Keep track of your Call Center Agents' Performance and your Customer Satisfaction
Use this template when you want to keep track of your call center agents' performance and your customer satisfaction. The data you receive from the survey can help you gain valuable insights and be used to optimise your call center's performance.
When trying to create a new agent, simply add this template to your account. Then you can make changes to customise it based on your business needs.
We start with a Speak node introducing the company to the caller. Using the Speak node we don't expect any input from the caller in this node.
Continue with adding a Collect Input node with the first identification prompt. E.g. "May I ask you a few questions about your experience today?"
Now we need to utilize the confirmation value we will receive. We want the agent to give out a different response depending on whether the caller says yes or no - we are creating conditions. Therefore, we are adding a Conditions node in order to classify the answer of the caller.
After receiving the confirmation of the caller to go ahead with the questions, we are adding another Collect Input node with another survey question. E.g. "Thank you. It will only take a few moments. Firstly, were we able to resolve your request?" or "Please rate the experience from 1 to 5. With 1 being the lowest and 5 being the highest score."
You can add as many prompts as possible. Simply keep adding Collect Input nodes.
Step 4 - Use the Survey Data
To utilize the values we collected in the survey, we need to add the Webhook node that sends them to a third-party service of your choice using a customizable API request.
To end the survey, we are adding a Speak node with a response saying e.g. "Thank you very much for your time. Have a nice day!" and the action node End Call terminating the conversation.
You will notice that all No Input or Missed Tabs are still connected to the following node. In a post-call survey, we don't want to escalate the call to a live representative or prolong the conversation for the customer unnecessarily.