Hoperfy offers a white-label hotel booking platform for event organizers to monetize attendee accommodations. The platform automates the booking process, providing a branded experience for guests and generating revenue for organizers through a 50/50 profit share on reservations.
Funding
$30K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Event organizers often face challenges in monetizing visitor accommodations, leading to missed revenue opportunities and increased operational overhead. Managing hotel inquiries and bookings manually consumes valuable resources and prevents organizers from capturing a share of the profits generated by attendee stays.
Solution
Hoperfy provides a white-label hotel booking platform that automates the accommodation process for event attendees, enabling organizers to generate revenue. The platform is fully branded to match the event's identity, offering a seamless booking experience for international guests. Through a 50/50 revenue-sharing model on each reservation, organizers can transform hotel bookings into a passive income stream without requiring additional staff. The system also delivers real-time analytics to monitor booking behavior and optimize event profitability.
Target Audience
The primary target audience includes event organizers, conference planners, and trade show managers who host international attendees and seek to monetize accommodation services.
Features
- White-label booking engine with full event branding customization
- Automated booking workflow for hotel accommodations
- 50/50 revenue-sharing model on all completed bookings
- Real-time analytics dashboard for tracking visitor booking behavior and revenue
- Integrated customer support for event attendees
- API for accessing back-end booking data for marketing and pricing analysis
- Optional flight booking integration
- Advanced analytics with AI-driven suggestions for booking patterns and recommendations