A global business process outsourcing
taps auMina™ for 100% call monitoring
and sentiment analysis

A global leader in business process outsourcing and information technology services across multiple locations with over 80,000 professionals. The company helps their clients to create a competitive edge by utilizing business process outsourcing and IT services.


CHALLENGES
  • Inability to monitor huge call volumes owing to the lack of QA bandwidth
  • Lack of actionable insights to improve customer satisfaction
  • Lack of understanding of the ‘real voice’ of customers using traditional survey methods

SOLUTION
  • auMina™ uses Machine Learning (ML) based voice recognition technology to analyze the customer’s voice data and derive actionable business insights.

BUSINESS BENEFITS
  • Enabled 100% call monitoring
  • Customized and flexible dashboards offering near real-time, and actionable insights
  • Identified gaps in the IT helpdesk process
  • Improved agent soft skills and IT skills
  • Recognized leaders and laggards through automated call scoring
  • Auto-generated reports on a daily and weekly basis

THE BUSINESS NEED

The company wanted to deliver business insights to one of their Fortune 500 customers, who used the company’s services for its Global IT helpdesk. The client did not have enough QA bandwidth to monitor high volumes of calls and was able to monitor only 5-10% calls manually. Consequently, it was difficult to evaluate agent’s performance, understand the customer’s ‘real voice’, and measure customer satisfaction scores.


AN INSIGHTFUL CONVERSATIONAL ANALYTICS SOLUTION

The company approached Uniphore for a solution to address the business need. auMina™—a conversational analytics platform—was recommended. It provided the customer with actionable insights to evaluate agent performance and calls.

The conversational analytics solution enabled 100% monitoring of calls. The solution also provided auto generation of customized and advanced reporting, helping the company to identify targeted training to agents, leading to enhanced customer service experience. All customer-agent interactions were monitored on different parameters such as agent performance trends, individual agent performance, location, and other considerations. Unlike the conventional method of measuring customer satisfaction through an after-call-survey, the company could now assess customer satisfaction with 100% call monitoring, thus arriving at CSAT scores in a uniform and unbiased manner.