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Guide/Report/White paper

AI-enabled Quality Assessments

Learn how you can benefit from consistent and objective AI-enabled agent quality assessment in your contact centre.

In short, Quality assurance (QA) has long been at the forefront in the battle to improve contact centre performance and customer experience.

There are many experienced quality managers and supervisors working in contact centres and call centres today. And most of these operations have thousands if not millions of interactions stored – voice, email, and SMS. However, contact centres are missing out on huge opportunities to improve performance and gain insight. This is because most companies do not evaluate these stored customer interactions.

To counteract this problem, companies are increasingly using AI-enabled agent quality assessment to transcribe and analyse all interaction recordings.

Agent Quality Assessments

Contact centre management should take the responsibility of identifying  the required agent behaviours and characteristics. Moreover, to align these to the contact centre operational requirements. In turn, they should themselves be driven by the strategic requirements of the entire organisation.

The process of quality assurance tends to look at several specific steps in an iterative cycle:

  • Interaction recording
  • Monitoring and scoring interactions
  • Identification of issues and subsequent feedback, coaching, training and eLearning
  • Reporting at an integrated level
  • Identification of areas for improvement

Download this whitepaper by ContactBabel to learn more about what other organisations are thinking. See how you can benefit from consistent and objective AI-enabled agent quality assessments in your contact centre.