Enhancement of a peer-to-peer ride-hailing platform
Development and implementation of a user management system and a hierarchical reward model as part of the Multi-Level Marketing (MLM) integration for the ride-hailing platform
Client
Dylyver is a ride-hailing platform with a unique referral program that allows to earn commissions not only for drivers but also for passengers from each trip, as well as for partners who sign up in your network
Business challenges
- Develop and Implement a referral model on an existing platform
- Give users the tools to manage their funds and referrals
Our solutions
- Participation in the design of a multi-level marketing platform
- Implementation of a hierarchical rewards model
- Authorization and account management system
- Payroll management system
Project implementation
Prior to initiating development, the client provided calculations and mathematical formulas for determining referral bonuses. After analyzing the high-level concepts, we developed an algorithm that implements a complex hierarchical payout model, tailored to the user’s current level in the referral program.
The next phase involved the creation of an account management system. In addition to an authorization system supporting two roles, we developed a referral management system and a custom payroll module. This allowed users to top up an internal wallet for trip payments, receive commissions, and withdraw funds to a bank account or debit card.
Simultaneously, our team conducted thorough testing of the main platform. Following bug fixes, we integrated the new solutions with the platform’s core backend.
Technology stack
- Node.js
- React.js
- PostgreSQL
- RabbitMQ
- Docker
- Jest
Key activities
Business outcomes
The implemented project enabled the client to achieve the following goals:
- Increased the platform's value by empowering users with the ability to manage their funds and referrals
- Drove user base growth through the introduction of a comprehensive referral program
- Enhanced the platform's performance and user satisfaction by resolving bugs identified during extensive testing
