Backdoor - Giacomo Pollesel

Backdoor
Real Estate Intelligence.

[2024] Web platform for real estate investing

AI - UX DESIGN

Backdoor's insights are available at backdoor.fi.
Please ask for free access.

The Need

People often lack the time and knowledge to make informed real estate decisions. Unlike traditional finance, stocks and crypto, which have a plethora of dashboards and analysis tools, real estate lacks accessible market insights for investors.
Property data available online is fragmented and scattered across multiple sources. Therefore, it is often inaccessible and difficult to read or use effectively. Hence, there is a need for a tool that provides this information in an easy format, helping investors find the needle in the haystack, by making timely decisions and maximising return on investment.

The Product

Backdoor is an AI-powered toolset designed to make real estate data simple and accessible. The recently released MVP features a dashboard divided into three sections: Explore, Discover, and Analyse. From the dashboard, users can find the best properties on the market based on custom metrics like ROI, yield, and profit. Additionally, three new indicators—let index, price index, and demand index—provide a summary of complex measurements in clear colour-coded scores from 0 to 10.
AI is integrated at multiple levels, assisting with data analysis, predicting property valuations and forecasting future prices.

Backdoor.fi

The Process

To address the need, the goal was to create a toolset for real estate decision-making by gathering and synthesising a large dataset. The first step was finding all available information on the market. Three key sources were identified, which varied by country:

Historic property and rental prices. Available from national or regional organisations, updated every six months.
Real estate listing portals. The current offering is fragmented, data is updated in real-time.
Statistics and mapping data. Available from national or private institutions with low-frequency updates.

After a competitive analysis, target users were identified, and a first functional prototype was built using a regional data subset to test the concept. The dashboard included key features that were selected for the MVP:

Market Explorer: for finding the most promising categories and regions.
ROI Calculator: for calculating the relevant investment metrics for any property on the market.
Deal Finder: for comparing the metrics and finding the best opportunities.
Auction Assistant: for making informed decisions during property auctions.

The research phase included a series of user interviews, combining marketing analysis and usability testing. The insights led to an improved user flow and a value proposition focused on simplicity and accessibility. Three design iterations were built in Figma: a low-fidelity wireframe, a high-fidelity prototype for further testing, and a final design of the MVP. A cohesive design system was created based on Tailwind. The dashboard was then built with React and JavaScript.