Share a little about yourself. How did you come to be a User Experience (UX) researcher at Experientia?

It was a bit of fate, really. After my Bachelor’s degree and first Master’s degree in Anthropology, I have been working as a business systems analyst. I then went on to pursue an advanced Master’s degree in Public policy in Turin, Italy.

I had just graduated and was looking for work. It just so happened that Experientia was searching for a multidisciplinary UX researcher in their unit dedicated to R&D: someone knowledgeable in ethnographic methods but was also interested in studying for a Master’s degree in artificial intelligence (AI). This degree would be funded by an Italian regional project, aimed at hiring and upskilling young professionals, where Experientia is a partner.

Through my past work, which included the development of a business intelligence system, I became very familiar with data infrastructure. My role at Experientia has, in a way, brought me full circle by allowing me to merge the two perspectives: social science research and data infrastructure.

What’s a week like for you? 

One full day a week, I attend classes for the Master in AI. The other four days vary quite a bit, depending on the specific project and its phase I’m currently working on.

Some weeks I do desk research or user research. This includes conducting user interviews or designing research tools, like protocols, surveys, and study guides. Other weeks I am more involved in analyzing the research material or developing and conducting workshops to present the research.

Often the work I do requires significant collaboration between team members. Each of us brings together different perspectives and works together to make sense of the data from our research. The most rewarding part for me is doing user interviews and synthesizing the research so that it can be used in the design process.

What’s a common misconception about working in UX that you would like to correct?

I think that the research process involved in UX is often taken for granted, particularly if it is qualitative in nature. In large part I think this stems from many industries, more or less, dipping their toes in the process, but not willing to dive in all the way.

What happens is either research is underfunded, unambitious, or, most often, insufficient time is allocated to crucial tasks like synthesis. I think this often produces lacklustre results. Many clients, for example, find comfort in standard market research. They are used to using it as the basis for their decision-making.

I think it often feels a little bit scary for organizations to use the insights from UX research in a double diamond framework to inform strategic business decisions, particularly if the organization is larger and more traditional. In the double diamond process, you expand and widen your understanding of a problem before synthesizing findings. This becomes essential for the ideation and prototyping phases that come later in the process. In the end, overcoming the inertia is possible if we use the right tools for communicating the research results and insights. This is why those who work in data visualization are so crucial to the team.

What are the most challenging parts of your work and what are your best hacks for those?

One is keeping up to date with information and developments across a variety of disciplines, fields, technologies, or projects. I try to dedicate a small portion of my day to reviewing headlines across several different sources (often supported by social media apps and email threads). Usually I do a quick skim of all the material and only dive a little deeper if something is relevant to the specific projects I am working on or to my larger interests for my role.

Another challenge is that it’s difficult to routinize tasks in UX research. My role requires lots of creative thinking and informed decision-making. Everything varies from project to project, which is the beauty of it, but it can also be exhausting. I try to think of ways to build frameworks and store knowledge to expedite some processes. Having some structures in place helps me direct my focus to where it’s most needed.

What would you say are the most understated skill-sets for being a UX researcher? 

A rather understated skill is theoretical grounding, but it can really sharpen and deepen the research results. UX researchers with very strong research backgrounds, generally across the social sciences, often have strong methodological and theoretical training.

I think the UX research community tends to emphasize method over theory, without realizing that both are mutually constitutive. Having a theoretical understanding of the research topics informs both the design of research tools and the analysis phase, particularly for complex topics like urban regeneration or health care.

What’s one piece of advice you wished you had when you were switching roles? 

It would be knowing how crucial relationship-building is across the job, whether internally with the team, externally with project partners, or even among the wider UX community. Every facet of relationship building is important in order to be successful across different aspects of the job. I’m continually learning how to better manage this.

What’s your favorite passion project?

Developing further skills in data science and data visualization. I’m learning a wide range of topics in AI, but because it is not a regular part of my daily job, I’ve been independently working on my technical skills. Finding the time to do so has not always been easy.

In particular, I’m interested in understanding how best to mix quantitative and qualitative methods in my role. One aspect is transforming qualitative data gained from ethnography into data stories. Another is engaging in larger discussions about data and ways to reframe that discourse. Instead of looking at data as “oil”, which can be extracted, consider that data is something chosen and created by people. As such, it is important to pay attention to the processes of creation and selection.

I like to explore ways in which qualitative research can render these data creation and selection mechanisms more transparent. This means contextualizing the data itself in more human-centered ways. I’m excited to work on a current project, where we are researching why people in a city with low crime rates may feel insecure, to help make the city more livable.