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PersonaEngine
What we wanted from
personas
A way of describing a audience
that could that support design &
make the client happy
We got to a point where we had a fairly solid
process.
It would start with gathering data through
interviews and observation.
Out of this we would build a survey.
We would then spend several days analysis the
survey data, using filters, cross tabs, basically
eyeballing the data.
Finally we had make it presentable which also took
time. We wanted to show the work that had gone
into personas.
What we were doing
What we were doing
Persona creation was the short straw. No one
wanted to do it.
Trawling through survey data and trying to make
manual comparisons was boring and time hungry
Choices were based on intuition
We were loosing a lot of data as filters are
reductive
And we still had to produce charts to populate
our documents.
The Issues
The idea
THE IDEA
Life would be better if we could automate the
analysis and generate all the assets we need to
build a document.
Any completed survey response creates a pattern
based on the answers they provide to the
questions.
We can then compare these responses statistically
to see who is similar and who is different.
And because this is data we can generate charts
we need automatically
PROFILE
SET OF
PERSONAS
PERSONA
VISUALISATION
RAW DATA: CSV
RESEMBLANCE
MATRIX
PROFILE
QUESTION SET
PROFILE
CREATION
PERSONA
CLUSTER
ANALYSIS
REPORT
GOOGLE
CHARTS
THE MODEL
Jeremy (the developer) got to work on it. But his
time was split between client work.
As he was making progress someone offered him a
more interesting job. Jeremy left. He was really the
only one who knew his work.
A short time later the company went under.
However this turned out to be an opportunity.
THE BUMP
Here is the one I built
PROFILES
CREATE PERSONAS
THE OUTPUT
http://personaengine.webnarrativ
e.co.uk/persona/uxpa

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PersonaEngine - James Sinclair

  • 2. What we wanted from personas A way of describing a audience that could that support design & make the client happy
  • 3. We got to a point where we had a fairly solid process. It would start with gathering data through interviews and observation. Out of this we would build a survey. We would then spend several days analysis the survey data, using filters, cross tabs, basically eyeballing the data. Finally we had make it presentable which also took time. We wanted to show the work that had gone into personas. What we were doing
  • 4. What we were doing
  • 5. Persona creation was the short straw. No one wanted to do it. Trawling through survey data and trying to make manual comparisons was boring and time hungry Choices were based on intuition We were loosing a lot of data as filters are reductive And we still had to produce charts to populate our documents. The Issues
  • 7. THE IDEA Life would be better if we could automate the analysis and generate all the assets we need to build a document. Any completed survey response creates a pattern based on the answers they provide to the questions. We can then compare these responses statistically to see who is similar and who is different. And because this is data we can generate charts we need automatically
  • 8. PROFILE SET OF PERSONAS PERSONA VISUALISATION RAW DATA: CSV RESEMBLANCE MATRIX PROFILE QUESTION SET PROFILE CREATION PERSONA CLUSTER ANALYSIS REPORT GOOGLE CHARTS THE MODEL
  • 9. Jeremy (the developer) got to work on it. But his time was split between client work. As he was making progress someone offered him a more interesting job. Jeremy left. He was really the only one who knew his work. A short time later the company went under. However this turned out to be an opportunity. THE BUMP
  • 10. Here is the one I built