Sentiment Trends
A running measure of how customers feel, drawn from every conversation and checked against your real survey scores — so a dip shows up early, not at the quarterly review.
A once-a-quarter survey is like asking someone how they felt all winter. A calibrated sentiment trend is more like a daily thermometer: each single reading is rough, but the curve — checked regularly against surveys you trust — shows when the temperature really starts to drop, while there is still time to do something.
The problem, in plain words
Your customers tell you how they feel constantly — in tickets, in chat, in offhand remarks — but that feeling only becomes a number once a quarter, when the survey results come in. By then, whatever soured them has been souring them for months. And raw AI sentiment scores on their own do not fix this: a model calling a message 6.2 out of 10 means nothing unless you know how that maps to the satisfaction metric your business already tracks. Uncalibrated scores are noise with decimals.
What we set up
We extract a sentiment reading and a satisfaction estimate from every conversation, across every channel. Then comes the part that makes it trustworthy: calibration. The AI's scores are regularly checked against your real survey results (CSAT or NPS — the satisfaction and loyalty surveys you already run), so a given score has a known meaning in the metric your business already uses, instead of being an arbitrary number. From there we draw trend lines per channel, per customer group, and per product area. When a curve moves in a way that matters, an alert goes out — and it arrives with example threads attached, so the first question, what are they actually upset about, is answered before it is asked.
How it works, step by step
- Every conversation gets a reading
Tickets, webchat, email — each conversation yields a sentiment score and a satisfaction estimate.
- Scores are calibrated against surveys
The AI's readings are regularly compared with your real CSAT or NPS results, so the numbers mean what you think they mean.
- Trend lines are drawn
Per channel, per customer group, per product area. Single scores are noisy; the curves are what carry the signal.
- A real shift triggers an alert
Not every wobble — a material move, past thresholds tuned to your data.
- Examples come attached
The alert includes actual threads behind the dip, so the investigation starts with evidence, not a hunch.
What changes for you
Before: a bad quarter announces itself in the survey results, long after the damage is done. After: sentiment is a tracked operational signal — you see a product area starting to slide while the trend is young, read the exact conversations driving it, and investigate while the cause is still fresh. What it won't do: it won't tell you why customers feel the way they do — it points at the shift and hands you the threads; the diagnosis is still human work.