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82match
greenwoodsorganics.com
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1 co-citations2 shared tech2 shared categoryfood-and-drink
79match
grassfedmoo.com
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apocolatte.com
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apocalatte.com
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1 co-citations3 shared tech1 shared categoryfood-and-drink
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mamasusies.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
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manztou.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
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izideli.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
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1 co-citations2 shared tech1 shared categoryfood-and-drink
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bonappetistas.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
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coreyfiske.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
72match
dgelatomalta.com
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1 co-citations2 shared tech1 shared categorydesserts-and-baking
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getminoto.com
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70match
bakedsocal.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
68match
hamdandates.com
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1 co-citations3 shared tech2 shared categoryfood-and-drink
67match
makimakitrading.com
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67match
2hitaphoa.com
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mardahatinabila.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.