In today's business environment, customer satisfaction has become a critical aspect of success. With the rise of social media and online reviews, customer satisfaction can make or break a business. One of the most effective ways to measure customer satisfaction is through contact center data analytics. In this blog post, we will explore how businesses can efficiently measure and analyze customer satisfaction using contact center data.

Contact centers are the primary touchpoints for customers to connect with businesses. They can also be used to collect feedback from customers who interact with the contact center. This feedback can be analyzed to identify trends, areas for improvement, and insights into customer behavior. Most contact center operating businesses are required to record their interactions for compliance purposes, meaning that they already are sitting on a goldmine of information. Analyzing this (ideally with a contact center software solution that is able to record, analyze and securely store customer data) can save you time and effort, regarding both data management and data processing.

Contact center data is constantly and automatically collected, but as is this data dump can not be considered as value for your business. What turns it into added value is analyzing it according to your business strategy, focuses and goals. Depending on what your business focuses on, several approaches to data analytics methods can be considered. To help you navigate through endless ideas and possible solutions, we summarized the key factors that are useful for all contact centers regardless of industry. To measure customer satisfaction using contact center data analytics, businesses need to consider the following steps:

1. Define Key Performance Indicators (KPIs)

The first step in measuring customer satisfaction is to identify the KPIs that will be used to measure it. Common KPIs for measuring customer satisfaction in a contact center include call abandonment rate, average handle time (AHT), first-call resolution (FCR) rate, and customer satisfaction scores.

2. Collect Customer Feedback

Contact centers can collect customer feedback in a variety of ways, such as through post-call surveys, IVR surveys, and via QA forms. The feedback collected should be timely, relevant, and actionable.

3. Analyze the Data

Once the feedback is collected, it needs to be analyzed to identify trends and insights. Contact center analytics software can be used to analyze the data, identify patterns, and provide real-time feedback to agents.

Contact center software solutions use various techniques to analyze calls and determine customer satisfaction. Some of these techniques include:

  • Sentiment analysis (SA). This technique uses natural language processing (NLP) to analyze the tone, language, and context of the customer's voice to assess their emotional state. The software then categorizes the sentiment as positive, negative, or neutral.
  • Speech analytics. This technique uses machine learning algorithms to analyze the content of the conversation, such as keywords, phrases, and topics. This analysis can provide insights into the customer's needs, concerns, and satisfaction levels.
  • Customer feedback surveys. Some contact center software solutions incorporate post-call surveys to gather feedback from customers. This feedback is used to gauge customer satisfaction levels and identify areas for improvement.
  • Quality monitoring. Contact center software solutions often include quality monitoring features that allow supervisors to listen to calls and evaluate the customer service representative's performance. These evaluations can be used to identify training needs and improve customer satisfaction levels.

By combining these techniques, contact center software solutions can provide a comprehensive analysis of customer satisfaction levels and identify areas for improvement in customer service.

4. Take Action

The insights gained from analyzing the data can be used to improve the customer experience. For example, if customers are complaining about long delay times, the contact center can adjust staffing levels accordingly. If customers are complaining about the quality of service, agents can be provided with additional training. Also, fine tuning the right marketing approach to reach your customers perfects your product to be relevant on the market.

5. Continuously Monitor and Improve

Measuring customer satisfaction is an ongoing process. Businesses need to continuously monitor customer feedback, identify areas for improvement, and take action to improve the customer experience.


Contact center data analytics can provide businesses with valuable insights into customer satisfaction. By identifying areas for improvement and taking action to level-up the customer experience, businesses can increase customer loyalty, retention, and ultimately drive growth and profitability. It is well-worth investing into a solution that is able to provide UC data management and enhanced analytic capabilities to ease up on your agents.