Motivation
Being a researcher can be difficult; you need to deal with vast amounts of data and draw meaningful insights. When my colleague faced the daunting task of analyzing 65 user interview recordings, I saw an opportunity to help. I wanted to create a tool that would not only save time but also enhance the depth of analysis. This led to the development of an automated tool for transcribing and analyzing emotions in the interviews, transforming a labor-intensive process into a more efficient and insightful one.
User Research
I interviewed 3 UX designers and 2 researchers to understand their needs, creating personas to identify main objectives, expectations, and pain points.
Methodology
Participants: 2 UX researchers and 3 UX designers.
Methods: Semi-structured interviews and online surveys.
Data Analysis: Thematic analysis to identify common themes and pain points.
Common Challenges
Managing and organizing large volumes of interview data.
Time-consuming manual transcription and preliminary analysis.
User Needs
Automated transcription with high accuracy.
A safe tool for confidential data.
Desired Features
Integration with tools like Slack, Teams, and Google Meetings.
User-friendly interface with minimal learning curve.
Final thoughts
There is a strong demand for an AI tool to simplify and speed up qualitative data analysis, with a focus on transcription accuracy, analysis flexibility, and data security.
Task Flow Definition
I mapped out the current process of conducting interviews, highlighting manual work and inefficiencies. Integrating Dialog AI could automate steps like scheduling, transcription, and data analysis, saving time and reducing errors.
Wireframe Design
Low-fidelity wireframes outlined the visual roadmap of the app, allowing rapid iteration before creating detailed mockups.
Style Guide
Color schemes, typography, and icons used in the project.
Home
The home screen summarizes the user's workspace, projects, team, and updates.
Projects
Users can create and manage projects, adding team members.
Studies
Each project can contain multiple studies, with functionalities for categorizing studies with custom tags.
Files
Users can add and organize documents, filtering and sorting files, and changing display modes.
New File
Users can customize fields for new documents and make notes in the annotations area.
Media Files
AI transcribes and analyzes audio and video files, categorizing the interviewee's emotions.
Insights
The insights tab summarizes conversations with positive and negative aspects, including editable tags.
Analysis
The analytics tab features a dashboard with AI-generated metrics like overall sentiment, emotion, and notable pain points.
Conclusion
This project showcases AI's role in enhancing UX design processes, underscoring my commitment to innovative solutions that improve user experience understanding. I will continue exploring new technologies to further advance UX design effectiveness.
Thanks for reading!