I think what you mean here is that you have already created personas
based on real research, and your "client" wants them validated.

I've had clients ask for that too. Often this is their first foray
into qualitative research, and they don't feel comfortable, and want
some quantitative comfort. I know of one company that spent 7 *months*
and lots and lots of time and money to "validate" their personas.
More time than it took to create them in the first place. Yikes.

Tamara Adlin includes several methods for validating personas in her
book, including showing the final personas to future research
participants or even the interviewees themselves and seeing if they
resonate with them.

Another method is to distill the personas into a few key traits,
behaviors or characteristics and use them alongside future research.
For example, is this usability research participant very
Danielle-like with some Molly tendencies, or is she more like Bill?
The risk to this is that people may not understand that if everyone
doesn't exactly and perfectly fit into one persona or the other, it
doesn't mean that the personas are invalid. However if this is used
effectively, the idea that personas are always being tested and
validated is a powerful one.

And of course you could use those key traits to create a survey,
analyze the findings, etc. etc.

BUT... if fundamentally you just have some folks who are
uncomfortable with qualitative research, you might start there. I
usually try to explain that there are many right answers, just like
there are many right ways to sort the change in your pocket, and
these aren't carved in stone so if later you discover (in any way:
traffic data, usability research, whatever) a gap or something
unexplained you can create a new persona or clarify an existing
persona if that's appropriate. I also try to emphasize that
quantitative data is great and very useful and we should keep doing
it, and this qualitative stuff fills a different need. Just as we
don't toss out qualitative data for not doing a good job going
deeply into users motivations, we shouldn't toss quantitative data
for being a small sample size (or whatever the beef is with it).
They're complimentary.

If you can't address that, if it is the fundamental issue, I wonder
if any amount of validation will be enough.

Good luck! I'd be interested to hear how this effort goes for you.


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Posted from the new ixda.org
http://www.ixda.org/discuss?post=47635


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