Filters

Context

Filters are the backbone of any property search experience. For LavaMap’s listing platform, the challenge was heightened by the complexity of New York City’s real estate market, where property types, transaction modes, and investment opportunities vary widely. Our objective was to design a filtering system that would reduce friction, minimize search steps, and deliver highly relevant results for different types of users.

Design Challenge

Enable users to quickly find the right property with minimal effort.
Account for the different mental models and needs of renters, buyers, and investors.
Research and identify the most common property types and use cases in NYC’s diverse market.
Ensure the filtering system was powerful without becoming overwhelming or confusing.
Provide clarity and transparency in results, so users trusted what they were seeing.

Solution Overview

Conducted research into common search behaviors across renters, buyers, and investors to inform filter categories and defaults.
Designed a context-aware filtering system where the options adapted based on the search type (e.g., renting vs. buying vs. investment).
Developed a hierarchy of filters. Primary filters for the most essential attributes (price, location, size). Secondary filters for advanced criteria (building type, amenities, zoning, investment metrics).
Focused on progressive disclosure, surfacing only the most relevant filters up front and allowing advanced users to dive deeper.
Optimized the interface to reduce steps and keep users focused on the results, not the configuration process.

Impact

Significantly improved the speed and accuracy of property discovery for LavaMap users.
Created a flexible yet intuitive system that could serve diverse user segments without overwhelming them.
Helped position LavaMap as a smart, user-friendly alternative to traditional property search platforms.
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Filters

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Want to get in touch?
Drop me a line!