Demystifying UX Research: A Product Designer’s Perspective
As a product designer, collaboration with the research team is an integral part of my work. Whether it’s gathering insights, conducting usability tests, or identifying user needs, I rely on their expertise.
However, I realized that I had never personally experienced the work of a researcher myself. Because of that, I was feeling like I couldn’t really bring much to the conversation when talking about research, or just did not always understand why things were done one way or the other. I believe this lack of knowledge can be the source of some misunderstanding or even discord between designers and researchers. To bridge this gap, I approached our UX research manager with a proposal to participate in their work and receive training in research methodologies.
My goal was not to change careers and become a researcher, but rather to step into their shoes, understand the research process better and encourage everyone in the product team to appreciate the value of research. In this post, I will share my journey, objectives, and insights gained during this experience.
What I wanted to get out of this experience
Before diving into it, I set clear objectives for my training. I aimed to gain a clear understanding of various UX research methods, learn to ask the right questions to obtain relevant insights, and expand my skills in data analysis. To achieve these objectives, I planned to shadow experienced researchers, participate in bite-sized learning sessions with the team, and design, run, and analyse my own moderated interviews with their support. I allocated a three-month period alongside my regular work to accomplish these goals.
To familiarize myself with the research process, I reviewed past research projects, understanding the rationale behind the chosen techniques, the setup, and the analysis. Additionally, I had the opportunity to shadow one of our researchers during a usability test.
This experience highlighted the importance of research in challenging designers’ assumptions and articulating insights that might be obvious to designers but not to others.
My Research Project
Selecting a research topic turned out to be a challenging task, as the possibilities were vast.
But when I started this project, ChatGPT was making headlines and thought I would run a study about AI. While I could have explored the user experience, reliability, and accuracy of AI predictions, I wanted to tackle a different angle. The ethical implications and biases associated with AI were significant considerations, but I felt this topic might be too vast and complex to cover comprehensively. Instead, I opted to focus on how people interact with AI, particularly exploring awareness, acceptance, and trust.
Defining Research Objectives:
Defining clear and focused research objectives was a difficult task. While I was thinking about the research objectives, I was also trying to figure out what research questions would allow me to reach those objectives. I was worried that I would not be able to get the insights I needed. And I felt a bit stuck at that point, going round and round between objectives and questions. Sharing and discussing my ideas with the research team really helped and made me see this part of the project as a more creative and iterative process than I thought. Feedback from the research team was invaluable in refining these questions and developing a robust discussion guide. My research objectives revolved around understanding people’s perception of AI, their current usage and level of awareness, their thoughts on AI in consumer products, and their concerns and level of trust in AI.
Recruitment:
To conduct interviews, I needed to carefully consider participant selection. Initially, I aimed to interview six participants across different age groups and genders. Given the focus on AI-powered products, I designed screening questions to determine participants’ experience and interactions with AI, but it was very general, thinking I could then go through potential participants to align with my recruitment criteria.
To facilitate the recruitment process, I utilised usertesting.com, which forced me to rethink the recruitment. The platform allows to set filters and screening questions to determine if people have the experience or perspective needed. Based on the answers, the platform then allocates a person and schedules the meeting.
To ensure I have a diverse group of participants across different product categories, I created six different sessions, each with its set of filters and screening questions.
Crafting the Discussion Guides:
To guide the interview process, I developed discussion guides for each product category. These guides followed the same structured format:
1. Introduction
2. Opening interview: General technology-related questions
3. AI interaction: Exploring participants’ interactions with specific AI-powered products
4. AI as a concept: Examining understanding and opinions about AI
5. Trust: Probing thoughts on AI’s role in various domains such as justice, recruitment, and medicine
The Interview Process:
As a novice interviewer, I approached the interview process with some apprehension. I ran focus groups in the past and I have spent many hours watching user testing interviews, but I have never conducted one myself.
The first session was the pilot, the opportunity to put my discussion guide to the test but also find my rhythm… And it was not great! I spent too much time on one part, and then ran out of time. I was unable to take notes, while fully listening to the participant, following my plan, and keeping an eye on the clock! Another important aspect I had not really thought about before is the balance you have to strike between following the discussion guide and being flexible enough to explore valuable insights beyond the planned questions.
After the interview, I identified areas for improvement, revised my approach, and refined the order of my questions. I also decided not to take notes during the interviews, as they were recorded. Subsequent interviews proved more successful.
I enjoyed doing the interviews more than I thought I would. There is something special about spending an hour with someone you have never met, getting to know some very personal aspects of their life, talking about some random subject, seeing into their home and probably never meet again.
Data Analysis:
Analysing the gathered insights was a time-consuming yet straightforward process. Since I refrained from taking notes during interviews, I reviewed the recordings to capture key points accurately. Organizing the data into a table format within Miro, I grouped it by participant and research question. Summarizing the findings for each question facilitated a clearer understanding of the data.
From these summaries, I identified categories that shaped the narrative for presenting the findings.
The presentation:
Transforming the raw data into a compelling story was an interesting process. I translated my findings into a narrative, combining factual information with a creative approach to convey the insights effectively. With the freedom of a training exercise, I could tailor my presentation to engage and captivate the audience through both narration and visuals.
Conclusion
A lot of the work going into a research plan goes unnoticed, and participating in the research process has provided invaluable insights. It has reinforced the importance of understanding and appreciating the work done by UX researchers. Engaging in research enhances our ability to be better designers and collaborate effectively. By understanding each other’s craft, we can foster a culture of continuous learning and improvement within the design team. I am grateful for this enlightening experience and the dedication our UX researchers bring to the table.
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