Habitual
Smartwatch-Integrated Dating App for Lifestyle-Based Matching
Overview
Habitual is a dating app that redefines compatibility by using smartwatch data to match users based on their daily habits including fitness, sleep, diet, and communication patterns. Unlike other dating apps that rely on superficial traits or passive swiping, Habitual helps users find meaningful relationships built on shared lifestyles and well-being.
By connecting mobile and smartwatch experiences, Habitual promotes more natural, authentic matches between people whose routines and values align whether that’s an early-morning runner, a night-owl gamer, or someone committed to plant-based eating.
Role
UX Research · UX/UI Design · Prototyping & Implementation
Team
Four-person team of UX designers and researchers
Collaborated with peers for ideation, testing, and iteration
Tools
Figma · FigJam · Zoom · Google Docs · Google Sheets · Google Slides · Pen & Paper
Defining the Challenge
Existing dating apps prioritize convenience and appearance over compatibility. Our challenge was to create a system that uses lifestyle data from smartwatches to build deeper, data-driven connections.
Design question:
How might we create an authentic dating experience by aligning people’s everyday habits rather than focusing on looks?
Research Phase
Preliminary Research & Market Scan
To identify opportunities, I led a market analysis comparing major dating apps such as Tinder, Bumble, and Hinge. I found that while many offered smartwatch extensions, none utilized wearable data for matchmaking. This discovery validated our concept’s novelty and potential competitive advantage.
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User Interviews
We conducted interviews with smartwatch owners aged 18–35 who actively used dating apps. We explored their motivations, frustrations, and what “compatibility” meant to them.
Key findings:
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Users were tired of superficial “swipe culture.”
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People valued shared interests and routines more than curated profiles.
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There was enthusiasm for passive data use, but concerns about privacy and control over data visibility.
Personas
Based on findings, I created two personas representing users seeking meaningful or casual connections grounded in shared habits. Their narratives illustrated both emotional and functional goals, guiding design priorities.
Ideation & Concept Development
Brainstorming & Design Charrette
Using FigJam, our team hosted a design charrette to brainstorm how smartwatch data could create value. We identified five habit-based categories:
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Fitness activity
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Sleep patterns
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Diet
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Communication habits
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Shared spaces
We mapped user journeys for both mobile and smartwatch contexts to ensure seamless cross-platform experiences.
Lo-Fi Sketching
I led the initial sketching sessions, translating concepts into quick paper wireframes. The focus was on information architecture — how users navigate between profiles, data sync, and messaging.
Design & Prototyping
Mid-Fidelity Prototype
I created the mid-fidelity prototype in Figma to validate the app’s structure and key workflows:
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Sync smartwatch data
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View matches and mutual interests
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Message or schedule a date
For the smartwatch interface, I designed simplified flows for quick actions (browse, like, chat) to minimize distraction while ensuring feature parity with mobile.
Usability Testing
We conducted five remote usability tests over Zoom with smartwatch owners familiar with dating apps. Each session lasted 30–45 minutes and included tasks like syncing data, checking matches, and scheduling dates.
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Goals:
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Evaluate task completion across devices
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Identify confusing navigation or terminology
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Gather feedback on perceived trust and usefulness
Key insights:
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Icons were often misinterpreted (e.g., heart, chat, and profile symbols).
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“Matches” was confusing — users assumed it meant mutual likes.
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Scheduling was too long and lacked time/place fields.
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Users wanted optional social media verification for authenticity.
Iteration & Refinement
Revisions
I synthesized results in FigJam affinity maps and prioritized fixes based on frequency and severity:
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Clarified navigation with labeled icons and consistent headers
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Simplified scheduling from five to three steps, including time and location
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Enhanced trust features with optional verification
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Improved readability with consistent typography and contrast
Hi-Fidelity Prototype
Using the revised flow, I built the high-fidelity prototype in Figma with a minimal, nature-inspired visual identity to reflect balance and wellness. The interface emphasized intuitive motion, color harmony, and readability across screen sizes.
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Final features included:
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Habit-based matchmaking visualization
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Seamless smartwatch-mobile syncing
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Smart notifications for upcoming dates
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Customizable privacy controls
Mobile Highlights
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Discover Tab: Personalized feed of compatible matches based on activity, diet, and sleep data.
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Connect Tab: Unified chat and scheduling experience.
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Profile Sync: Seamless smartwatch connection with status confirmation.
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Smartwatch Highlights
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Quick Match View: Swipe through nearby matches when on the go.
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Date Reminder: Subtle haptic notifications for upcoming plans.
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Mini-Chat: Respond to messages without needing the phone.
Impact
Through Habitual, our team demonstrated how wearable data can support authentic, wellness-aligned relationships. Participants described the concept as “a dating app that finally makes sense for my lifestyle.”
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The project showcased my ability to:
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Translate qualitative insights into actionable design
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Build and iterate multi-device prototypes
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Balance innovation, usability, and trust in emerging technology
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Reflection
Habitual taught me how to merge research-driven design with speculative technology. I learned the value of designing for subtle, everyday moments — where technology enhances connection instead of complicating it.
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The experience solidified my approach as a research-oriented designer: empathetic, data-informed, and always thinking about how technology can make relationships more human.