We map here a less-experienced researcher; somewhere close to 1-2 years of experience. They’re not yet running end-to-end projects, but starting to learn and own the entirety of a basic interviewing and testing process. They are well-versed in managing data and basic prototype / concept testing. They are actively practicing their skills in how to debrief and analyze data from simple tests and interviews. And they are beginning to build out broader interviewing skills.

Data is the currency of user research. What we collect and how we deal with impacts every decision in the project that follows. The integrity of our work relies on the integrity of our data.

Managing and organizing raw research data is a crucial foundational skill. Doing it well instills the level of care and attention that peoples’ data deserves. There are related skills with a similar but less pronounced trend—coordination, capturing data, prototype testing, and survey development. 

These foundations of the practice are basic building blocks that can be adapted and remixed to suit any type of project. The ability to do so requires that these basics are developed to the point you can think through outlines of the activity and visualize how it might unfold.

We saw an extremely strong signal for the continued importance of Presenting the work across all levels at workshop participant experience.

The need to tell a good story starts right away. The scope is small at first—the story of a bug, a breakdown, or a simple missed opportunity—but it grows quickly. Established researchers present strategic direction and insights at a project, product-line, and organizational level. The good ones are good because they practiced, and they paid attention. 

Start paying attention to how different vehicles for results affect how the team engages with them. It’s not just what you know, but how you share it (and when, and with whom), that will drive impact.

Planning end-to-end projects was a strong signal in “most desired skill” for less experienced researchers.

It’s a logical next step: the building blocks (coordinating, interviewing, collecting data, so on) fit together and make projects. Planning a “pure” research project lets the researcher determine how research activities fit into team needs, and this is usually how learning to plan starts. Projects with cross-functional partners become a first real point of leverage in the organization, collaborating with a team to determine the course of the work.