- Many teams struggle to find the time for user testing,
especially if they're under pressure to innovate quickly
to meet rapidly changing user needs.
Our standard advice is to expedite the research process
by testing early prototypes with small groups of users.
But if you're really in a crunch,
there are a few expert level techniques you can add
to speed things up even more.
Now a warning, you need to proceed with caution
because these are advanced techniques
that require experience and good judgment to use effectively
and make sure you don't cause a problem worse
than the one you're trying to solve.
The first method is RITE testing,
which stands for rapid iterative testing and evaluation.
Now this is a method in which you try to get
to a workable solution as quickly as possible
by fixing every problem as soon as it is discovered.
You might literally change your prototype
after each user testing session.
A research team at Microsoft used this method,
found it to be very effective
and coined the acronym RITE to describe this process.
For this to work, you must have the ability
to edit your prototype almost instantly.
You also need to be in the right context.
If you have a large set of stakeholders
with diverse opinions who are unlikely
to come to quick agreement
or stakeholders whose input is essential,
but who can't or won't actively participate
in the research process, this is not the right method,
but for a team of one or small tight-knit teams
that can sync up after each session
to agree on a path forward,
this technique allows you to test and explore
many directions in a short amount of time,
which lets you be more confident in the final choice.
The second expert level method you can use
is competitive testing of multiple design solutions
using a within subjects design.
Which means, you're gonna create multiple prototypes
and show those to participants,
and every participant will see
both versions of the solution.
I found this technique effective
for eliciting specific feedback,
comparing very granular elements of a design,
but it comes with a big grain of salt
or maybe even a whole shaker of salt.
You risk contaminating people's opinions of a design
with what they observed in the previous version.
You can minimize this effect by alternating
the order in which you show people the designs.
So your first participant would see
the A version and then the B version,
the next person who comes in,
you'll start with your B version and then only show them
the A version afterwards.
By alternating the order,
you're less likely to have a bias
that persists across multiple people.
The other risk is that upon seeing two different versions,
your participant may go into designer mode.
That is, they start giving you advice about
what they think would be a good solution
instead of actually trying to use the design.
Now, sometimes you might get a good idea out of this,
but what we're really looking for with this method
is that moment when somebody understands something
they previously missed and mentions
what specifically helped them understand.
Or if they call out something specific
that they're missing the second time around
and they realize how important it was
to their first experience.
For example, imagine you have a big table of data
and in the first prototype,
your user doesn't understand what that table is about
and doesn't notice the legend at the bottom explaining it.
Perhaps in the second prototype,
you've put the legend at the top of the table
and now you get to witness a Eureka moment
when that same user encounters the table
and suddenly they understand exactly what it's about.
And they often give you a great quote
about how helpful that legend was.
A within subjects design means,
is the exact same person on both designs.
So it's very sensitive to smaller differences
and how these details affect people's success.
If you were testing with two separate groups of users,
your comparison of how the table and the legend
should be laid out would be a lot less direct.
Maybe one of your groups of users has people
who don't even go to that page
or people who already understand
what that table is about
and don't even need a legend to explain it.
A within subject study, lets you see an alternate reality.
If the exact same person had seen a different solution,
would it have solved that person's problem?
Of course, both of these methods,
right and within subjects testing have limitations
and they're not appropriate in all cases
or even in most cases.
But when they fit your situation,
these methods can dramatically accelerate
the number of options you're able to test
and especially enable you to rule out
any effective solutions,
allowing you to zero in that much faster
on the solutions that do work.