Role: UX Researcher
Duration: 3 months
The challenge
EnVsion is an AI-powered platform that helps UX researchers analyze interview data by automatically generating transcripts, highlights, and summaries.
Despite a high number of free trial registrations, the product struggled with:
- low conversion to paid subscriptions
- unclear value proposition
- lack of feature prioritization
The key question:
Why are users not converting — and what should the product focus on to increase value?
Deliverables:
1. Heuristics evaluation report with evaluation;
2. A comprehensive report detailing the insights gathered from research activities and recommendations for the implementation;
3. A presentation to the implementation team, introducing key findings, insights, and recommendations.
Project Overview
It was a collaborative project from the Research Bookmark organisation. After conducting a thorough analysis of the previous research data and collaborating with the EnVsion team, we have observed a high level of user subscriptions for trial periods, yet there is a notable absence of conversions into paid subscriptions. To address this issue, we conducted user interviews and usability testing sessions, complementing it with heuristics evaluation to ensure a seamless and intuitive interface, information architecture and usability, as well as optimal information architecture and usability.
Personal challenges: It was my first experience working with AI technologies so I took some time to be able to understand how the processes, models are functioning. Additionally, I found it challenging to separate my research and UI mindsets while preparing heuristic analysis. This required the ability to differentiate between usability problems and interface points of improvement.
Personal milestones: I gained hands-on experience redesigning the EnVsion landing page to drive higher conversion rates. I was involved working within agile methods, ensuring regular progress updates and close collaboration with team members.
Working with my colleague on affinity map
Working with my colleague on affinity map
RESEARCH
To understand both user needs and product issues, I combined:
- User interviews with UX researchers (freelancers & small teams)
- Usability testing on key workflows
- Heuristic evaluation of the interface and structure
Focus areas:
- how researchers analyze interviews
- pain points in current workflow
- perceived value of AI features
We identified two main usability tasks such as “creating and managing a highlight” and “creating and managing a tag”.
Key insights
1. Value exists — but is not clearly communicated
Users appreciated:
- AI-generated highlights
- automatic summaries
But struggled to understand:
- how the tool fits into their workflow
- what makes it different from alternatives
2. Collaboration is a critical missing feature
Researchers often work in teams, but:
- no real-time collaboration
- no easy way to share insights
It limits adoption in professional environments.
3. Information architecture created friction
Users experienced confusion due to:
- unclear connection between videos and projects
- lack of filtering and organization
- missing feedback (e.g. confirmation messages)
4. Core workflows were not intuitive
Key tasks like:
- creating highlights
- managing tags
were difficult due to:
- poor visibility of actions (e.g. save button)
- inconsistent UI patterns
Here on the picture you can see the presentation of one of the pain points and the recommendations for its solution from the report that was delivered to the implementation team.
Key product decisions & recommendations
Based on the research, I helped define priority areas for product improvement:
1. Introduce collaboration features
- shared workspaces
- team-level access and permissions to support real research teams.
2. Redesign information architecture
- clearer project structure
- improved filtering and organization to reduce cognitive load.
3. Improve tagging & highlight management
- ability to edit, merge, filter tags
- clearer workflows for highlight creation to support large-scale qualitative analysis.
4. Strengthen AI-driven value proposition
- emphasize AI-generated insights
- support report creation workflows to position EnVsion as a time-saving tool.
Impact
- Delivered a comprehensive research report with prioritized recommendations
- Presented findings directly to the implementation team
- Contributed to redefining product direction and feature priorities
- Designed a new landing page to better communicate product value and improve conversion.
Thank you for exploring my project! If you're curious to see more of my work, head over to the "Work" section. And if you have any questions or just want to chat, feel free to reach out – I'd love to hear from you!
Tschuss, ciao, au revoir, ade!