mcn 2011 beyond likes and hits
DESCRIPTION
Pairing technology and evaluation is crucial to ensuring that we infuse the visitor voice into our work. While a lot of attention is being paid to existing analytics and metrics online to help us better understand our virtual visitors, what do we really learn from those tools? How can we put them to use to help us dig deeper, see more clearly, and truly progress our work with a visitor focus? What other methods might help us learn more, in real time and over time, about visitors', audiences', and communities' habits, preferences, interests, and behaviors-- on and offline? This session will make a strong case for partnership and alliance between the tech side of culturals-- be it web, digital media, mobile, social media, etc.-- and the audience research and evaluation side. Through case studies and examples, this session will demonstrate mistakes made (and lessons learned) with audiences which could have been prevented if the two camps had teamed earlier and with a unified vision and strategy. In turn, successful examples of partnership will be shared. Additionally, regardless of the size and shape of your institution, there are simple strategies-- even with limited time, money, and resources-- to leverage visitor studies, audience research, consumer trends, and your own visitors' voices in your work. This session will highlight several key ways to ensure your work is not just audience focussed, but audience informed. Presented 11/18/2011 at the Museum Computer Network conference in AtlantaTRANSCRIPT
Beyond Likes
and Hits
Guerilla-Style Evaluation
and Digging Deeper
Into Data
I’m Kate, but you can
call me Kathleen
Some stuff I like:
What I don’t like:
Insight into our
visitors, audiences,
and communities
lives in a lot
of places…
SilosVisitor Studies
and Evaluation
Online
Analytics
Site Search
DataLogs from
Social Media
Admissions/
Ticket Sales
Fragmentation
Differentiation
Synthesis
WhatWhy
Organization’s Goals
Users’ Goals
Exploring the world we don’t
Measuring the world we know
Awesome table
of glaring
overgeneralizations(Thanks, Louis Rosenfeld!)
What they analyze
What methods they
employ
What they’re trying to
achieve
How they use data
What kind of data they
use
Web
Analytics
User
Experience
Users’ behaviors
(what’s happening)
Quantitative measures
to determine what’s
happening
Organizational
Goals (key performance
indicators)
Measure performance
(goal-driven analysis)
Statistical data (“real”
data; large volume,
tons of errors)
Users’ intentions and
motives (why those
things happen)
Qualitative methods to
explain why things
happen
Helps users achieve
goals (expressed as tasks
or topics of interest)
Uncover patterns or
surprises (emergent)
Descriptive data (in
small volumes, tons of
errors)
We can learn
from each
other’s
data
We can improve
each other’s
tools
We can test
each other’s
hypotheses
We can help tell
each other’s
stories
We are smarter
together
Get
out
of
our
silos..
Establish what’s
common
Play games
together
Blue sky it
If you could design your
institution’s brain related to
visitor, audience, and community
data– from scratch– what would it
look like?
Put people together
the ones who can
tell the story…
…and the ones who
know the data
Integrated research
destroys assumptions
and leads to true insights
A few examples…
minisites
tweetups
“What the heck
is a tweetup?”
“Maybe in the
future don’t put
such an
emphasis on
twitter”
pet rex
What can
YOU do?
have visitor studies or evaluation?
talk to them
don’t?
advocate for it
either way… go rogue
Guerilla evaluation
techniques
-enlist help
-be brave; leave your cube/bldg
-get contact info & follow-up
-ask one simple question
Wanna meet half-way
between our silos…?
We’ll play
the keytar!
Check me out:
exposeyourmuseum.com
#exposyourmuseum
QR for the toolkit
Thanks to Louis Rosenfeld for my gratuitous thievery of his slides:
http://www.slideshare.net/lrosenfeld/beyond-user-research and for
all the other countless things I stole in the making of this presentation.