Capture key points without manual note-taking.
Metrics provided:
How teams use transcript analysis
Quality Assurance
Automatically score 100% of calls instead of sampling. Identify agents or prompts that need improvement.
Example:
Flag calls where quality score drops below 7
Prompt Optimization
Analyze how voice AI handles different scenarios. Find where customers get frustrated or confused.
Example:
Discover that 40% of callers ask about pricing but script doesn't address it
Competitive Intelligence
Track mentions of competitors, pricing discussions, and feature requests across all calls.
Example:
Alert when customers mention switching to competitor
Training & Coaching
Use transcript insights for agent training. Show specific examples of good and poor handling.
Example:
Review calls with high escalation rates to identify patterns
Common questions about call analytics
You can extract sentiment (positive/negative/neutral), customer intent, action items, objections, competitive mentions, satisfaction indicators, and conversation quality metrics. The analyzer provides both quantitative scores and qualitative insights.
Our sentiment analysis achieves 90%+ accuracy on clear statements. Mixed sentiment or sarcasm can be harder to detect. The analyzer shows confidence scores so you know when to review manually.
Yes, the analyzer supports multilingual transcripts including Hindi, Tamil, Telugu, and other Indian languages. It can also handle code-switched conversations (mixing Hindi and English).
Key metrics include: talk time ratio, interruption count, silence duration, resolution indicator, escalation flag, sentiment trajectory, and overall quality score (1-10). These help identify coaching opportunities.
Both. For live calls, real-time analysis provides immediate alerts (e.g., 'customer frustrated'). For recordings, you get comprehensive post-call reports. Historical analysis helps identify patterns across many calls.
The analyzer highlights specific improvement areas: 'Agent interrupted 5 times' or 'Customer mentioned competitor X'. Use these insights to update prompts, add objection handling, or improve training.
You can paste text transcripts directly, upload .txt files, or connect to call recordings (we'll transcribe them). For production use, our platform automatically captures and analyzes all calls.
Yes, configure rules like 'Alert when sentiment drops below 3' or 'Flag calls mentioning refund'. Alerts go to Slack, email, or your CRM. This helps catch issues in real-time.
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