UX Research | Product Design
Dados is a versatile data-tracking platform that utilizes custom metrics, provides correlation-based insights, and integrates with wearables and popular health and fitness apps.
My wife, Julia, created a spreadsheet to track her daily activities, nutritional intake, hours of sleep, medications, supplements, and mood. Her goal was to have a custom tracker that could track anything and everything she wanted in one place. Ultimately, she wanted to view the correlations between different metrics and habits over time. How was her mood the next day if she got a bad night of sleep? If she drank less water, what was her perceived effort on a run?
For Julia, having a holistic view of her data was crucial to optimizing her health and wellbeing while minimizing unnecessary effort like taking multiple supplements without knowing which ones actually made her feel better.
A unified platform for collecting, correlating, and analyzing all her personal metrics would empower her to find insights to support her goals efficiently.
Wearable devices and health apps provide users with an immense amount of health and lifestyle data, but this data is fragmented across multiple apps and platforms. Julia and I have experimented with various wearables and apps over the past couple of years, tracking metrics like sleep, heart rate variability (HRV), and exercise. While these devices excel at gathering data, I found several pain points:
There is a need for a unified platform that integrates data across devices, allows custom tracking of metrics, and provides insights. This would empower users to optimize their health and wellness.
To address the challenge of fragmented and overwhelming health data, I hypothesized that a unified platform could enable users to create a complete picture of their health and wellness.
Potential solutions:
By leveraging existing data sources and enabling custom tracking, Dados provides users with a complete picture to efficiently gain personalized insights about their well-being.
After completing my initial user interviews, I synthesized the insights to define two core user personas that encompassed the target users for Dados: athletes and hobbyists. Developing these personas allowed me to better empathize with and design for my core users.
Creating these user archetypes based on my interview findings allowed me to consistently reference and make decisions through the lens of who I was designing Dados for. The personas kept the core needs and mindsets of target users front and center as I translated insights into potential features and functionality.
Following multiple testing rounds and iterative design improvements, I successfully developed the final mockups for the app.I addressed the primary concerns of users by:
Dados started as an inspiration from my wife, Julia, who wanted to have a custom data tracker. Some day, I will bring Dados to life. The core of Dados starts with simple custom data tracking, and I plan on continuing to iterate and test to meet users' needs.
The future of Dados involves seamless integration with a wider range of wearables for enhanced usability, including devices like Whoop. I will incorporate learning language models to provide users with deeper insights and recommendations.
I would like to work alongside a developer to build out Dados as a usable tool. This will require a proper handoff of all documentation, and communicating the feature requirements to the developer.
Overall, I consider Dados to be a successful project.
Through the design process for Dados, I learned the immense value of an iterative approach centered around continuous user testing and feedback. In the beginning, I relied heavily on recreating features from existing apps without deeply understanding my users' needs. After initial user testing yielded dissatisfaction, I went back to my user research and developed persona-based prototypes aimed specifically at my target users' wants and preferences. Additional testing enabled me to rapidly redesign based on feedback until designs aligned well with user needs. This experience underscored the importance of early and frequent testing to create a product that truly meets user needs while balancing business requirements.
By scrapping my initial ideas and developing new prototypes specifically addressing user-articulated needs, I was able to dramatically improve user satisfaction in subsequent testing. This taught me the immense value of user-centricity through employing user research to deeply understand target users early on and continuously design to meet user needs.
Given the insights from this project, if I were to start over, I would implement more frequent and rapid testing cycles to accelerate learning. I would focus on quickly developing minimally viable prototypes to test key assumptions and ideas with target users very early on. By testing rough concepts rapidly at every stage, I could gain insights faster, pinpoint issues sooner, and redesign with user feedback top of mind. Shortening testing cycles enables designers to fail fast and learn faster. This approach of continuous testing and improvement ensures designs evolve to best meet user needs and priorities quickly and efficiently.