Home Repair Index
A programmatic data site that publishes independently computed repair costs — foundation repair and roofing, localized to 25 US metros.
Every published figure is the output of a documented pipeline: cross-referenced national baselines, government wage data, and local soil and hail context — not copied estimates.
Visit homerepairindex.comThe Problem
Repair-Cost Content Is Recycled Guesswork
Search for "foundation repair cost" and you get the same vague national ranges copied between lead-gen sites, with no methodology and no local adjustment. A crack repair in San Antonio's clay soil and one in Seattle are different jobs with different labor markets — but the internet quotes them the same number. Home Repair Index computes its figures instead, and shows its work.
25
US metros with localized cost pages for foundation repair and roofing
≥3
Public cost guides cross-referenced for every national baseline figure
100%
Of published figures traceable to a documented, repeatable pipeline
How It Works
Computed From Sources, Not Copied
The site is the visible end of a data pipeline. Baselines come from cross-referenced public guides, localization comes from government statistics, and the whole thing rebuilds from data on demand.
Cross-Referenced National Baselines
No cost figure enters the dataset from a single source. Every national baseline — per repair type, per severity tier — is cross-referenced from at least three public cost guides before it's accepted. Outliers get investigated, not averaged in. The result is a defensible starting number instead of one site's guess.
Localized with Government Wage Data
Labor is the biggest driver of repair-cost variance between cities, so each metro gets a construction-wage multiplier computed from the Bureau of Labor Statistics QCEW dataset. A national baseline times a metro's real wage multiplier produces a localized range that actually reflects that market — and updates when the government data does.
BLS QCEW Wages
Metro-level construction wages fetched programmatically and turned into cost multipliers per city.
USDA Soil + NOAA Hail
Each metro page carries local risk context — expansive-soil profiles for foundations, hail history for roofs.
Published Methodology & Re-Verification
The site publishes its full methodology — where baselines come from, how multipliers are computed, when figures were last verified. Data pages carry re-verification dates and go through scheduled refreshes. In a category built on recycled numbers, showing your work is the moat: it's what makes the site citable and worth ranking.
Programmatic Static Build
Cost pages, city pages, and guides are generated by a Node build pipeline from structured data files — trades, metros, baselines, multipliers. Change the data, run the build, and every affected page updates consistently, sitemap included. The output is a fast, dependency-free static site with editorial guides layered on top of the data core.
Under the Hood
A Data Pipeline That Emits a Website
No CMS, no database, no servers — structured data in, static HTML out, tested end to end.
Node.js
Build pipeline
BLS QCEW API
Wage data
USDA / NOAA
Soil + hail data
Static HTML
Generated site
Cloudflare Pages
Hosting
JSON Data Files
Source of truth
Automated Tests
Pipeline checks
Search Console
SEO monitoring
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Data products, programmatic SEO sites, automated content pipelines — if it starts with real data and ends with something people search for, we can build it.
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