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This is our story of helping a leading insurer maximize the value of its interaction analytics platform to enhance customer experience and drive significant savings. By applying deep domain expertise, we uncovered critical inefficiencies in customer interactions. Our analysis focused on leveraging advanced sentiment analysis to unlock actionable insights and enable strategic improvements.

As we know…

The insurance industry is transforming rapidly, driven by evolving customer expectations and the increasing adoption of advanced analytics tools. However, maintaining seamless customer experiences across claims, sales and customer care operations remains a common challenge.

Contact centers often struggle to understand customer intent, reduce repeat contacts and leverage technology for automation – all critical to improving operational efficiency and customer satisfaction.

The challenge for our client was…

Without clear insights into customer behavior, it faced inefficiencies in resolving queries, which led to customer dissatisfaction and increased operational costs. Despite significant investment in a leading interaction analytics platform, the client needed help to extract actionable insights.

The core challenges included :

Customer Intent Categorization

Understanding the reason behind customer interactions to provide personalized responses

Repeat Contact Reduction

Reducing the number of follow-ups with customers calling for the same issue

As the consulting and domain partner…

WNS collaborated with the client to unlock the full potential of their interaction analytics platform. Our functional expertise with the client’s existing platform ensured high-quality project delivery within tight timelines.

We conducted an in-depth analysis of customer interactions to accurately identify the intent and the root cause for repeat contacts. This targeted approach enabled WNS to achieve an 85 percent intent categorization rate, delivering actionable insights to drive meaningful improvements.

Key aspects of the solution included:

  • AI-driven Insights

    Used Artificial Intelligence (AI) capabilities within the interaction analytics platform to enhance customer sentiment understanding

  • Comprehensive Recommendations

    Delivered 39 tailored recommendations addressing agent training, process optimization and technology enhancements

Seven recommendations for agent training and skill development

Seven recommendations for process improvement

25 recommendations for technology and digital intervention

The detailed analysis…

Enabled the client to enhance agent performance through targeted training, streamline business processes to improve efficiency and implement technology-driven solutions to automate tasks and reduce repeat interactions.

Quantifiable outcomes included:

 percentage point reduction in repeat contacts
 

AUD  Million in annualized savings through contact reduction  

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