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100match
julielynnesalon.com
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1 co-citations6 shared tech2 shared categoryhair-care
100match
jmhairloft.com
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1 co-citations6 shared tech2 shared categoryhair-care
100match
archerhousehair.com
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1 co-citations6 shared tech2 shared categoryhair-care
90match
juliadlashes.com
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90match
hcsalon114.com
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90match
breannrehl.com
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1 co-citations4 shared tech2 shared categoryhair-care
80match
majestichairacademy.com
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1 co-citations4 shared tech1 shared categoryhair-care
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1 co-citations4 shared tech1 shared categoryhair-care
80match
manehausco.com
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1 co-citations4 shared tech1 shared categoryhair-care
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healinghairartist.com
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1 co-citations4 shared tech1 shared categorybeauty
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hfsparejuvenate.com
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1 co-citations4 shared tech1 shared categorybeauty
80match
holisticrubies.com
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1 co-citations4 shared tech1 shared categorybeauty
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aliyahatelier.com
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1 co-citations4 shared tech1 shared categoryskin-care
80match
adrianagreyesthetics.com
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1 co-citations4 shared tech1 shared categoryskin-care
80match
aesthetic-alchemy.com
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1 co-citations4 shared tech1 shared categoryskin-care
80match
botanicalmane.com
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1 co-citations4 shared tech1 shared categoryhair-care
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dfaskin.com
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1 co-citations6 shared tech0 shared categoryskin-care

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.