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96match
cosmiccoatingsca.com
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2 co-citations6 shared tech1 shared categoryhome-improvement
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cottonprestigeservices.com
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88match
kellhomerenovations.com
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2 co-citations7 shared tech1 shared categoryhome-improvement
87match
graulichbuilders.com
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4bvision.com
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2 co-citations4 shared tech1 shared categoryremodeling-and-construction
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86match
aaawallcoverings.com
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2 co-citations7 shared tech1 shared categoryhome-improvement
85match
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aegeandesignbuild.com
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2 co-citations7 shared tech1 shared categoryremodeling-and-construction
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adipropropertysolut.com
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1 co-citations7 shared tech1 shared categoryremodeling-and-construction
82match
diehlpavinginc.com
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2 co-citations7 shared tech1 shared categoryremodeling-and-construction
82match
bonaconstruction.com
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2 co-citations7 shared tech1 shared categoryremodeling-and-construction
81match
bonillabuildersco.com
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2 co-citations6 shared tech1 shared categoryremodeling-and-construction
80match
24kcleaningservicesllc.com
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2 co-citations7 shared tech0 shared categoryhome-improvement
80match
a-stonecleaning.com
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2 co-citations7 shared tech0 shared categoryindoor-environmental-quality
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cheeseheadlandscapes.com
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2 co-citations7 shared tech0 shared categorylandscaping
79match
aestheticbykarina.com
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bbrivers.com
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How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.