Unity4 and Daisee Partner
Unity4 and Daisee Partner to provide automated quality management for customer interactions
Ops Team
Unity4 and Daisee are excited to announce a direct partnership that combines Unity4’s advanced cloud contact centre solution and experience in the work from home model with Daisee’s Automated Quality Management solution for customer interactions, powered by artificial intelligence, speech and text analytics.
The service allows organisations to quickly understand the quality of every customer interaction across three core pillars
- Communication
- Conduct
- Compliance
Understanding the impact COVID has on customers and employees is crucial to enable businesses to react and offer support immediately. The ability to have 100% coverage of all customer interactions leaves no stone unturned ensuring peace of mind and a rich dataset from which to make decisions.
Unity4 work closely with the innovators in emerging technologies and view Speech and Text Analytics and Artificial Intelligence as pivotal in unlocking data to maximise customer interactions and aid in the management of staff. Daisee is a thought leader and dynamic player in this space. Combined with an easy to consume and use model, our decision to partner was a no-brainer. Customers are getting value from day one, it is exciting times. Take the challenge and give it a try you won’t regret it.
Craig Boorman, Managing Director of Unity4 Contact Centre Technology.
Daisee ingests conversational media into its patent-pending Semantic Engine, utilising a comprehensive combination of Artificial Intelligence (AI) and Natural Language Processing (NLP) to derive Natural Language Understanding (NLU). Daisee’s machine-read comprehension of the underlying context of a communication is far superior in focus than traditional speech and text analytics that use a simple word-match and counting approach. The software groups language based on meaning which is essential to locating desirable features in interactions where similar things are said in different ways.
Once the interaction data is analysed, enriched and provided with a quality score, workflows triage low-scoring, high risk interactions for operational personnel to review and remediate. This end-to-end process is automatic.