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65match
grlimited.com
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2 co-citations3 shared tech1 shared categorymarketing-and-advertising
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
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2 co-citations0 shared tech1 shared categorymarketing-and-advertising
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2 co-citations0 shared tech1 shared categorymarketing-and-advertising
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
56match
bahamamedia.com
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
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dh-techs.com
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
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2 co-citations1 shared tech1 shared categoryadvertising-industry
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eleana-us.com
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
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linkedcommerce.com
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
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baghdadcreative.com
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
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bolocreate.com
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
54match
greenhousedigi.com
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2 co-citations1 shared tech1 shared categorymarketing-and-advertising
52match
jimbroad.com
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2 co-citations0 shared tech1 shared categorymarketing-and-advertising
52match
haxestech.com
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2 co-citations0 shared tech1 shared categorymarketing-and-advertising
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greatpowermarketing.com
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2 co-citations0 shared tech1 shared categorymarketing-and-advertising

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.