SPEECH ANALYTICS CASE STUDY

THIS GLOBAL BANK INCREASES CUSTOMER SATISFACTION AT ITS CONTACT CENTER BY DOUBLE DIGITS

THE CUSTOMER

ING Turkey, a subsidiary of ING Group, one of the largest financial institutions globally, was targeting to effectively manage its call center operations with more than 500 agents.

THE PROBLEM

Trying to monitor, analyze, and score all contact center interactions was not possible because of the vast amount of customer calls. ING was searching for a solution to evaluate 100% of all interactions and effectively analyze them for actionable results to increase agent performance.

THE SOLUTION

Using Sestek’s Speech Analytics, ING achieved to gained valuable insights to improve both customer experience and agent performance.

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Net Promoter Score
increased
by 10%

quote-leftCall center interactions contain critical data about customer satisfaction and agent performance. Sestek Speech Analytics provides us with crucial insights about agent performance and customer satisfaction. This helps us greatly to improve customer experience.

HEAD OF CONTACT CENTER COMPLAINT MANAGEMENT AND BRANCH OPERATIONS MANAGEMENT
ING

The Insight

  • Using speech analytics, ING discovered that agents with seniority over 36 months exhibited higher anger ratios, longer talk times, and lower wait times.
  • The analysis pinpointed an aggressive and dominant tone of speech, resulting in poorer customer experience.
  • ING than implemented a training program for senior agents and helped increase the overall performance of this group.

The Results

10% INCREASE
IN NET PROMOTER
SCORE
15% INCREASE
IN SALES QUANTITY
SCORE
3% DECREASE
OVERALL SILENCE RATE
DURING CALLS
ing-logo-case-study

As a subsidiary of ING Group, ING Turkey is one of the leading banks, operates with more than 4000 employees and 200+ branches in Turkey.

ABOUT SPEECH ANALYTICS

This technology offers an effective way to leverage customer interaction data. This solution transcribes all recorded customer calls to the call center, then analyzes the interactions using various technologies like emotion detection, trend analysis, and more. Through analyzing these transcriptions, brands discover actionable insights for improving customer experience and the performance of call center agents.