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77match
keonaaussies.com
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1 co-citations4 shared tech2 shared categorydogs
77match
hausderbullin.com
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1 co-citations4 shared tech2 shared categorydogs
77match
hidemandbullies.com
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1 co-citations4 shared tech2 shared categorydogs
77match
alldogobedience.com
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1 co-citations4 shared tech2 shared categorydogs
77match
corkdogtrainingclasses.com
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77match
deweylaunch.com
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1 co-citations4 shared tech2 shared categorydogs
68match
haydene.com
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1 co-citations4 shared tech2 shared categorydogs
68match
allaboutdoodledogs.com
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1 co-citations4 shared tech2 shared categorydogs
67match
heuerhausdds.com
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67match
genesisbelgians.com
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1 co-citations4 shared tech2 shared categorydogs
65match
kandopuppies.com
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65match
hiddenheartsbassethounds.com
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65match
greatlakespoodles.com
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65match
4roundfarm.com
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0 co-citations4 shared tech2 shared categorydogs
65match
banditopetsitting.com
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0 co-citations4 shared tech2 shared categorypets
65match
copperrosebeagles.com
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0 co-citations4 shared tech2 shared categorydogs
65match
devokehunters.com
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0 co-citations4 shared tech2 shared categorydogs
64match
majesticoton.com
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1 co-citations4 shared tech2 shared categorydogs

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.