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78match
manztou.com
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1 co-citations2 shared tech2 shared categoryfood-and-drink
78match
greenwoodsorganics.com
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1 co-citations2 shared tech2 shared categoryfood-and-drink
78match
chaloc.com
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1 co-citations4 shared tech2 shared categoryfood-and-drink
72match
mangutli.com
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1 co-citations2 shared tech2 shared categoryfood-and-drink
72match
mamasusies.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
72match
mammatallow.com
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1 co-citations4 shared tech1 shared categoryfood-and-drink
72match
mamatallow.com
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1 co-citations4 shared tech1 shared categoryfood-and-drink
72match
izideli.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
72match
jenality.com
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72match
jimmyspoke.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
72match
countrysidemeathouse.com
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1 co-citations4 shared tech1 shared categoryfood-and-drink
72match
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1 co-citations4 shared tech1 shared categoryfood-and-drink
72match
bonappetistas.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
72match
bonnyd.com
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1 co-citations4 shared tech1 shared categoryfood-and-drink
72match
coreyfiske.com
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1 co-citations2 shared tech1 shared categoryfood-and-drink
72match
cornbeltconvenience.com
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1 co-citations4 shared tech1 shared categoryfood-and-drink
72match
crapeating.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

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.