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65match
jackdogproductions.com
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3 co-citations4 shared tech0 shared categorydocumentary
59match
1-voiceintl.com
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0 co-citations4 shared tech1 shared categoryfamily-children
58match
juliedonofrio.com
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3 co-citations5 shared tech0 shared categorydocumentary
57match
bottlesnbackpacks.com
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55match
georgiakiwanis.com
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1 co-citations5 shared tech1 shared categoryfamily-children
53match
handbookseries.com
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53match
juliepickren.com
Julie Pickren
3 co-citations3 shared tech1 shared categoryfamily-children
51match
elerigrace.com
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3 co-citations5 shared tech0 shared categoryromance
50match
hhnlegacy.com
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2 co-citations5 shared tech0 shared categoryhorror
49match
joaniequinn.com
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4 co-citations5 shared tech0 shared categorycomedy
49match
corneliagrey.com
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2 co-citations4 shared tech0 shared categoryromance
48match
feedlivebutterflies.com
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4 co-citations2 shared tech0 shared categorynature
47match
holidaymagiccd.com
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4 co-citations3 shared tech1 shared categoryfamily-children
47match
bostoncampfair.com
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2 co-citations4 shared tech1 shared categoryfamily-children
46match
jackact.com
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2 co-citations4 shared tech1 shared categoryfamily-children
46match
elisevcastle.com
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1 co-citations4 shared tech0 shared categorycomedy
46match
ferrershousehold.com
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1 co-citations4 shared tech0 shared categoryhistory
45match
makesmileci.com
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3 co-citations1 shared tech1 shared categoryfamily-children

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.