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48match
bazarsera.com
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4 co-citations4 shared tech1 shared categoryshopping
46match
couponhuts.com
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45match
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45match
genelleamber.com
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44match
greenvely.com
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5 co-citations4 shared tech1 shared categoryshopping
43match
cedgroup.co.uk 🇬🇧
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3 co-citations5 shared tech1 shared categoryshopping
43match
jenaeinez.com
jenae inez
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42match
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5 co-citations4 shared tech1 shared categoryshopping
42match
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4 co-citations5 shared tech1 shared categoryshopping
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healme2.com
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4 co-citations5 shared tech1 shared categoryshopping
42match
1adayvitamins.com
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4 co-citations5 shared tech1 shared categoryshopping
42match
featured-promotions.com
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42match
feelbetterforless.com
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4 co-citations5 shared tech1 shared categoryshopping
42match
getdailynutrients.com
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4 co-citations5 shared tech1 shared categoryshopping
42match
gethealthyquick.com
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4 co-citations5 shared tech1 shared categoryshopping
42match
jamiiexpress.com
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4 co-citations4 shared tech1 shared categoryshopping
42match
anyzell.com
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aquapatches.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.