Conducting (m)user research
I’ve been talking with my friends at the World Resources Institute over the last few weeks about prioritising users when developing great digital products that people use to change the world. As I was talking to more and more people about the objectives of user research, I remembered the cover art for the new Muse album and thought it made a really great visual metaphor for what we’re trying to achieve. I hope you agree with my logic!
Full disclosure, my favourite album OF ALL TIME is the Muse album Origin of Symmetry. I loved them for a very long time: their mix of progressive melodies and dynamic vocals just did something for me that no other band has quite ever done. But I’m not here to fanboy over a small band from Devon…
I’m here to talk about users. We want to change the world by providing the right information to the right people at the right time. Often our chief target ‘user’ will be the ‘decision-maker/ policy-maker’, someone with authority who can set a direction for others to follow or whose decisions have greatest impact. They’ll likely be supported by either a technical or scientific advisor, an expert in the particular field. Especially in our experience in the non-profit space, we’ve found that the people that actually use a site, dataset or report are the advisors or officers: they are tasked to understand the data, explain it to the decision-maker and assist them in making their decision.
As I talked about this subject, I recalled the Muse album cover and something clicked. I showed it to a few people to explain the difference between end users and actual users when prioritising what you build on a website. Our v1 of the model is shown below. The end user is the person in the chair, the person with actual responsibility and the power to make a difference. While they are the people we want to try and target when building tools and applications, they’re an indirect target because, often, they are not the ones using the data, tool or report day in and day out.
When we’re developing tools to help people combat climate change, limit deforestation or make governments more open, we’re thinking about three key things, illustrated in this image:
- the big hand to the left of the picture: this is the advisor or officer, the key user of the tool itself. We need to think about what will appeal to them so they gain a deep understanding of the data.
- the lever between the big hand and the body in the foreground: This represents the interaction between an advisor and the decision-maker. What type of interaction is it: a face-to-face discussion, a paper-based report, or a shared URL link? What information and visualisations can we equip the advisor with to make a compelling argument to the decision-maker?
- the body at the centre controlling the machine: this is our decision-maker, the people we really want to influence. How do you make it really easy for the decision-maker to understand the information given to them and actually make a decision as a result of seeing the data?
The Live version
We’ve used this model a couple of times when making choices for our projects, particularly around adding analytical functions or specialist data layers. Progressive disclosure fits neatly in here, the idea of revealing more technical features at a later point in an interface. With progressive disclosure you acknowledge that some functions are mainly for specialists and can introduce ‘analysis paralysis’ if presented to non-technical users straightaway, so we place it later in the interaction. This means what ‘end users’ see (part 3 of the image) is visually arresting, compelling and understandable but options to analyse or customise are available for experts (part 1). Top that off with some simple short URL sharing options and you’ve made it really easy for experts to hand beautiful, usable maps to decision-makers (part 2).
Black Holes and User Revelations
That’s my model, something simple but really useful for us to start picturing real users completing actual tasks on the end product. I use it to frame any surveys, interviews, literature review or user tests we do, making sure we collect information about how different users like to see data displayed, how users interact with each other to discuss data and how viewing and talking about data fits in the decision-making process. When you reach that point you start to see who the most important users are and what kinds of displays will best satisfy their needs, so you can optimise the site for each person and increase the chances of it being used in the decisions that matter.
I’ll revise and refine the model as we work on more projects and observe these interactions at first hand. Do you have any thoughts, or other music-based metaphors? Dark Side of the User?
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