Introduction - Measuring the User Experience: Collecting, Analyzing, and Presenting Usability Metrics - page 14

asking the user. In our years of UX research, we have yet to come across a busi-
ness or user goal that was not measurable in some way. You may have to be cre-
ative in how you collect the data, but it's always possible.
Myth 9: Metrics are not Understood or Appreciated by
Management
Although some managers view user experience research as providing only qualita-
tive feedback about a design or product, most managers see the value of measure-
ment. It has been our experience that UX metrics are not only understood but very
much appreciated by upper-level management. They can relate to metrics. Metrics
provide credibility to the team, the product, and the design process. Metrics can be
used to calculate ROI. Most managers love metrics, and UX metrics are one type
of metric they will embrace quickly. UX metrics can also be real attention grabbers
with management. It's one thing to say there's a problem with the online checkout
process,butit'sanentirelydifferentthingtosaythat52%ofusersareunableto
purchase a product online successfully once they've found it.
Myth 10: It's Difficult to Collect Reliable Data with a Small
Sample Size
A widely held belief is that a large sample size is required to collect any reliable
UX metrics. Many people assume that you need at least 30 participants to even
start looking at UX data. Although having a larger sample size certainly helps
increasetheconfidencelevel,smallersamplesizesof8or10participantscan
still be meaningful. We will show you how to calculate a confidence interval
that takes into account the sample size when making any conclusion. Also, we
will show you how to determine the sample size you need to identify usability
issues. Most of the examples in this topic are based on fairly small sample sizes
(fewerthan20participants).Sonotonlyaremetricspossibletoanalyzewith
fairly small sample sizes, doing so is quite common!