Piperic Business Intelligence

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1 co-citations2 shared tech2 shared categorysoftware-and-applications

1 co-citations2 shared tech2 shared categorysoftware-and-applications

julianflores.com

1 co-citations2 shared tech1 shared categorytechnology-and-computing

1 co-citations2 shared tech1 shared categorytechnology-and-computing

kellehertech.com

1 co-citations2 shared tech1 shared categorytechnology-and-computing

1 co-citations2 shared tech1 shared categorysoftware-and-applications

kennethnoble.com

1 co-citations2 shared tech1 shared categorytechnology-and-computing

kennyandpamela.com

1 co-citations2 shared tech1 shared categorytechnology-and-computing

1 co-citations2 shared tech1 shared categorytechnology-and-computing

1 co-citations2 shared tech1 shared categorytechnology-and-computing

1 co-citations2 shared tech1 shared categorytechnology-and-computing

manaitservices.com

1 co-citations2 shared tech1 shared categorysoftware-and-applications

1 co-citations2 shared tech1 shared categorytechnology-and-computing

mangalore-properties.com

1 co-citations2 shared tech1 shared categorytechnology-and-computing

1 co-citations2 shared tech1 shared categorytechnology-and-computing

jackinwater.com

1 co-citations2 shared tech1 shared categorytechnology-and-computing

1 co-citations2 shared tech1 shared categorytechnology-and-computing

javiercastanon.com

1 co-citations2 shared tech1 shared categoryit-and-internet-support

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:

co-citations how often the same third-party websites link out to both — sites referenced together tend to serve the same world.
shared tech how much of their technology stack (CMS, e‑commerce, analytics, frameworks…) overlaps.
shared category whether they sit in the same business / industry category.
positioning how closely their titles and on‑page wording line up.

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.