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Below is a sample analysis of 25 customer support conversations. This is exactly what you get after uploading your own data.
Conversations Analysed
25
Topics Identified
8
Avg. Sentiment
+0.42
Action Items
12
Sentiment Breakdown
Average sentiment score
+0.42 / 1.0
Topic Distribution
Sample Conversations
Each conversation is individually scored and categorised. Click to expand.
AI-Generated Action Items
Prioritised recommendations based on the analysis results.
Improve billing transparency
Multiple customers reported confusion over duplicate charges. Add real-time billing notifications and a clear charge breakdown in the account dashboard.
Reduces billing-related contacts by ~40%
Reduce first response time
3 conversations mentioned waiting 2+ days for a reply. Target: respond to all tickets within 4 business hours.
Estimated 25% improvement in CSAT
Promote loyalty programme
Loyal customers show highest sentiment (+0.80). Proactively communicate rewards during support interactions.
Potential 15% increase in repeat purchases
Expand self-service returns portal
Returns & refunds conversations had the second-lowest sentiment. A streamlined self-service flow could reduce friction.
Save ~2 agent-hours per day
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