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Each month, I highlight one Key Performance Indicator (KPI) for service and support. I define the KPI, provide recent benchmarking data for the metric, and discuss key correlations and cause-and-effect relationships for the metric. The purpose of the column is to familiarize you with the KPIs that really matter to your organization and to provide you with actionable insight on how to leverage these KPIs to improve your performance!

This month, I depart from our usual format, and instead of discussing a single metric, I will introduce and discuss a number of metrics that are unique to chat.

The Chat Channel

If you are like most consumers, you have probably experienced a chat session. Perhaps you engaged in chat with an agent at your bank or insurance company to resolve a payment issue. Or you may have used chat to troubleshoot your new computer or a software application you installed.

Why chat? One reason is that some people simply prefer this channel for service and support. Chat is the channel of choice for a growing number of consumers and businesses, particularly among millennials. The second reason is economics. An effective chat channel can significantly reduce the cost per transaction versus a more traditional live voice support model. Because of this, chat has the potential to both improve customer satisfaction (by giving customers an alternative channel choice) and reduce the cost per ticket.

Costs are typically lower in the chat channel because chat agents can handle more than one chat session at a time. These are called concurrent sessions, and some agents are talented and skilled enough to handle as many as four concurrent chat sessions. When agents handle more than one session at a time, the cost per session is reduced accordingly.

Chat Metrics

Many chat metrics simply mirror their live agent counterparts. For example, customer satisfaction for chat is the same metric as customer satisfaction for the live voice channel. However, the values for the metrics in each channel are likely to be different—sometimes dramatically different. Customer satisfaction in the traditional voice channel might be 80%, while customer satisfaction for chat might be 90%, or vice versa.

The metrics listed below are common to both the chat and voice channels. Some names might vary slightly—for example, speed of answer in the voice channel becomes speed of response in the chat channel, and call abandonment rate becomes chat abandonment rate in the chat channel.

Cost Metrics

  • Cost per Chat Session
  • Cost per Minute of Chat Handle Time

Productivity Metrics

  • Chats per Chat Agent per Month
  • Chat Agent Utilization
  • Ratio of Chat Agents to Total Headcount

Service Level Metrics

  • Average Speed of Response
  • Chat Abandonment Rate
  • Percent of Chats Answered in 30 Seconds

Quality Metrics

  • Customer Satisfaction
  • Chat First Contact Resolution Rate
  • Chat Quality

Agent Metrics

  • Annual Chat Agent Turnover
  • Daily Chat Agent Absenteeism
  • Chat Agent Occupancy
  • New Chat Agent Training Hours
  • Annual Chat Agent Training Hours
  • Chat Agent Tenure
  • Chat Agent Job Satisfaction

Contact Handling Metrics

  • Average Chat Handle Time

There is another category of metrics unique to chat. These include the following:

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Jeffrey Rumburg

Jeff Rumburg is a co-founder and Managing Partner of MetricNet, where he is responsible for global strategy, product development, and financial operations for the company. As a leading expert in benchmarking and re-engineering, Mr. Rumburg authored a best selling book on benchmarking, and has been retained as a benchmarking expert by such well known companies as American Express, Hewlett-Packard, General Motors, IBM, and Sony. Mr. Rumburg was honored in 2014 by receiving the Ron Muns Lifetime Achievement Award for his contributions to the IT Service and Support industry. Prior to co-founding MetricNet, Mr. Rumburg was president and founder of The Verity Group, an international management consulting firm specializing in IT benchmarking. While at Verity, Mr. Rumburg launched a number of syndicated benchmarking services that provided low cost benchmarks to more than 1,000 corporations worldwide. Mr. Rumburg has also held a number of executive positions at META Group, and Gartner. As a vice president at Gartner, Mr. Rumburg led a project team that reengineered Gartner’s global benchmarking product suite. And as vice president at META Group, Mr. Rumburg’s career was focused on business and product development for IT benchmarking. Mr. Rumburg’s education includes an M.B.A. from the Harvard Business School, an M.S. magna cum laude in Operations Research from Stanford University, and a B.S. magna cum laude in Mechanical Engineering. He is author of A Hands-On Guide to Competitive Benchmarking: The Path to Continuous Quality and Productivity Improvement, and has taught graduate-level engineering and business courses.

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