Buyer Spring

BuyerSpring is an in-progress real estate platform exploring a new way to buy and sell homes. Instead of flooding users with every available listing, it focuses on matching the right buyers with the right homes. The product is not live yet, but the core functionality is built and working, with design continuing to evolve.

I’ve led product design, frontend development, and user research, building BuyerSpring as both a concept and a real system.

The problem

Most real estate platforms treat home buying like shopping for shoes: show everything and let users filter it down themselves. Buyers scroll endlessly through listings that mostly don’t fit. Sellers have little insight into which buyers are truly a good fit for their home.

The experience is inefficient, impersonal, and overwhelming. On top of that, the real estate industry is slow to change. Any new platform has to prove it can build trust, work with agents, and show real value early—often through small, regional pilots.

BuyerSpring set out to challenge the “search and hope” model and replace it with something more intentional.

The idea

The core idea behind BuyerSpring is simple: don’t show every home—show the right ones.

Instead of starting with listings, BuyerSpring starts with people. Buyers enter meaningful information about what they want—budget, features, lifestyle fit, and priorities. Homes are then scored against that data using a custom matching algorithm.

The product isn’t about browsing—it’s about matching.

Designing the experience

The UX was designed to feel personal and assistive, not transactional. Buyers don’t just see a home—they see why it fits them. Matches come with explanations, not just photos and prices.

Sellers get visibility too. They can see which buyers are the strongest fit for their home, rather than treating all interest as equal.

Agents are part of the system as well. Tools allow them to manage matches, track progress, and support both sides of the transaction.

I designed the product flow to feel more like a guided experience than a marketplace: clear steps, meaningful inputs, and feedback that makes users feel understood.

Building the platform

BuyerSpring is built with Next.js, Tailwind, Supabase, and Mapbox. I implemented the full frontend, the matching logic, data flows, and core user journeys. While the visual design is still evolving, the underlying functionality is complete and working.

This project has been as much about building real software as it has been about testing a product idea.

Where it’s headed

BuyerSpring is preparing for a pilot in Tacoma. That pilot will allow us to refine the scoring system, validate user flows, and test whether a match-first model actually changes behavior.

Even before launch, the work has validated a key idea: when you focus on quality matches instead of quantity of listings, you create a calmer, more confident experience for buyers—and more meaningful leads for sellers and agents.

BuyerSpring isn’t finished yet. But it already represents the kind of work I care most about: challenging default patterns, designing around real human needs, and building products that feel thoughtful instead of noisy. Patent pending.