Qianhong Lin
Using the double diamond method, I explored the challenges of menstrual health tracking apps during a two-month project in my Master’s in Data-Driven Design. Through research and synthesis, I uncovered a critical gap: these apps often fail users with irregular cycles due to rigid, one-size-fits-all algorithms. As a data-driven designer, I challenged these assumptions by focusing on the exploration and synthesis phases to understand user pain points deeply. My goal was to design a solution that is inclusive, adaptive, and user-friendly—transforming cycle management from a frustrating experience into an empowering one. This project reflects my commitment to combining data-driven insights with user-centred design to create meaningful impact.
Client:
Fictional
My Role:
Data-Driven Designer
Year:
2025
Service Provided:
UX/UI Design, Ethical Design, Data studies, research
Project overview
Current period-tracking apps are built for standard cycles, leaving users with irregular cycles—especially those with conditions like endometriosis—frustrated by inaccurate predictions, overwhelming interfaces, and generic advice. Symptom Sync addresses this gap by focusing on personalisation, user control, and actionable insights, transforming raw symptom data into meaningful patterns.
Problem
Current period-tracking apps are designed for standard cycles, leading to inaccurate predictions, overwhelming interfaces, and generic advice. Users with irregular cycles experience frustration and disengagement due to the lack of adaptability and customization.
Solution
Symptom Sync introduces Symptom Clustering with AI Hypotheses, grouping symptoms into patterns, suggesting triggers, and offering actionable tips. Users confirm or adjust AI interpretations, ensuring personalised and evolving insights.
Key Design Choices
The design prioritizes user-centered adaptability by allowing modular input, ensuring users can personalize their experience based on individual needs and preferences. Instead of offering generic advice, the focus is on delivering actionable insights, personalised and data-driven suggestions that empower users to address their symptoms effectively. Transparency is embedded throughout the process to build trust, making it clear how insights are generated and what data informs them.
Key features include symptom-focused tracking, which lets users monitor specific concerns rather than relying on broad categories, and customisable views. This approach reflects a commitment to blending data-driven design with user-centric principles.
