UJET Launches AI-Modeled Interaction Design
UJET’s AI-modeled Interaction Design for virtual agents helps companies identify the common customer needs, informed by large-scale AI insights directly from customers, and then automates their resolution. UJET, providing cloud contact centre solutions, launched AI-Modeled Interaction Design. It will help companies identify and value optimal virtual agent deployments leveraging customer insights to drive enhanced customer […]
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UJET’s AI-modeled Interaction Design for virtual agents helps companies identify the common customer needs, informed by large-scale AI insights directly from customers, and then automates their resolution.
UJET, providing cloud contact centre solutions, launched AI-Modeled Interaction Design. It will help companies identify and value optimal virtual agent deployments leveraging customer insights to drive enhanced customer experience (CX) capabilities and automated virtual agent responses.
“Contact centre demand is rising as labour shortages continue. As a result, wait times are longer than ever, service is suffering, and customers are rightly irritable. AI can and should take on a more prominent role to keep businesses running smoothly and customers happy,” said Vasili Triant, chief operating officer at UJET, in a statement. “Our latest AI technology holds immense potential to transform organisations and, when designed correctly, can dramatically improve experiences, enhance efficiency, raise productivity, and drive growth.”
UJET’s AI-modeled Interaction Design for virtual agents helps companies identify the most common customer needs, informed by large-scale AI insights directly from customers, and then automates their resolution. They are leveraging conversational AI and machine learning powered by Google’s CCAI Insights and UJET architects’ contact centre optimisation roadmaps to unlock human and machine capabilities.
With topic and conversation analysis, companies can get a prioritised list of the virtual agents they need to make the most significant difference for CX. It improves key customer care metrics such as wait time, self-service rate, first-call resolution, and much more. The data gathered has actionable insights and capabilities, including the following:
- It resolves recurring points of customer concerns, such as issues with payment methods, passwords, website/app rendering on different platforms, and much more.
- Proactively address rising trends in complaints or returns before they become a bigger problem.
- Harnessing customer insights based on repeated requests for new product lines or enhancements to existing products/services.
- It gathers competitive intelligence directly from end-users. Hear now from customers about what they liked or didn’t like with a competitor.