Customer signal arrives scattered across calls, tickets, surveys, and cancellations, and most of it is never read, let alone synthesized. The deciqAI customer listening agent turns that firehose into clear themes, so you stop guessing what customers want and start seeing it.
── ── What it does
- Synthesizes sales calls, support threads, and cancellations
- Detects churn signals and captures the reason behind them
- Rolls up NPS open text by theme, segment, and sentiment
- Surfaces recurring feature and pain themes with verbatim
- Watches competitors for pricing, product, hiring, and PR moves
- Answers what to build next and why, backed by signal
How does the listening agent synthesize customer feedback?
It processes every sales call, support thread, and cancellation as it happens and rolls the signal up into themes by segment and sentiment. Instead of reading 200 tickets, you get the patterns that actually recur and the verbatim behind them.
Can it tell me why customers are churning?
Yes. It detects churn signals and attaches the why, the actual reason a customer disengaged or canceled, not just the fact that they left. That turns churn from a lagging number into an early warning you can act on.
Does it track competitors too?
It runs a competitor watcher that flags pricing, product, hiring, and PR changes daily. You see what rivals are moving on without manually checking their sites, so your roadmap reflects the market, not last quarter.
FAQ
How is this different from reading my support tickets myself?
The agent reads all of them continuously and synthesizes the patterns, so you see recurring themes and sentiment trends instead of a few anecdotes you happened to catch.
Does it explain churn or just count it?
It captures the why behind each churn signal, the actual reason a customer disengaged, so you can fix causes rather than watch a number drop.
Can it really tell me what to build next?
It ranks recurring themes by frequency, segment, and sentiment and ties them to real customer language, giving you an evidence-backed answer instead of a guess.