Party Tonight: Find Events, Grab Tickets, Meet People!

The team conducted surveys, competitor analysis, and interviews with event organizers to map user pain points in event discovery. Partnerships were established with ticketing platforms to outline API requirements, while behavioral data on event preferences (genres, locations, pricing) was aggregated to train initial AI models.

Wireframes for the recommendation feed, booking flow, and community hubs were designed in Figma, emphasizing intuitive navigation. Gamification mechanics, such as achievement badges and challenge-based rewards, were prototyped and tested with focus groups to refine user incentives.

Machine learning models were trained on user behavior (clicks, saves, purchases), event metadata, and location data. NLP algorithms parsed event descriptions and user reviews to enhance recommendation relevance. A/B testing optimized suggestion accuracy across demographics.

RESTful APIs were built to aggregate event data from platforms like Ticketmaster and Meetup. WebSockets and Firebase Cloud Messaging enabled real-time alerts for ticket drops and event updates. postGres and Redis managed structured data and caching for high-speed queries.

Stress tests simulated 10,000+ concurrent users during virtual concert ticket releases. AI recommendations were fine-tuned using feedback loops, while edge cases (e.g., conflicting event schedules) were resolved. Security audits ensured GDPR compliance for user data and payment processing.

A phased rollout launched in three cities, with localized event partnerships and influencer campaigns. In-app challenges (e.g., “Explore 5 Events in a Month”) drove early adoption, while community hubs integrated Discord-like chat features to foster user connections.