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78match
hibearbrick.com
Home
3 co-citations14 shared tech1 shared categoryshopping
75match
aethertaiwan.com
首頁
3 co-citations15 shared tech1 shared categoryshopping
73match
hkohbaby.com
Ohbaby 美國日本直送
3 co-citations15 shared tech1 shared categoryshopping
67match
2littlebob.com
Home
1 co-citations15 shared tech1 shared categoryshopping
64match
bonbonscientific.com
首頁
3 co-citations15 shared tech1 shared categoryshopping
63match
hgbegin.com
首頁
2 co-citations15 shared tech1 shared categoryshopping
63match
ho9cake.com
首頁
2 co-citations15 shared tech1 shared categoryshopping
63match
greenrizelife.com
首頁
2 co-citations15 shared tech1 shared categoryshopping
61match
jiliegg.com
首頁
2 co-citations14 shared tech1 shared categoryshopping
61match
feng-hang.com
Feng Hang
2 co-citations14 shared tech1 shared categoryshopping
61match
gemmore.com
首頁
2 co-citations14 shared tech1 shared categoryshopping
57match
jane-color.com
首頁
3 co-citations13 shared tech1 shared categoryshopping
56match
jfstore.com
陳記百果園
3 co-citations15 shared tech0 shared categorygrocery-shopping
56match
boosthealth-jp.com
首頁
2 co-citations15 shared tech1 shared categoryshopping
56match
diffshop1.com
DIFF官方網站
2 co-citations15 shared tech1 shared categoryshopping
54match
hiyorimeat.com
日荷肉舖
3 co-citations15 shared tech0 shared categorygrocery-shopping
54match
hkdrhealth.com
首頁
2 co-citations15 shared tech1 shared categoryshopping
52match
mommomusa.com
首頁
2 co-citations14 shared tech1 shared categoryshopping

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.