Quality Monitoring refers to the use ofconversational analytics technologies (including Speech Analytics) to evaluate the quality of customer interactions systematically and on a large scale, rather than through occasional manual listening. In concrete terms, it automates the process of listening to customer calls or conversations and analyzing their content. While traditional manual quality control only covers 1 to 5% of recorded calls, automatic analysis allows 100% of interactions to be screened, avoiding the loss of valuable information in a random sample of calls. In other words, AI scans all conversations and systematically detects occurrences of quality criteria (greetings, speech compliance, problem resolution, etc.), thus providing comprehensive and consistent quality coverage.

This automation differs from manual control in terms of speed, efficiency, and scalability. According to a specialist publication, what humans traditionally did can now be achieved much faster and on a larger scale thanks to AI. Speech Analytics automatically Speech Analytics structured information from each customer conversation, whereas a human supervisor would only have been able to listen to a fraction of them. It is therefore a productivity lever for Quality teams: they can devote their time to analyzing results and coaching, rather than manually listening to each call.