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75match
hollandesw.com
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2 co-citations7 shared tech1 shared categoryshopping
68match
boodlo.com
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65match
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65match
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65match
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64match
gratitudegardensco.com
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63match
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59match
booster3.com
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58match
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58match
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apkabagwala.com
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57match
jiyazon.com
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56match
bookobuddy.com
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2 co-citations2 shared tech1 shared categoryshopping
56match
hatsandhive.com
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3 co-citations0 shared tech1 shared categoryshopping
56match
dicarbu.com
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55match
ceoluxurychild.com
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1 co-citations7 shared tech1 shared categoryshopping
55match
bankscloset.com
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kjsmarket.com
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2 co-citations1 shared tech1 shared categorycoupons-and-discounts

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.