April 7, 2015
OK, it is certainly a cliché and clearly suffers from an incomplete view of the world, but many contact center executives would still nod their heads in agreement with the statement, “You can’t manage what you can’t measure.” Contact centers generate a huge volume of data, and everyone from agents on the floor to CEOs in their corner offices would benefit from being presented with actionable analytics based on that data. However, turning that data consistently into actionable knowledge that is useful to improving performance remains challenging. The key questions for contact center professionals around this data are:
- What do you measure?
- How do you present the data from those measurements?
- What do you do with those measurements?
Our new report, Implement Effective Customer Service Metrics, tackles these questions and also presents dozens of common metrics broken down by audience and potential use case. Here are some highlights of our research findings in the report:
- Link to corporate KPIs. In order to ensure alignment with broader corporate goals, every customer service metric should be aligned to specific corporate KPIs. These are measures that your executive team uses to guide the ship of your company, and if you are not aligned to the corporate direction at the metrics level, it will become much harder to prove the value of your organization to the company. Your executives want to see a few key measures that track the outcomes and business results of customer service programs. Understand what those KPIs are and show that you support those measures.
- Balance explicit and inferred metrics. Several metrics today rely on simply asking customers or agents about their experiences. Customer effort, Net Promoter Scores (NPS), and basic customer satisfaction scores are typically collected in this manner. However, often these explicit measures do not give companies actionable information on the specific sources of friction that cause higher effort, or drive down satisfaction or NPS. To get a balanced point-of-view, you’ll also need to create metrics using systems data, essentially inferring measures such as customer effort.
- Remember that self-service metrics matter. For the first time, Forrester data now shows more consumers used Web self-service to resolve their service issues than picked up a phone for that purpose. Self-service clearly appeals to customers and means you need to apply the same rigor to measuring self-service as you do measuring agent-assisted service.