Case study · Real estate
Property discovery and lead conversion for a US real estate marketplace
A US marketplace connecting buyers, sellers and agents had plenty of traffic but few enquiries. We built personalized property discovery, AI valuation and a one-tap route to contact an agent.
Context
The client and the situation.
The client runs a real estate marketplace across major US metropolitan areas. It had strong listing inventory, but visitors browsed without contacting agents.
Challenge
What was holding them back.
- Few visitors became leads.
- Finding relevant properties was hard.
- Price estimates were unreliable.
- Users were shown too many irrelevant listings.
Approach
How we framed the problem.
We focused on discovery and trust. Users need to find the right property faster and believe the price they see. Contacting an agent should take one step.
What we built
The product, module by module.
Property recommendations
Personalized listings based on behavior, budget, preferences and location patterns, with the most relevant shown first.
AI valuation model
Real-time price estimates from historical sales, neighbourhood trends and property features, with a confidence score.
Map-based web platform
Interactive map search, filters for price, location and amenities, and market trend insights.
Mobile app
Property browsing, saved searches with alerts and a one-tap Contact agent flow.
Results
What changed.
Results reported for the project after launch.
Technology
Stack used.
- React
- Next.js
- React Native
- Node.js
- Regression models
- Geospatial analysis
- Google Maps API
More work
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