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:
- Implementation of a speech analytics program with machine learning and predictive analytics in order to increase efficiency and sales.
- 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.
- 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.