As part of the International Day of Awesome, they suggested writing a blog post about someone you think epitomizes the ideals of awesomeness. If there was anyone who epitomized awesomeness, it is my soon-to-be husband, Bradley Wright.
Not only is he so awesome, that he even has his own awesome pose — The Awesome Pose of Bradley Wright — he’s one of the most talented web developers out there… he even built this website for me! Plus anyone who can put up living with me, deserves a medal.
I’m sure you’re all retching at this super, sappy post, so I’ll finish it here!
If you’ve ever had to apply for something which requires credit history, then you’ve probably seen this type of form. Unfortunately, it’s almost always done badly.
Rich Amos has documented a more elegant, user friendly approach to this type of form. Ben Bashford and myself chipped in with some feedback based on our experiences.
Director of Main Library at Pedagogical University of Cracow
Talking about task analysis - What their goals are and what they actually do to achieve these goals. How their previous knowledge helps them achieve this.
5 examples: Buying products, finding in library, betting on horse races, finding the law, I want to know more about cancer? I am confused…
Comparing Amazon display to library catalogue. Seems like we missed a trick to improve the experience!
Functions of a Library Catalogue by Charles A. Cutter (1904) from Rules for a Dictionary - Interesting to see the main goals are still the same over 100 years later.
Librarians used to find us physical books, now they are search engines!
OPAC = Online Public Access Catalogue. Consistent system across all libraries which allows for integration.
Interesting way of checking the navigation labels - Taking a screenshot with these options and allowing people to write what they thought the terms were.
Final result was a cleaner, simpler interface with labels that people understood. However they had a negative reaction due to changes in the log-in / account details.
Whilst the presenters, Sabrina Mach & James Page, seemed like lovely people, I didn’t like the selling aspect of this talk. I thought this was about different techniques for ethnography, guess I should read the fine print next time!
The debate about whether ethnography conducted over a short period of time is actually ethnography. We want to be applying deeper conceptions and discarding crude and inaccurate assumptions.
Gurus are less likely to be open to change. They don’t want to be a novice again.
People find lab testing boring. As time wears on, they lose interest.
Maria Cristina Lavazza - From shelves to mobile devices
I was particularly interested in this session because it’s not often that you hear about the IA of food. Given it is something that is so central in our lives, it is quite surprising I’ve never really seen it mentioned before.
A lot of this was stating the obvious for me but it’s definitely great for anyone unfamiliar with combining these methods. The book sounds like it would be a great primer.
What is web analytics - Where are they coming from, what are they doing and where and when they are leaving.
Web analytics is often seen as boring, their implementation is not always correct, often end up with a huge chunk of data without adequate interpretation.
User research has data from only a small number of people, it’s just a snapshot in time, it’s difficult to capture some behaviour and the setting can be artificial (in a lab etc).
The two methodologies help each other. User research helps interpret the data, data can focus the research. Improving the pool of information strengthens your argument.
The example of an unexpected landing page, is something WA can pick up which UR can investigate.
The example of preparing a usability test. Created a scenario based on these entry paths (Google)
The example of advanced functionalities. What are people using? There was actually no data on the features.
The example of unintended user flows. People not using internal search of a website. User research noticed that the page offered no reasons to stay.
Web analytics can validate findings. Only 2/10 test participants experienced this problem. Quantified this issue with the data of thousands of visitors.
The combined methods can be used throughout the process. One report without conflicting information.
Even basic analysis helps, although the tools do not magically provide the insights. You can measure the impact of your changes. We should have access to this data, as we have information of the how and why.
IA Shuffle - Specialists in Design, do they breed failure?
