Dialpad AI Customer Service Analytics
Key Results
Call coverage (from 5% manual sampling)
Sentiment and topic insights
Manager time saved on call reviews
1The Challenge
Customer service managers were manually reviewing call recordings to understand common issues, agent performance, and customer sentiment. This was time-consuming, inconsistent, and couldn't scale with growing call volume.
2Our Solution
Built an AI-powered analytics workflow that automatically transcribes calls, uses Claude/GPT for sentiment analysis and topic categorization, and surfaces insights through an automated dashboard and email reports.
Our Approach
Integrated with Dialpad system via API/Webhook to capture call recordings and metadata
Implemented AI transcription and analysis pipeline using Claude/GPT for sentiment, topic categorization, and resolution detection
Built metadata extraction for call duration, agent ID, and timestamps
Created data aggregation and validation layer before loading to analytics database
Designed CS Analytics Dashboard (Web UI) with automated PDF/email reporting
✓The Impact
Call coverage (from 5% manual sampling)
Sentiment and topic insights
Manager time saved on call reviews
Technology Stack
Project Details
Client
Customer Service Organization
Industry
AI & Automation
Duration
8 weeks
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