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50match
mankrafts.com
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0 co-citations1 shared tech1 shared categoryadvertising-industry
50match
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50match
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0 co-citations1 shared tech1 shared categorymarketing-and-advertising
45match
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45match
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45match
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0 co-citations1 shared tech1 shared categoryadvertising-industry
45match
matthewinnovativeagency.com
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0 co-citations1 shared tech1 shared categorymarketing-and-advertising
42match
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0 co-citations1 shared tech1 shared categoryadvertising-industry
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0 co-citations1 shared tech1 shared categoryadvertising-industry
41match
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41match
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0 co-citations1 shared tech1 shared categoryadvertising-industry
41match
admiraloutdoor.com
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0 co-citations1 shared tech1 shared categorymarketing-and-advertising
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afakrause.com
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0 co-citations1 shared tech1 shared categoryadvertising-industry
41match
bandit-usa.com
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41match
elevatesocialhaus.com
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0 co-citations1 shared tech1 shared categorymarketing-and-advertising
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ficoremedia.com
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0 co-citations1 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.