Code & Craft initiated an in-depth user research study with a goal of achieving a clearer understanding of the client's user base and identify the core user groups through clearly defined and validated user personas.
The initial discovery took the form of a porto-persona workshop with the leadership team to identify some of the initial user assumptions by utilizing their existing knowledge of the user base.
Proto-Personas are a great way of extracting valuable and often valid, user insights within a short amount of time. It's also a great platform to introduce some of the core concepts and explain the value creation that is generated through a user centric research study.
Proto-personas must always be validated with real data from actual users. This data can come from a range of different sources, in this instance we conducted over 130 in-person interviews across a 2-month period.
The interviews were structured around the initial user assumptions that were identified during the Proto-Persona workshop. However one of the main benefits of in-person interviews was the ability to adapt the questions to each participant.
Armed with nearly 10 hours of recorded interviews we conducted a thorough analysis that consisted of listening to each interview and noting down every insight we believed had value. This resulted in over 850 individual insights.
In order to identify the trends and patterns, we used a technique called Affinity Mapping to sift through the insights we had identified. Affinity Mapping is a great way to categorize large amount of data based on natural groupings.
As a result, we ended up with clear conclusions that were applied to our initial hypotheses.
listened to interviewsy
Over the course of several weeks we listened to the interviews,noting anything down that gave us insight into Spartan racers.
From the detailed notes we went through the process of abstracting individual insights and then used a technique called affinity mapping to divide them into 10 categories.
The last phase of the user research study was to take our validated user hypotheses and structure them in a personal document.