Improving Agent Performance

Problem: An insurance company wants to evaluate its all customers representatives’ performances to increase its competitive advantage in the market. Nevertheless, evaluating a large number of customer agents can indeed be a challenging task, especially when dealing with a significant volume of interactions.

Success scenario: To evaluate all agents, the analysts of the company decide to create Automatic Evaluation Forms with the help of Knovvu Analytics.

They started with Category Based questions. For instance, they chose the section name as “Service Quality/Excellent Customer Experience” and entered their questions, “Was the greeting done in an appropriate manner?”, “Did the agent interrupt the customer?”. They also decided on the scores that agents would receive if they answered "yes" or "no" in the section below the questions.

Then, they created Acoustic Parameter Based questions. Here, they selected the parameter type to ensure to catch the required results. For example, they selected “Agent Monotonicity Ratio” as their parameter to give 0, if agent monotonicity ratio is greater than 50 and selected 10 as the score, if agent monotonicity ratio is between 50 and 0.

Reason of the problem: Since the company has a significant amount of customer agents, the company has some doubts about the scale, consistency, quality control, data analysis, and time constraints when evaluating their agents.

• Scale: Managing and evaluating a huge number of customer agents requires significant resources, both in terms of time and personpower. The more agents there are, the more interactions need to be reviewed and assessed.
• Consistency: Ensuring consistent evaluation across a large number of agents can be demanding. Different evaluators might have varying criteria or interpretation, leading to inconsistencies in the evaluation process and results.
• Quality control: Maintaining quality control becomes more complex with a large number of agents. It can be challenging to monitor the performance of each agent, identify areas for improvement, and provide targeted feedback when dealing with a large workforce.
• Data analysis: Analyzing the data collected from interactions becomes more intricate when the volume is substantial. Extracting meaningful insights and identifying patterns or trends may require advanced analytics tools and techniques.
• Time constraints: Evaluating a significant number of customer agents can be time-consuming. It may take considerable effort to review interactions, provide feedback, and track improvements while simultaneously managing other responsibilities.

Result: Evaluation of all agents was ensured with the automatic evaluation forms. Since the system helps monitor the quality of customer-agent conversations, it identifies instances of non-compliance, errors, or missed opportunities, enabling the company to take corrective actions and improve service quality. Also, because Knovvu Analytics automated evaluation forms ensure a consistent and objective assessment across a large number of interactions, the company overcomes inconsistencies or biases that might arise from manual evaluations performed by different individuals.

Taking all these results into consideration, the company provided specially tailored training and coaching sessions for the agents. As a result, they not only became one of the top performers in their market but also achieved a 23% increase in call quality in relation to customer satisfaction.