Automation of User Matching Flow for a Housing Platform to Enhance Scalability

The client operates a platform that connects property owners with potential tenants, but currently relies heavily on manual processing with over 27 manual steps in the matching workflow. This causes high operational hours—approximately 6 hours per match—and limits scalability, slowing user acquisition and market expansion.

A mid-sized online platform connecting property owners with prospective tenants, focusing on international markets and social sharing experiences.

• Reduce manual processing steps in the matching flow from over 27 to a minimal number (target: 3).
• Decrease overall matching time per user from approximately 6 hours to 1 hour.
• Enhance platform scalability to support increased user base and growth targets.
• Implement a cost-effective, serverless architecture to minimize operational costs.
• Improve user experience through faster, more efficient matching processes.

• Frontend interface for users to view and update profiles, preferences, and social sharing options using ReactJS.
• Backend system using Python to process matching logic, manage user data, and coordinate workflows.
• Serverless deployment on cloud platform utilizing Lambda functions, DynamoDB for data storage, and SQS for task queuing.
• Automated matching process that minimizes manual intervention, reducing steps from 27 to 3.
• Real-time notifications and updates to users based on matching status.
• Administrative dashboard for platform management and oversight.
• Secure authentication, user data privacy, and role-based permissions.

• Authentication systems for user login and registration
• Notification services for user alerts
• Third-party verification or social media APIs for profile enrichment
• Analytics platforms for performance monitoring

• System should maintain high availability with 99.9% uptime.
• Response times should support real-time user interactions, aiming for sub-second latency where possible.
• Cost-efficient operation utilizing a serverless architecture, targeting minimal monthly cloud costs.
• Scalability to support increased concurrent users as the platform grows.
• Data security and compliance with relevant privacy standards.

By automating the user matching process and reducing manual intervention from over 27 steps and 6 hours per match to just 3 steps and 1 hour per match, the platform is expected to significantly increase operational efficiency, support rapid user acquisition, and enable scalable growth. The improvements are projected to facilitate faster onboarding, improved user satisfaction, and lower operational costs, fostering sustained market expansion and competitive advantage.