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UX Measurement #2
So, how can we measure UX?
It’s less straightforward than one might think.

This is the second in a series of articles on user experience measurement:
- Conversion rate & average order value are not UX metrics
- ☞ So, how can we measure UX?
- Seven heuristics for identifying proper UX instruments and metrics
The precise, quantitative measurement of user experience (UX) based on one or more metrics is invaluable for design, research, and product teams in assessing the impact of UX designs and identifying opportunities. Yet these teams often employ supposed UX metrics like conversion rate (CR) and average order value (AOV), which can’t provide that measurement [1]. In fact, I believe this can be extended to an even more general statement: In themselves, none of the metrics that are usually readily and easily available from Web analytics data can reliably measure UX. I understand that this is frustrating news to many, since resources are always limited, attention spans short, and Web analytics so very, very convenient.
Whenever I discuss this, I encounter objections like, “But we have to do something,” or “It’s easy to just state what one shouldn’t do, but that doesn’t help much.” And while it’s a perfectly fine start to…