Say you were asked to improve the UX of an already existing feature, and you wanted to provide some kind of proof and metrics how is this approach.
- A 'talk out loud' user test (6 participants) giving them a key task to perform and taking notes of key issues and problems.
Using things like task completion rate and time on task isn't really going to provide you with any statistical confidence with a sample size of 6?
- Then perform something more quantitive on a much larger group (e.g. 60 participants) so rather than 'talk out loud' (which can result in a lot of video footage to go through) just give them a task to do and record task success rate and time on task, as well as something attitudinal like 'how easy or hard, did you find that task [1 - 5]'.
This is then your starting data.
Then design and prototype and iterate through designs.
For the final design create an advanced prototype and then repeat the same thing so 6 'talk out loud tests' followed by 60 tests where you're recording task completion rate, time on task and easy/hard rating.
At that point, assuming the metrics are good, you should have proven that what you designed is an improvement in UX before handing it over to developers.
Thoughts on that approach anyone? Any alternative approaches?