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62match
4categories.com
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58match
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jimivarner.com
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hawaiianmenopause.com
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elfiensclinic.com
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1 co-citations4 shared tech0 shared categoryphysical-therapy
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marginwizhealth.com
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dhwellnesssolutions.com
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1 co-citations2 shared tech2 shared categorywellness
54match
gentlehabitnutrition.com
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2 co-citations2 shared tech1 shared categoryhealthy-living
51match
healandmeal.com
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1 co-citations2 shared tech1 shared categoryholistic-health
51match
bookyourbody.com
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1 co-citations2 shared tech1 shared categoryhealthy-living
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dialyourhealth.com
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1 co-citations2 shared tech1 shared categoryhealthy-living
51match
feelforyourself.com
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1 co-citations2 shared tech1 shared categoryhealthy-living
51match
fibbonity.com
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1 co-citations2 shared tech1 shared categoryholistic-health
50match
manhallab.com
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1 co-citations3 shared tech0 shared categorywomen-s-health
50match
apexcarypt.com
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1 co-citations3 shared tech0 shared categoryphysical-therapy
49match
iyogaguru.com
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1 co-citations2 shared tech1 shared categorywellness
49match
breathe-app.com
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1 co-citations4 shared tech2 shared categoryhealthy-living
48match
arrelsbienestar.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.