Love: Dating App For Meaningful Relationships
Love is a dating app for meaningful relationships. No endless swiping: guided discovery highlights shared values. Built-in icebreakers and mini-games help conversations start naturally. Education from relationship experts and reflective achievements on profiles promote empathy and readiness.
2023
4 Months
Dating App
Seymur Mammadov
Challenge
In a crowded market, the key UX problems were swipe fatigue, paywall-driven incentives that discourage depth, and the “what do I say?” paralysis after matching. We framed these through a mixed-methods study: literature scan (Reddit/Quora/forums/articles), first-date field observations, competitive teardown, and interviews. It took multiple iterations before a tight problem statement emerged. Another challenge was crafting a modern, simple UI for complex, interactive flows without cognitive overload.
Results
Outputs included a slow, verified onboarding; personality and values testing with visible achievements; opt-in privacy (hide from contacts/Instagram); guided value-based matching; post-match icebreakers and cooperative mini-games; and gentle check-ins to encourage meeting or closing loops. Prototype tests with previous and new participants reported high satisfaction and easier first messages, with participants describing deeper, more empathetic introductions versus swipe-and-ghost patterns. The concept demonstrated strong potential to reduce churn and improve conversation quality.
Final Product
Research
Product Development
Prototype Access
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Conclusion
Love shows how a slow-dating, safety-first model can realign incentives from speed to depth. Through literature review, field observation, competitor analysis, and interviews, we reframed swipe fatigue and paywall friction into testable design problems. Iterative prototyping delivered guided onboarding, value-based matching, and built-in icebreakers that reduced first-message paralysis. Qualitative evaluations reported higher confidence and more substantive early conversations. Next steps include longitudinal studies on retention, well-being, and fairness of matching outcomes.