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47match
javahutkingsbeach.com
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2 co-citations2 shared tech2 shared categoryfood-and-drink
43match
majorinmocha.com
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43match
majornmocha.com
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43match
haveasippe.com
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43match
bakeryartisan.com
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2 co-citations0 shared tech2 shared categorydesserts-and-baking
43match
elitefoodanddining.com
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2 co-citations0 shared tech2 shared categoryfood-and-drink
43match
major-rager.com
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42match
jimmyschicagobeef.com
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42match
majesty-jc.com
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1 co-citations1 shared tech2 shared categoryfood-and-drink
42match
cha2cha.com
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41match
kelleysquareliquors.com
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41match
jimmyspoke.com
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1 co-citations1 shared tech2 shared categoryfood-and-drink
41match
greyandcashmonrovia.com
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41match
boudamnn.com
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41match
jansnoodles.com
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1 co-citations1 shared tech2 shared categoryfood-and-drink
41match
heychef.com
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41match
greenleafgrill.com
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41match
bakephuket.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.