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80match
kenjams.com
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7 co-citations1 shared tech0 shared categoryfreelance-writing
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janetlewendonart.com
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7 co-citations1 shared tech0 shared categorypainting
75match
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6 co-citations1 shared tech0 shared categorydrawing-and-sketching
75match
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4 co-citations1 shared tech1 shared categoryphotography
65match
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7 co-citations1 shared tech1 shared categoryphotography
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60match
cedphoto.com
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7 co-citations0 shared tech1 shared categoryphotography
55match
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jamiedell.com
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5 co-citations1 shared tech1 shared categoryphotography
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jimfarrant.com
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7 co-citations1 shared tech0 shared categorypainting
55match
greenerpainter.com
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7 co-citations1 shared tech0 shared categorypainting
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7 co-citations1 shared tech0 shared categoryaudio-production
55match
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55match
georgejamesantiques.com
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7 co-citations1 shared tech0 shared categoryantiquing-and-antiques
55match
meditecuae.com
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7 co-citations1 shared tech0 shared categoryworkshops-and-classes
50match
jennaemmerich.com
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3 co-citations0 shared tech2 shared categoryphotography
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ivyhouseantiques.com
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6 co-citations1 shared tech0 shared categoryantiquing-and-antiques
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6 co-citations1 shared tech0 shared categorypainting

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.