GenAI Enhances Call Center Performance and Efficiency in Energy Sector

About the Client

A leading global energy company is focused on providing sustainable and innovative solutions to meet the world’s growing energy needs. With operations spanning across various continents, it is committed to delivering reliable, affordable, and clean energy through a diverse portfolio of power generation and distribution assets.

The Challenge

An energy and utilities leader faced difficulties in evaluating the performance of their extensive call center network. Their manual process, which assessed only 4% of calls through time-consuming listening and scoring using a 25-point rubric, limited their ability to gain valuable insights. This inefficiency impeded efforts to improve customer service quality and increased operational costs.

The Solution

Leveraging Google Cloud’s AI/ML capabilities, call center agent evaluations were automated using speech-to-text, sentiment analysis, and summarization. Google’s Text-Bison model assessed transcriptions against predefined rubrics and analyzed sentiment to evaluate interactions. All calls were efficiently analyzed, eliminating manual effort. Cloud Functions and GCS automated the process, storing data in BigQuery. Managers could focus on coaching, with insights visualized in a Looker Studio dashboard.

The Result

Comprehensive Call Coverage: Automated analysis of all calls ensured complete visibility into agent performance, enhancing overall insights.

Voice of Customer Insights: Delivered in-depth understanding of customer interactions, driving meaningful operational improvements.

Manager Efficiency: Streamlined processes freed managers from manual tasks, enabling them to concentrate on coaching and quality improvements.

Increased Scalability: Provided consistent evaluations and scalable solutions, improving efficiency across all call center teams.