How we rank Rochester window cleaning companies

Every business in our directory gets a single composite score derived from a transparent formula. We publish the formula and our data sources so you can verify the rankings yourself.

The formula

score = ((C × m) + (reviewCount × avgStars)) / (C + reviewCount)

Where:
  C        = 10        (prior weight — Bayesian smoother)
  m        = 4.0       (prior mean — the expected average rating)

This is the same Bayesian average IMDB uses to rank movies. It prevents a brand-new business with 5 perfect reviews from outranking an established operator with 200 reviews at 4.7 stars — because the 5-review business hasn't earned the statistical signal that says it's consistently 4.7+ at scale.

Worked example

Business A wins even though Business B has a perfect average — because A's 4.67 is supported by far more data points. Business C and B tie despite different stats, illustrating that volume and average trade off through the Bayesian prior.

Data sources

• Google Business Profile — primary source for review count + average stars + service area
• Yelp — secondary review signal where present
• BBB.org — accreditation status + complaint history (public records only)
• NY State business registry — verifies legal entity name + active status
• Business's own website — for service offerings + pricing where published

We update business data weekly. If you see something stale, email connormeador@gmail.com.

What we DON'T do

• Pay-for-placement — no business pays to rank higher
• Reciprocal-link schemes — no "link to us, we'll link to you"
• Scraped review text — we link to original sources, we don't republish
• Fabricated certifications — only verifiable industry credentials are mentioned
• AI-generated "sample of their work" images tied to specific businesses