Often agent performance is measured quantitatively in terms of the number of calls they take per hour, average call time, average processing time, and so on. However, it is important to evaluate the quality of calls – conversations really – in order to identify areas that may need improvement by the agent in terms of quality of customer-handling, as well as gauge the experience from the customer’s perspective in terms of what they’re looking for, are the happy before they even engage with your agent, are they calling in to complain, and have they reached the appropriate department.  This data cannot necessarily be obtained quantitatively, without listening to the nature and substance of the conversation.

The term “agent performance” comprises so much more than just the immediate conversation they have with customers.  Additional performance metrics that often agents are assessed on include:

  • Average call wait time
  • Call drop rates
  • Amount of time spent on calls
  • Average call duration
  • Speed of service
  • Hold times
  • Number of calls handled per hour

These are in addition to the four main factors mentioned earlier, which include:

  • Attitude
  • Product/service knowledge
  • Understanding of the customer’s issue
  • First call resolution

It’s one thing knowing that the conversations agents are having are the organization’s most valuable source of customer information, and it is another enormous undertaking to extract that information, analyze it, and take actions based on the findings.

To make the compilation and analysis of this vast amount of data more manageable, it has become essential to use the right technology that will help accomplish a huge portion of this undertaking for a company automatically, and nearly instantaneously.  Companies need to consider whether that data could be more efficiently aggregated and analyzed, and whether the use of speech analytics technologies can expedite turning that data into proactive actions.  Implementing a solution should revolve around key management objectives and goals the executive team wishes to achieve in the near future.  The benefit of a cloud-based audio mining solution is its flexibility and scalability.  Without the hindrance of equipment and servers to maintain, expanding a solution to mine increasing call volumes, based on growing needs and additional applications of the solution, it is simple and quick to make adjustments to a cloud-based solution to increase call traffic that is handled and recorded by a speech analytics provider.