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72match
kanekobros.com
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1 co-citations2 shared tech1 shared categoryshopping
72match
larakahn.com
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1 co-citations2 shared tech1 shared categoryshopping
72match
malamakihoneybees.com
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1 co-citations2 shared tech1 shared categoryshopping
72match
hausofgaud.com
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72match
bbbdubai.com
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72match
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1 co-citations2 shared tech1 shared categoryshopping
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bootscootindoobie.com
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1 co-citations2 shared tech1 shared categoryshopping
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1 co-citations2 shared tech1 shared categoryshopping
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devicashop.com
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1 co-citations2 shared tech1 shared categoryshopping
67match
bbdsales.com
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1 co-citations2 shared tech1 shared categoryshopping
67match
get3driven.com
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1 co-citations2 shared tech1 shared categoryshopping
64match
fennbach.com
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1 co-citations2 shared tech1 shared categoryshopping
62match
mamimakesmagic.com
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1 co-citations2 shared tech0 shared categoryparty-supplies-and-decorations
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jacksonandvale.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.