One of the main challenges for us as researchers is making our findings more actionable for the rest of the team, particularly during the discovery phases when we’re conducting exploratory research.
At least initially, early stage research can bring more ambiguity than clarity, throw up more questions than answers and we often end up with challenges and problems that are too broad to solve.
As researchers, it’s our responsibility to use research methods that will facilitate good design and product decisions. It’s not enough to just do the research, we need to help translate what we’ve learnt for the rest of the team so that it’s useful.
How we did it
We’re working on a commercial service. Our team’s remit was to find out what would make our service different because, in theory, if we can solve unmet customer needs, we can compete in a saturated market. A successful product or service is one that is viable, feasible and desirable.
This post covers 3 techniques we’ve recently tried. Each one helped us reduce ambiguity, achieve a clearer product direction and get a better understanding of our users, their behaviours and motivations.
1.Learning from extremes
When we’re testing for usability or we’re seeing how well a functional journey works, we usually show users a single, high fidelity prototype. However, earlier on in the design process, we put very different ideas in front of users so we can elicit a stronger reaction from them. If we only showed one idea at that point, their reaction is likely to be lukewarm. It’s when we elicit joy, hatred, confusion for example that we learn a lot more about what they need from a product.
In this instance, we wanted to uncover insight that would help us define what might make a more compelling product.
We identified the following problem areas:
- Time – people don’t have much of it.
- Choice – there is so much.
- Inspiration – people struggle with it.
Instead of prototyping something that would attempt to improve all 3 of these problem areas as we would do when testing usability, we mocked up 3 very different prototypes – each one addressed just one of the problems.
The extreme prototypes helped users better articulate what meets their needs and what might work in different contexts. It wasn’t a case of figuring out which version was ‘best’. We used this technique to test each idea so we could find out which elements work and therefore include them in the next iteration. It also started informing the features that the experience would be comprised of.
Overall though, it helped us reach a clear product direction which gave us a steer in our next stage of research.
2.Doing a diary study
A diary study is a great way to understand motivations and uncover patterns of behaviour over a period of time. We recently invited a bunch of urban shoppers to keep a diary of how they were deciding what to eat at home.
We asked them to use Whatsapp, partly because it was something they already used regularly but also because its quick, instant messages reflect the relatively quick amount of time it takes for someone to make a decision about what to eat. The decision is not like choosing which house to buy where you might think about and record decisions carefully in spreadsheets, so it would be difficult for people to reflect on their ‘what to eat’ decisions retrospectively in interviews. Whatsapp was a way to get closer to how choices are made so we could better understand the context, behaviour and decision itself.
The engagement was much higher than we expected. We captured lots of rich data including diary entries in text, video and photo format. We didn’t ask for or expect the visuals but they were very useful in bringing the contexts to life for our stakeholders.
When we looked for patterns in the data, we found that nobody behaved in the same way every day, or over time. However, we were able to identify ways people make choices. We called them ‘decision making modes’. We looked at the context in which people made decisions and the behaviour we’ve observed. Each mode highlighted different pain points, for example, they may have leftovers to use up. This enables us to prioritise certain modes over others, get alignment as a team on who we’re solving problems for, and think about features to help address some of the pain points for users.
3.Using sacrificial concepts
‘Sacrificial concepts’, a method developed by design company IDEO, allow us to gain insight into users’ beliefs and behaviour. We start with reframing our research insights as ‘How might we…?’ questions that help us find opportunities for the next stage of the design process.
For example, we found that buying groceries online feels like a big effort and a chore for shoppers because of the number of decisions involved. So we asked: “How might we reduce the number of decisions that people need to make when they shop online?”
We did this as a team and we then create low fidelity sketches or ‘concepts’ that we’re willing to sacrifice that we can put in front of users.
Just like when we test extremes, the purpose of testing those ideas wasn’t to find a ‘winning version’ – it was to provoke conversation and have a less rigid interview.
Sacrificial concepts are a fast and cheap way to test ideas. No-one is too invested in them and they allow us to get users’ reaction to the gist of the idea as opposed to the interface. They give us a clearer direction on how to address a problem that users are facing and they are a good way to make research findings more usable in the design process.
What’s worked for you?
Those are the 3 main ways we’ve approached research in the early phase of one particular commercial Co-op service. We’d like to hear how other researcher and digital teams do it and their experiences with the techniques we’ve talked about.
Principal user researcher