I spent most of last week at the 2013 AMSRS Conference
Lovely city and a great
conference. There were over 500 attendees and around 40 presentations along
with some interesting panels, two of which I had the opportunity to sit on.
The content was all that you would expect in
an MR conference these days, a good reminder that we are a global industry in
which pretty much everyone is working to solve the same set of problems.
The presentations I heard were all well done,
better than what I sometimes see at other conferences.
Unfortunately, I don’t have any breakthroughs
to report but it was a nice opportunity to think about the state of play in MR.
One nice feature of this conference was the significant
representation from the public sector, some clients but mostly companies that
do what we in the US might call social policy or government research. By and large, MR and government researchers
go their own separate ways here but in Australia and to a lesser extent in
Europe that’s not always the case. I
have always felt that both MR and government research in the US would benefit
from closer collaboration, but I don’t expect to see that happen any time soon.
There also was a significant contingent of client-side
researchers, more than one usually sees in the US save for the artificial
environment created by TMRE. And, as
conference co-chair Ray Poynter wryly observed, they weren’t hiding their name
badges, suggesting that they felt more like colleagues than targets of
There were five plenary sessions, mostly featuring the usual
suspects (like me). Our job was to be
thought provoking and I think we managed.
I’ll leave it at that.
To accommodate that many papers there had to be some
parallel sessions, and I attended three of them. Some observations:
I’m not sure that MR has yet tuned into big data
in a meaningful way. It’s more than
loyalty card data or social media data.
It seems to me that it’s more about combining different kinds of data
from lots of different sources, and more about the techniques of data mining
and machine learning than it is about sampling, inferential statistics, and
hypothesis testing. We continue to view
big data through the lens of our current paradigm, and I don’t think that’s
where the big data movement is going.
Mobile seems frozen in place. Everyone continues to talk about
“in-the-moment” and geolocation but I don’t see mobile as being really there
yet in a meaningful way. The
unintentional mobile respondent issue is where the action is right now and I’m
surprised it’s not getting more attention.
Long surveys designed for computer administration are a serious problem
and the industry ought to be running as fast as it can to solve those two
problems now. But I don’t get a sense of
Finally there is behavioral economics,
neuroscience, neuromarketing, behavioral science – whatever name you put to
it. MR has been struggling to figure out
what to do with it beyond wiring people up in qual settings or grabbing images
of faces and making inferences that some might say go beyond the current
science. There is a lot of experimenting
going on, which is a good thing, but I think we are still in the learning
The conference closed with one of those personally inspiring
talks from an author of what we used to call “self-help” books (maybe we still
do) that have become standard fare at MR conferences these days. Nigel Marsh
has written Fat, Forty, and Fired and
Overworked and Underlaid. He was typically personable and funny. As always happens to me in these situations I
was nearly overcome with envy of his command of the stage. But I never feel especially inspired to go
out and take command of my life like I am supposed to do. Maybe it’s an age thing.