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Internet-Filiale - Sparkasse Marburg-Biedenkopf — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Consumer Banking →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
spk-barnim.de ↗	92 match 1 shared topics	Internet-Filiale - Sparkasse Barnim	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-aachen.de ↗	92 match 1 shared topics	Internet-Filiale - Sparkasse Aachen	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-koblenz.de ↗	92 match 1 shared topics	Internet-Filiale - Sparkasse Koblenz	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-lev.de ↗	91 match 1 shared topics	Internet-Filiale - Sparkasse Leverkusen	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-rhein-nahe.de ↗	91 match 1 shared topics	Internet-Filiale - Sparkasse Rhein-Nahe	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	email phone	none
spk-suedholstein.de ↗	91 match 1 shared topics	Internet-Filiale - Sparkasse Südholstein	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
taunussparkasse.de ↗	90 match 1 shared topics	Internet-Filiale - Taunus Sparkasse	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-re.de ↗	90 match 1 shared topics	Internet-Filiale - Sparkasse Vest Recklinghausen	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-bremen.de ↗	90 match 1 shared topics	Internet-Filiale - Die Sparkasse Bremen AG	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	email phone	none
sparkasse-cgw.de ↗	90 match 1 shared topics	Internet-Filiale - Sparkasse Celle-Gifhorn-Wolfsburg	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-solingen.de ↗	89 match 1 shared topics	Internet-Filiale - Stadt-Sparkasse Solingen	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
stadtsparkasse-oberhausen.de ↗	89 match 1 shared topics	Internet-Filiale - Stadtsparkasse Oberhausen	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
ospa.de ↗	89 match 1 shared topics	Internet-Filiale - OstseeSparkasse Rostock	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	email phone	none
sparkasse-oberlausitz-niederschlesien.de ↗	89 match 1 shared topics	Internet-Filiale - Sparkasse Oberlausitz-Niederschlesien	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-heilbronn.de ↗	89 match 1 shared topics	Internet-Filiale - Kreissparkasse Heilbronn	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sskduesseldorf.de ↗	85 match 1 shared topics	Stadtsparkasse Düsseldorf \| Internet-Filiale für Privatkunden	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
www-naspa.com ↗	81 match 1 shared topics	Nassauische Sparkasse	de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none
sparkasse-mainfranken.de ↗	80 match 1 shared topics	Sparkasse Mainfranken Würzburg \| Ihre Bank für die Region	Germany de	consumer-banking Adobe Experience Manager	robotsllmsaihumans	emailphone	none

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:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

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.