Use case

Sentiment Trends

Trend lines on sentiment, satisfaction, and dissatisfaction signals across channels and cohorts — calibrated against a CSAT or NPS baseline so the curve means something.

Overview

Sentiment scores in isolation are noise. Sentiment trends, calibrated against a real survey baseline, are an early warning system.

What it solves

Surfaces sentiment shifts in time to investigate them, instead of after the quarterly survey confirms the trend.

How we build it

Sentiment and CSAT-proxy extraction per conversation, calibrated against a real survey baseline (CSAT, NPS) so the model's score has a known mapping to the metric the business already tracks. Trends per channel, per cohort, per product area. Material shifts alert with example threads.

  • Per-conversation sentiment and CSAT proxy
  • Calibrated against real survey baseline
  • Trends per channel and cohort
  • Alert with example threads

What changes when it is in place

Sentiment becomes a tracked operational signal, not a vibe.