User Hero

Helping User Researchers Process Interviews Faster.

Project Overview

User research is extremely important for every company to help drive decisions. Having run into the pains of organizing and synthesizing large studies in our previous companies, we set out to help ease the process of running and processing user interviews, so that companies could get to insights faster.

My focus was to figure out the precise problem area that was most ripe for solving - both from the business and the user perspectives. My task was then to rapidly design and iterate the product itself. We went from concept to #3 on Product Hunt in about 5 months.
2020 - 2021
Figma, Invision, Miro, Zeplin, Asana
UX/UI Design, Web Design, User Research, Product Management


In 2017, I launched a company aimed at tackling the public health crisis plaguing urban environments. We were accepted to a prominent accelerator whose motto is “Talk to Your Users” - this became my primary focus for three years.

I spoke with hundreds of users and experienced the daily struggle tracking, processing, and sharing the learnings that came from these conversations.

Compiling notes, quotes, and clips across multiple interviews and studies to inform my team about what needed to be built was a tedious administrative nightmare.

I asked myself, “How might I make the tracking and processing of interviews better?” With the hundreds of products out there, why wasn't there a tool that made running the interview, compiling my observations, and creating my recommendation charts simple?
Researchers spend an inordinate amount of time recruiting and UX Ops are a key pain point for research projects.

The administrative and "tedious" parts of the research process is an acute problem for UX researchers and a key obstacle in their ability to feel effective.
How Might We...?
...make the process of running user interviews less time consuming?
...reduce the headache of processing all the information from user interviews?
...make learnings from user research easier to share?


Being pre-product, we needed to begin with secondary research and recruiting participants to better understand the problem space.

I ran a round of interviews with three segments of participants who regularly conduct user research: Early Stage Founders, UX Researchers, and Product Managers. Participants were recruited from UX Slack communities and my network.
Research Methods
User Interviews
User Journey
Empathy Mapping
Market Research Analysis
Competitive Heuristic Analysis
Prototype testing
User Interviews
Initial conversations quickly showed that while UX Operations are a serious headache, another acute problem for researchers and product managers was in the actual conducting of interviews and systems for synthesizing/organizing that data.

I used the Jobs to Be Done framework along with some affinity mapping to further refine the various issues and priorities for our potential personas.
Empathy Mapping
Follow up interviews allowed me to do some empathy mapping to further refine the problem area. At this point, it became clear that the goal of establishing "credibility" for a recommendation was behind much of the work leading up to the actual presentation of findings. This work included lots of tedious data crunching, something that was ripe for software to streamline.
Based on this initial round of interviews, I identified three personas that would be potential users of a tool to help them research. Running further interviews with these segments allowed me to hone my understanding of each persona and identify potential problem opportunities, with the goal of creating User Journey Maps to allow us to identify a key value proposition for our product.
User Journey Mapping
Creating Journey Maps for the personas helped clarify what specific moment in the user's journey we could target when thinking about solutions.

Two Areas became apparent opportunities for further exploration:
- Coordination of UX Ops
- Documentation and synthesis of interviews
Market Testing
To further understand the market potential of the different product directions, we ran tests consisting of multiple landing pages to evaluate interest in different problem areas. Each landing page described a solution for a specific area of the problem space and had an email collection form. We posted multiple versions of the landing pages with different headlines to test market interest. Respondents were than interviewed to understand the acuteness of their problems (is this "hair on fire"?).
Paper Prototyping
Leveraging the interviews with the landing page respondents, I began creating user flows and paper prototyping some possible software solutions.


The results of the research phase led us to moving away from UX Ops as a product direction, and towards knowledge management and Voice of the Customer. While there were issues in the UX Ops space, the knowledge processing/management was a more desirable market.

One of a designer’s most important jobs is to establish credibility, whether through storytelling or documentation, so that other stakeholders accept and adopt the outcome of a design process. 

For many designers a presentation is used to communicate all the evidence to prove “this is how I know what I know”.

Working backwards from that outcome, the obvious solution was to design software to help compile the evidence collected during interviews, often a time consuming and tedious process, automatic. 
Key Insights
UX Ops are an issue, but the specific issue varies wildly between the personas - from sourcing to actual coordination.

From a market perspective, knowledge management was more desirable.

Credibility is key for a researcher convincing stakeholders of their recommendations.

Much of a researcher's job is documentation to backup their knowledge.
With a hypothesis in hand, I began the design of a platform that allows a researchers to create their studies and populate it with interviews. The goal would be for each of these interviews to be annotated individually, pulling clips and quotes from a recording or notes.

These observations and clips automatically get compiled into a a common outcome for researchers to present, such as a rainbow chart or response matrix. The researcher can share this simple visual tool that documents all of the insights and also allows for stakeholders to drill into each one.

In automatically connecting the disparate data that gets created during each study, a normally tedious administrative process, the researcher can focus on the details of each interview.
Design System
Working with the engineers, we determined that the best stack to quickly create the front-end for the webapp would be React with Tailwind CSS framework. I built our brand and the design system in Figma to match the framework so that screen ready designs could be quickly implemented.
Final Screens and Iterations
Using the design system and tailwind framework, I delivered final screens to the engineers for key flows. These flows allowed us to launch quickly and test on real users. Ongoing cycles of user testing with prototypes of key flows allowed us to refine the screens and UX further.


We had a tight window to define a market and a problem that would allow us to build/launch a product. Leaning heavily on a traditional design thinking framework allowed us to quickly land on the most attractive opportunity for problem solving and quickly iterate to a solution.

Closely working with the distributed engineering team throughout the process kept us all aligned around key product goals and greatly increased our development speed.

Leaning heavily on component libraries and a robust design system also helped accelerate our build rate.

Ideally, there would have been more time to prototype in earlier phases - there were some false starts in the final design process - but because of the tight team communication, we were quickly able to course correct.