Score 100% of conversations, not a sample
Most quality programmes review a handful of calls per agent each month — often around 1% of the total. That is enough to satisfy a compliance box, but far too little to coach fairly or catch a problem early. If you review 1% of conversations, you are guessing about the other 99%.
The result is unfair scores, missed risks and coaching built on whichever calls happened to be picked. Sampling was always a workaround for the fact that humans can't review everything. Automation removes that limit.
How Feelingstream helps
Feelingstream transcribes every call with speech-to-text and, together with chats and emails, evaluates each one against your existing scorecard. The same checks a manual reviewer would apply — identity verification, mandatory disclosures, tone, correct process, resolution — run on every conversation, automatically.
Each evaluation is shown beside its evidence: the transcript, and for calls the time-aligned audio. Reviewers add comments where human judgement matters, so automation handles the scale while people handle the nuance. Nothing is a black box; every score can be traced back to what was actually said.
What you can measure
- Review coverage rising from a small sample to 100% of conversations
- Fewer disputed or inconsistent scores between reviewers
- Earlier detection of compliance and quality risks
- Team-wide score trends that reveal where to focus coaching
Where to go next
- Pillar guide: Automated call-centre quality assurance
- Product: Automatic quality scoring
- How it works: Inside an automated quality evaluation
- Coaching: Coach on evidence, not anecdotes
Ready to score every conversation against your own scorecard instead of a sample? Book a demo.