Call Center Analytics

Enhance Customer Service & Prevent Customer Dissatisfaction

Call center analytics is an umbrella term whose overall purpose is to enhance the customer service experience and therefore increase customer satisfaction. It does not take a marketing expert to understand that businesses that offer services or sell products must prioritize these two factors in order to run their business. With the competitive pressure businesses face today, why not use data analytics to understand what customers are looking for in a product and become a leading, top-quality seller?

There are six subsets of call center analytics, otherwise known as call center analytics software, used by customers and salespeople alike:

  • Speech Analytics
  • Text Analytics
  • Desktop Analytics
  • Cross-Channel Analytics
  • Self-Service Analytics
  • Predictive Analytics

Speech, text and self-service analytics are customer-oriented, meaning that the tools analyze voice and written data that customers provide, which help businesses discover what customers have issues with or absolutely love. These data allow businesses to learn more about their customers in general, and ultimately provide insight as to how their products could be improved to suit their needs.

On the other hand, desktop and cross-channel analytics are used by businesses to ensure that customer support workers and platforms are functioning at their very best to properly and efficiently handle customer inquiries.

Finally, predictive analytics is the most complex, yet impressive of the subsets, as these tools find patterns in the products that customers purchase and can therefore predict what the customer may want to purchase next.

Sales are obviously important when it comes down to business, but if your customer service is lacking and customers are not satisfied with what they purchase and cannot negotiate with the seller to correct the issue, sales and profitability will decrease significantly. Therefore, call center analytics is just as important because:

  • Prioritize customers’ feelings and attitudes (good or bad) about a product or service
  • Decrease future issues that customers could encounter with a product
  • Prevent product issues by analyzing customer complaints and suggestions for
  • improvement
  • Prevent future issues with products, thus increasing customer satisfaction
  • Ensure customer service representatives are performing at their very best, and if not, taking the proper measures to do so