Summary
K-Drama Fan Club is a consumer social app project for fans who want a place to react, discuss, and keep the feeling of a show alive after the finale.
The project started as a product hypothesis, not just an app idea. I wanted to test how fans behave after finishing a show, what they look for next, and whether a dedicated community surface could create more value than another generic watchlist.
Context
The product sits at the intersection of entertainment fandom, lightweight social behavior, and mobile-first community design. The early assumption was that fans wanted better ways to track and discuss shows. Discovery pushed the product toward something more human: casual conversation, gossip, reactions, and the social rituals that happen around a show.
Problem
K-drama fans already have places to find information. The harder question is whether they have a place that matches how they actually talk after watching: emotional, casual, opinionated, and social.
The product problem became: how do you create a mobile experience that makes low-pressure discussion feel natural without turning the app into a heavy forum or another empty social feed?
Approach
I started with a persona and product hypothesis, then built enough of a mobile MVP to make the idea inspectable. From there, I used discovery conversations and feedback loops to learn where the initial framing was too broad or too sterile.
The important shift was from "fans need more structured show information" toward "fans need a place to keep talking in the way fandom actually works."
What I Built
- A mobile MVP that made the product direction concrete.
- Early social surfaces for discussion and community behavior.
- Product discovery notes around personas, motivation, and post-show engagement.
- Feedback loops for reassessing the app after conversations with likely users.
- A foundation that can support iteration without locking the product too early.
Product / Technical Decisions
- Built the MVP to learn, not to prove the original idea correct.
- Kept the product focused on behavior after watching rather than generic media cataloging.
- Treated casual discussion and community rituals as product requirements, not decorative social features.
- Used AI-assisted engineering workflows for speed while keeping product decisions grounded in user feedback.
What I Learned
The most valuable product learning came from the mismatch between my initial structure and how fans actually describe the experience of watching. People do not always ask for "features." They describe moments, habits, frustrations, and rituals.
That shifted the app from a neat product concept toward a more specific social behavior problem.
Next Steps
- Add more specific discovery evidence from interviews and notes.
- Replace "[add metric]" with real validation data when available.
- Clarify the MVP scope and what changed after feedback.
- Add public links once there is a polished, shareable destination.