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How to Cut Call Center Costs with Natural Language Generation

Call centers are often quietly called “cost centers” in companies, and it’s no wonder. With high rates of employee turnover along with the high demand for accuracy, call centers are some of the most costly ways to serve customers. However, call centers are vital to a successful business. Their role is to interact with the customer directly, addressing concerns and striving for satisfaction. Solving the customer’s problem quickly in a professional manner, and with the right advice, can make or break companies customer experience efforts. But how can you cut costs in call centers while at the same time increasing the quality of customer interactions?

Enedis, one of the largest European electricity distributors, offers us a roadmap to follow. They run several all centers in Europe to serve customers and help them address problems. A common problem and one which their call centers manage often is electrical outages. Call centers that manage disruption in supply play a unique role within Enedis and face unique time constraints along with security implications. The call centers require employees to deliver high-quality service while ensuring safety, often with customers in high-stress situations like a major storm with no power and fallen power lines.

 

The Problem: High Call Center Costs

When it came to training, there were two problems that Enedis faced. First of all, high turnover (25%) a problem which plagues call centers across the globe. In fact, industry turnover rates hover around 30%-45%. So, continually training new employees was a constant concern and cost.

The second problem they faced was having to bring temporary employees to the call center. During a high influx of calls, for example a major storm, they would bring employees from other departments to answer phones. These employees might not be up to speed and there was very little time to train them in these high stakes situations.

 

The Solution: Natural Language Generation

Using Natural Language Generation (NLG), Enedis was able to build an application in order to provide call center agents with advice and guidance. Now call center employees are guided through calls with a checklist to ensure they’re asking the right questions as well as collecting all the required information.

In addition, warnings prompt the employee to communicate any critical information regarding a particular situation that could be dangerous or a security issue. At the end of the call, all the collected answers and a written description could be sent to the appropriate department, ensuring a fast transfer of information.

 

Looking at the impact of NLG at Enedis, the results were very clear:  

1. A better employee experience:

  • Employees are more technically confident and can focus on providing quality service to the customer.
  • With more autonomy, new employees can be operational much faster (in 4 days vs several weeks before).
  • Now employees can deliver prompt quality support while being in compliance.

2. A better customer experience:

  • The employee looks professional to the customer because they can provide the right advice and accurate information.
  • The customer feels confident in the answers they receive.

Overall, there is a better balance between employee training, customer satisfaction, and costs and an increase in customer satisfaction – all while decreasing costs for the company.

 

“The power of Yseop’s software has enabled us to optimize our calls and reduce the costs of operations in the field through the creation of a smart toolbox, capable of guiding operators in solving the problem.” - Stéphane Colomas, Head of Agency Call Center Troubleshooting Electricity – ENEDIS

 

Thanks to NLG, Enedis achieves the balance between helping employees, providing a great customer experience, and reducing costs. Getting this balance right further strengthens customer relationships and reinforces Enedis’ ability to deliver quality customer service, even when facing unusual situations, like storm, more easily.

If you’re interested in learning more about how Natural Language Generation can fit with your business, download this white paper. Get tips on how to choose your first use case as well as examples of other successful use cases.