Negotiating Room · Mixup Ltd Co · personal venture case study
I built a ZIP-level buyer-leverage index across four live metro markets from public housing data — verified byte-for-byte reproducible against source, and published under the attribution and no-charge terms the source data requires.
ZIP-months recomputed from raw inputs and checked exact against the published record — two of the four metros shown; Dallas–Fort Worth and Miami passed the same gate. Underlying data: Realtor.com® Economic Research, licensed CC BY-NC 4.0.
Negotiating Room ranks each ZIP code 0–100 on how much room buyers have in that market right now — built from four public columns (price-reduction share, listing growth, days on market, and how many active listings are pending) computed as a percentile against every other ZIP in the same metro that month. It's relative, not absolute: about 50 is typical for that metro, not "balanced," and the number is a rank, never a discount or a dollar figure.
A single month's score is noisy on its own — roughly a fifth of ZIPs cross the midpoint from one month to the next. I disclose that on the page rather than smoothing it away quietly, and the method itself is printed alongside every map so the number isn't a black box.
The underlying housing data carries real licensing terms, so I read them and built the constraint into the product instead of finding out later.
| Source | Terms | How it's honored |
|---|---|---|
| Realtor.com® Economic Research | CC BY-NC 4.0 | Free to view, attributed and linked on every surface, never sold or gated |
| Census & FHFA geography | Public domain | Used for ZIP boundaries and metro reference lines, cited on the page |