Sentiment Analysis
Meza AI automatically analyzes customer communications to detect sentiment trends, identify at-risk accounts, and surface engagement opportunities.
How Sentiment Analysis Works
Data Collection
Meza ingests communications from connected sources like email, support, and meetings
AI Analysis
Our AI models analyze language patterns, tone, and context to determine sentiment
Score & Alert
Sentiment scores update in real-time and trigger alerts when trends change
Supported Data Sources
Email Communications
Analyze sentiment from customer email threads and responses
Support Tickets
Extract sentiment from support conversations and resolutions
Meeting Transcripts
Analyze sentiment from recorded calls and meetings
Chat & Slack Messages
Real-time sentiment from chat interactions
Sentiment Score Scale
Key Use Cases
Churn Risk Detection
Declining sentiment trends often precede churn. Get alerts when customer sentiment drops significantly.
Expansion Opportunity
Positive sentiment combined with high engagement signals expansion readiness.
Health Score Input
Sentiment scores feed into overall account health calculations for comprehensive risk assessment.