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Submitted by ma.santos on Mon, 06/28/2021 - 10:02
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A brilliant bank, providing credit card and loan services, approached Transcom with the objective to maximize loans with new and existing customers.

 

The challenge:

 

Due to the use of a traditional monitoring method, the client couldn’t efficiently track the quality of customer service. A very small number of customer contacts were scored, and feedback was provided only for a sample of calls within a few days after a call occurred. This made it difficult for agents to link feedback to specific customer interactions, and therefore analyze behaviors. Additionally, the client was unable to identify system-wide deficiencies, such as reasons for silent time.

 

Our solution:

 

  1. Implementation of a speech analytics program with machine learning and predictive analytics in order to increase efficiency and sales.
  2. The recording and analysis of 100% of interactions allow for the provision of immediate feedback to agents on what they do well, and what they could improve.
  3. This also enhances coaching and supervision processes by giving access to greater sample sizes for use in training and development.


 

The outcome:

 

  • By implementing the speech analytics program, the client saw an increase in sales by 20% and a reduction in AHT by 10%, resulting in cost savings and additional revenue.
  • The program allowed for improvements in the training and development of agents for future customer interactions.
  • By providing system-wide views on process, knowledge gaps could be identified and addressed to increase customer experience.

 

The result:

 

  • 20% increase in sales in a 4 month period.
  • 10% Average Holding Time reduction in the same period.
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