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52match
manespaceottawa.com
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1 co-citations3 shared tech1 shared categoryhair-care
49match
hazefragrances.com
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48match
jmysalon.com
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48match
elanoire.com
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1 co-citations2 shared tech1 shared categorymakeup-and-accessories
46match
eldridgemullenhof.com
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botanicanoctis.com
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mansibisht.com
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44match
devilleagency.com
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44match
jkwbeauty.com
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1 co-citations3 shared tech1 shared categorybeauty
44match
bankzsalon.com
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1 co-citations3 shared tech1 shared categorybeauty
43match
joannalakoura.com
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1 co-citations3 shared tech1 shared categorymakeup-and-accessories
43match
boujielashestanning.com
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1 co-citations2 shared tech1 shared categorybeauty
43match
bowieandbyers.com
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1 co-citations2 shared tech1 shared categoryhair-care
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elanhairbelfast.com
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1 co-citations2 shared tech1 shared categoryhair-care
43match
elevatesalonco.com
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42match
adjany.com
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42match
elirosabeautybar.com
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1 co-citations3 shared tech0 shared categorymakeup-and-accessories

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.