Analyzing Contact Center Performance Using Insights

Life Sciences
case study

Business Impacts

Improved Customer Support

Contact Center Insights for COVID-19

Reduced Average Wait Time

Customer Key Facts

  • Location : North America
  • Industry : Healthcare

Problem Context

During the COVID-19 global pandemic, many health care providers faced various challenges in handling high volumes in their contact centers. Building custom dashboards on Looker provides them with reports and valuable insights that help to manage customer queries efficiently, while also reducing average wait time (AWT).



  • Obtaining contact center data in .CSV format
  • Pulling data into Google’s BigQuery to process and transform the raw files
  • Bringing data to Looker from BigQuery and visualizing multiple metrics
  • Collecting the data from open sources about common queries observed among the customers, including medical insurance data queries
  • Understanding and building the KPIs that best fit the scenario of COVID-19 for a contact center

Technologies Used

Cloud Storage

Cloud Storage

Google's BigQuery

Google's BigQuery



Analyzing Key Statistics of Contact Centers & Developing Operational Insights for Process Improvement


Quantiphi built dashboards on Looker that analyze performance management, prioritize and sequence customer support, monitor work-from-home workforce productivity, and highlight the intents of the maximum customers for efficient training. In addition, the dashboards can provide answers to multiple COVID-19 related queries, reducing average wait times for customers.


  • Built custom dashboards that could keep tabs on all metrics while delivering the highest quality of service to customers
  • Improves performance by leveraging the insights for strategic decision-making
  • Generates recommendations to improve customer satisfaction and the response rate

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