SubMarket IQ

Inspiration

We were inspired by the proven engagement of Tinder’s left–right swipe interaction. Research shows that swipe‑based decision‑making is fast, intuitive, and captivating, so we asked ourselves:
What if exploring real‑estate submarkets felt just as effortless?

What it does

SubMarket IQ pulls public real‑estate and economic data, normalizes it, and displays it on a live geospatial dashboard. Users can explore any submarket and instantly see trends in rents, vacancy, migration, job growth, and permits.

It also includes a Tinder‑style swipe tool that shows properties matching the user’s criteria. Swipe right to save, left to skip — making property discovery simple and engaging.

How we built it

We combined data from:

FRED
Census ACS
HUD
Zillow
Building‑permit APIs
Custom web scrapers for public real‑estate datasets

All data flows into a unified model powering our Google Maps dashboard, complete with overlays and heatmaps.

We used Gemini to help design UI components and refine user flow.

We also implemented a weighted scoring system:

Inline example:
The score is computed as $S = \sum w_i f_i$.

Display example:

$$ \text{MatchScore} = \sum_{i=1}^{n} w_i \cdot f_i(\text{property}) $$

Challenges we ran into

Integrating the frontend with the backend
Rendering overlays and heatmaps with the Google Maps API
Normalizing inconsistent data formats across public sources

Accomplishments that we're proud of

A fully functional multi‑source data ingestion engine
A dynamic geospatial dashboard
A Tinder‑style property swipe interface
Clean integration of scrapers, APIs, backend logic, and UI

What we learned

We learned how effective teamwork becomes when responsibilities are split clearly. Coordinating across data, backend, and UI teams helped us move faster and debug more efficiently.

We also learned a lot about API integration, data cleaning, and real‑estate analytics.