Increasing Call Center Efficiency with Speech Analytics

Increasing Call Center Efficiency with Speech Analytics

Increasing Call Center Efficiency with Speech Analytics: A Case Study in the Banking Industry

Increased competition in the financial services industry is forcing banks to work even harder to gain a competitive advantage. This requires banks to adopt a customer-centric approach.

Today’s customers have high expectations. Being able to reach organizations from any channel they like increases their expectations of immediate and satisfactory responses. Customers are ready to switch brands whenever they are not happy with the service they receive.

Like many other organizations, banks feel this pressure. They are looking for ways to increase customer satisfaction, service quality, and business efficiency. Since improvement isn’t possible without accurate measurement and evaluation, the need for analytics has become more urgent.

Why Do Banks Need Speech Analytics?

Call centers are one of the main customer contact points for banks. Call center interactions include invaluable insights about a variety of elements: service quality, customer perception, customer experience, agent performance, call center efficiency, and so on.

Speech Analytics helps to reveal these insights by applying several data mining methods to recorded calls. By listening to and analyzing 100% of these calls, Speech Analytics allows banks to take advantage of enormous potential in identifying call drivers and acting accordingly.

Banks can use Speech Analytics technology in:

  • Call center monitoring and reporting
  • Agent performance analysis and training
  • Customer satisfaction and service quality analysis
  • Automation of quality monitoring processes
  • Crisis management
  • Competition, market, and campaign feedback analysis
  • Identification of cross-sales opportunities

Case Study: Speech Analytics for ING Bank

ING Bank is an excellent example of the successful use of Speech Analytics technology. Once Sestek Speech Analytics was implemented in its call center, ING Bank observed increases in call center efficiency, sales, and agent morale. The details of this successful project are presented below.

Increasing Call Center Efficiency, Sales, and Morale with Speech Analytics

Before Sestek Speech Analytics

To increase call center efficiency, ING Bank was aiming to obtain insights into customer experience, agent performance, sales potential, and service quality. These goals required in-depth analyses of recorded call center interactions. Because of its high call volume, ING Bank needed an automated means of evaluating calls across several metrics. With its ability to automatically track several call data metrics, Sestek Speech Analytics was the ideal solution, so ING Bank decided to implement this technology in its call center.

The Implementation of Sestek Speech Analytics

After ING Bank implemented Sestek Speech Analytics in its call center, the software automatically transcribed all recorded calls into text. Several data mining methods, including textual and emotional analyses, were applied. Thanks to this comprehensive evaluation, ING Bank uncovered issues that required improvement. This enabled the bank to take the necessary actions to improve call center efficiency.

After Sestek Speech Analytics

With the implementation of Sestek Speech Analytics, ING Bank observed an increase in agent performance and sales quality. In addition, telecom costs decreased thanks to shorter calls.

Boosting Efficiency with Lower Silence Ratios

After the implementation of Sestek Speech Analytics, ING Bank started to analyze agent performance with several metrics, including silence ratios, speaking speed, and interruption rate. The bank thus did not limit its performance evaluation to conventional metrics like service level and after call work. Using the software enabled the following:

  • Silence ratio was evaluated by using agents’ seniority and call center location as baselines.
  • When a call’s silence ratio went above a defined threshold, it was reported with seniority and location matches.
  • Team leaders received these reports daily via email and then provided feedback to the identified agents.

Overall, reports showed an improvement in silence ratios and incorrect operation rates. Silence rates decreased by 3%. This also provided a cost advantage by shortening average call duration.

An Increase in Customer Satisfaction and Sales

Before implementing Sestek Speech Analytics, ING Bank manually evaluated its sales calls. This tedious process was limiting its ability to properly evaluate, and important sales-related data were left unexplored. The bank was planning to automate the sales call evaluation process to increase potential sales. With the implementation of Sestek Speech Analytics, all sales data and sales scenarios are now analyzed:

  • The full contents of sales calls were integrated into automatic evaluation forms, allowing for simple evaluation reports on the performance and sales quality scores of agents.
  • The sales evaluation process was automated, enabling the measurement of the quality of all sales calls.
  • Regularly scheduled analyses enable ING to determine necessary actions in terms of higher call quality and sales potential.

By identifying opportunities for improvement and acting on them with ease, ING Bank recorded a 15% increase in sales quality scores.

Objective Performance Evaluation

ING Bank wanted to evaluate all calls using a comprehensive approach and measure the impact of employee seniority and working time on productivity. To achieve these goals, they integrated all survey results, sales figures, customer information, and organizational data into Sestek Speech Analytics and analyzed them with a 360-degree approach.

  • ING analyzed employee performance monthly, using metrics like seniority, sales efficiency, net promoter score, shift order, and silence ratio.
  • Different queries were generated based on team leader, call center location, and hourly shifts (between 09:00 and 24:00); these queries were then analyzed together with the sales and net promoter score data. As a result, ING discovered that:
    • Agents with more than 24 to 36 months of seniority had higher anger ratios, longer talk times, and lower wait times.
    • Increases in talk times and interruption rates decreased net promoter scores by 4–5%.
    • An aggressive and dominant speech tone was effective.

ING Bank used these data from Sestek Speech Analytics to make several changes to increase agent performance and morale. Consequently, net promoter score increased by 10%.

Learn more

To read the full ING Bank Speech Analytics Case Study, click here. To learn more about Sestek Speech Analytics, visit our product page.

Author Hilal Bakanay

Senior Marketing Specialist, Sestek https://www.linkedin.com/in/hilalbakanay/

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