CASE STUDY
20% reduction in customer complaints.

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Experiencing a rise in customer complaints and churn? Are customer support channels unable to satisfy customer demands?

Download this case study to learn:

In this case study discover how a customer remediation model:

  • Decreased customer complaints by 20%
  • Reduced case management activity by 70%
  • Improved average handling times by 22%
  • Increase net promoter score (NPS) by 53%
  • Reduced customer transfer rates by 83%
  • Exceeded sales performance targets by up to 103%.


Download now for these insights and more.

Global insurance group triages 90% of customer queries with generative AI

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90% of customer emails were triaged and categorised accurately

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Labour cost savings equivalent of up to three full-time employees

THE CLIENT

A global insurance group.

THE CHALLENGE

The client's operations team used to handle 2,000 to 4,000 email queries from customers across multiple shared mailboxes every month. This process involved up to five staff members manually reading each email to identify the customer's issue and then redirecting the query to the appropriate processing team. They sought a solution to automate this labour-intensive process, which was causing delays in resolving customer issues.

THE SOLUTION

Innovior, a Probe CX company, deployed a complete automated triaging system, leveraging generative artificial intelligence (AI) technologies such as PowerAutomate and Azure Open AI. This system was designed to automatically analyse incoming emails from all shared mailboxes. It employed a large language model, requiring no coding, to classify the content and determine its relevant processing category. Subsequently, the system efficiently routed each email to the appropriate processing queue.

THE RESULT

Through the adoption of Innovior's complete automated email triaging system, the client:

icon-gear-refreshAchieved accurate triaging and categorisation of 90% of incoming customer emails, streamlining redirection.
icon-group-of-peopleReduced manual labour costs to the equivalent of two to three full-time employees within the operations team.