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77match
costarhu.com
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2 co-citations5 shared tech1 shared categoryapartments
76match
botannia.com
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3 co-citations4 shared tech1 shared categoryapartments
62match
centroresidences.com
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3 co-citations4 shared tech1 shared categoryapartments
56match
cosmoloft.com
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1 co-citations5 shared tech1 shared categoryapartments
53match
gregorydevelopments.com
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0 co-citations3 shared tech1 shared categoryreal-estate-renting-and-leasing
53match
manilaroomsforrent.com
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1 co-citations2 shared tech1 shared categoryreal-estate-renting-and-leasing
50match
greenbaumrentals.com
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0 co-citations3 shared tech1 shared categoryapartments
50match
grovecondominium.com
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0 co-citations3 shared tech1 shared categoryreal-estate
50match
7locations.com
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0 co-citations3 shared tech1 shared categoryreal-estate-renting-and-leasing
48match
bandbrents.com
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0 co-citations3 shared tech1 shared categoryreal-estate-renting-and-leasing
48match
coronadoislandrental.com
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0 co-citations3 shared tech1 shared categoryreal-estate-renting-and-leasing
46match
baywoodsanmateo.com
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44match
apartamentosesfreus.com
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0 co-citations2 shared tech1 shared categoryvacation-properties
44match
apartamentsesfreus.com
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0 co-citations2 shared tech1 shared categoryvacation-properties
42match
bbhouseseattle.com
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0 co-citations2 shared tech1 shared categoryapartments
42match
appfoliotesting.com
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0 co-citations2 shared tech1 shared categoryreal-estate-renting-and-leasing
42match
balfourproperties.com
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42match
apartmentsnevenka.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.