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Designing Metrics for CX

7 helpful tips when creating metrics for customer experience (CX).

  • What would be helpful and relevant?

    Consider the impact of sharing this to the public. How would someone use this information in their everyday lives? Community engagement can be a powerful medium to explore these unmet needs.

  • Designing Metrics

    We encourage those who create metrics for the public to approach metrics themselves as a design problem. Who are these metrics for? What are you trying to accomplish in sharing them? What situation might be the audience use these metrics in? Frame your metrics work at the outset with strategy and return to these questions throughout.

  • Keep it plain and simple

    The language surrounding government metrics can often be surprisingly dense and filled with bureaucratic jargon. Worse, metrics and acronyms may go wholly undefined, leaving them meaningless to anyone without inside knowledge. If you are sharing metrics with the public, you should give them the context that they need to understand what you are sharing. At times, this may mean repeating simple things about what your agency is and does, in plain language. This is not to be underestimated – we were surprised by just how much work it took to describe what the metrics meant in simple terms, and recognize we still have room to improve.

  • Keep it accessible

    Make sure you what you create is accessible, by finding and partnering with your accessibility experts. It can be easy to over-rely on color to convey meaning in metrics, rendering them unusable with colorblindness. Consider the experience of a user who uses screen readers. Consider the experience of a blind or low-vision reader. Reduce visual noise and overwhelm – if you are creating visuals, consider what you want to highlight as your “signal” and make that clear.

  • Test your concept with users

    Individual design decisions may have larger impacts when it comes to communication and representation of data. Let’s look at the challenge of showing “deltas,” the difference between two numbers. In the case of metrics, this is the difference between your target and your actual. While this might seem like a small detail, its (mis)interpretation could matter greatly to an organization. Other examples include how to represent change over time, or whether to represent change as a percentage. Each of these design decisions can be prototyped and tested to minimize the risk of misinterpretation.

  • Consider representation and legibility

    Like any other aspect of customer experience, metrics can be mocked up, prototyped, tested and refined with user feedback. Before launching your dashboard or report, consider usability testing potential users. What do they think your metrics are trying to convey? Does their understanding match up with your intention? You can surface problems of interpretation in this way, many of which might be solved with minor changes.

  • Anticipate gaps

    The data you seek may not be there or may not be the data that you expect. Work with performance analysts and data scientists to help you make sense of messy data.

Last Updated: 06/13/2024
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