At Buyer Folio, we are focused on refining our co-buyer matching system and Folio Score to enhance the homebuying experience for our users. By integrating insights from overhoused and underhoused households, our goal is to create a more efficient, personalized, and data-driven matching process. This will allow us to match buyers with potential co-buyers based on housing capacity, affordability, and pre-qualification data, ensuring a better use of existing housing assets.

Participants will focus on:

• Conducting market research to analyze the needs of overhoused and underhoused households, understanding key challenges and opportunities.
• Improving the Folio Score system by incorporating available space data to provide more accurate co-buyer matches.
• Designing intuitive user interfaces for both buyers and co-buyers, enabling them to easily track their Folio Score, explore co-buying options, and view homes with surplus capacity.
• Analyzing the current matching algorithm, identifying areas for improvement, and suggesting enhancements to better meet market demands.

By the end of the project, participants will complete the following tasks and produce the corresponding deliverables:

1. Market Research Report on Housing Needs

• Understanding the Overhousing/Underhousing Paradox:
• Research Insights: Provide a comprehensive analysis of overhoused and underhoused households, incorporating data on vacant bedrooms, housing shortages, and regional disparities. Identify areas with significant underutilized properties, particularly those suitable for co-buying or shared ownership.
• Actionable Insights: Focus on broad insights into housing needs and underutilized assets without extensive regional analysis. Emphasize the identification of overhoused homeowners with surplus space or underhoused families who may benefit from co-ownership solutions.

2. User Research & Needs Assessment Report

• User Feedback Collection:
• User Interviews: Conduct interviews with prospective buyers, homeowners with extra space, and families in need of housing to understand their pain points, motivations, and the viability of shared ownership or renting out unused rooms.
• Research Findings: Summarize findings on how users feel about shared space usage (e.g., renting out rooms or investing in co-buying) and their expectations for a matching system, such as the Folio Score.

3. Refined Co-Buyer Matching Algorithm with AI Integration

• AI-Driven Matching System:
• Algorithm Enhancements: Recommend improvements to the co-buyer matching algorithm that incorporates users' property preferences, Folio Scores, and available underutilized assets (e.g., vacant rooms or large backyards). Use AI to provide the most relevant co-buying matches based on this data.
• Matching Criteria Rationale: Simplify the rationale for the matching criteria and focus on the core elements like space needs and property preferences.

4. UI/UX Design for Co-Buyer Dashboard and Matching Features

• Co-Buyer Dashboard:
• Simplified Dashboard Design: Create an intuitive and easy-to-navigate dashboard where users can view available homes with vacant rooms or larger backyards suitable for laneway housing. The dashboard should also show potential co-buyers who match their criteria.

5. User Testing & Feedback Report

• Conduct User Testing:
• Overhoused Participants: Test the platform with overhoused homeowners (those with surplus space). Gather feedback on the usability of the co-buyer matching process, and the effectiveness of the Folio Score in informing their decision-making process.
• Simplified User Scenarios: Focus on core testing scenarios related to the usability of co-buyer matching and the Folio Score’s role in the decision-making process. Test the functionality and ensure a smooth user experience in matching co-buyers and homes.