Project: EnVsion is an AI-based video repository tool designed to assist UX Researchers in interview analysis by identifying researchers' questions and summarising participants' answers. The main goal of the project was to identify areas for improvement and enhance the value of EnVsion website in their workflow.
Role: UX Researcher
Duration: 3 months
Problem: High level of registration for a free trial period, but a low level of permanent subscription. Unclear value proposition and unique features. No clear vision for the future positioning and needed features.
Conclusion: It was recommended to enhance several aspects of the products such as collaboration (allowing users to collaborate inside the tool), management and control (tags and highlights management features), security (control of involvement level of each participant) and AI involvement.
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
Pre-interview process
Our main users were user researchers who are conducting qualitative research that are working as freelancers or employed within small companies.
Our main goal of the research was to be able to understand the needs, pain points and challenges of researchers (user value) and identify specific features or improvements that can enhance EnVsion's value proposition for those users.
Interview process
The recruitment process of participants was made with the help of a screening form to ensure that we have people that were qualified for our study.
The interview script consisted of interview questions and usability tasks.
We identified two main usability tasks such as “creating and managing a highlight” and “creating and managing a tag”.
Some other crucial areas like creating accounts, adding team members to collaborate were identified during heuristics. However due to the limitation of the current version and time limit, we were not able to test them. Therefore we asked specific questions touching those topics during the interviews to be able to build use cases to provide as evidence for much-needed functionality.
Analysis process
Using the affinity map technique, we grouped all the feedback into more than 20 groups according to its common characteristics.
FINDINGS
Main positive points
1. Participants found the generated script accurate and they mentioned the importance of that;
2. The provided feature to summarise the paragraph or data while creating a highlight was identified as “time-saver”;
3. Participants mentioned the AI generated highlights as helpful and valuable;
4. The page where all the highlights were stored was very helpful since it was providing an interview’s overview.
Main pain points
1. Lack of real time collaboration - It helps a researcher to involve the team in the process or draw their attention to information nuggets relevant for their team members;
2. Major frictions while creating highlights or tags such as invisible save button, not protected sharing link with the video.
3. Problems with information architecture - it was difficult to understand which video was related to which project, lack of filtering or filing options, no confirmation messages of the creation of the tag or preventing or deleting something.
4. No management function of the tags such as combining them, deleting several or filtering them.
5. No clear identification of the icons - Icons were taken from different libraries and were not consistent. Some of the icons were misleading and didn’t provide any value to the users.
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.
Further development and recommendation
All the recommendations that were given were specific to each pain point that was described in the report. All the recommendations were prioritised and recommended for the implantation according to its priority.
Main further areas of development were to implement main collaboration features to ensure seamless teamwork and develop AI features such as AI generated highlights for further report creation.
I have also designed a new landing page that was pointing new features and important elements out.
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!