Customer service interactions at massive scale, and no systematic read on how customers really felt. Leadership heard anecdotes. Nobody could see the trend.
- A sentiment analysis model scoring customer service interactions
- Theme and trend tagging so patterns surface by topic, team, and time period
- Reporting that turned every conversation into evidence leadership could act on
Every interaction gets scored and tagged automatically, the moment it exists. What used to be a hallway argument about how customers probably feel becomes a chart of what the data says, and where it is moving.
Sampled QA and anecdotes gave way to evidence leadership can act on, with every customer service interaction scored and tagged, and patterns visible by topic, team, and time period.
Wherever conversations pile up faster than anyone can read them, a model can read all of them, and once the whole population sits on one chart the argument about anecdotes is over. Support tickets, call transcripts, app reviews, survey verbatims.