Duplicate content
Same or near-identical content on multiple URLs.
What duplicate content means
Duplicate content is the same or very similar content appearing at more than one URL, either on your own site or across different sites. Much of it is technical and innocent, such as print versions, tracking parameters or a product listed in two categories. Google usually picks one version to show and filters the rest. Its guide to canonicalisation covers how to state your preference.
Seen in practice
A furniture retailer's product descriptions are copied from the manufacturer, so the same text appears on dozens of other shops. Google has no reason to prefer this retailer's page. Adding its own measurements, photos, delivery details and buying advice gives the pages something other sites don't have.
Why it matters for your content
There's no general "duplicate content penalty" for normal technical duplication. The cost is dilution: Google may pick the wrong version, and links and signals may be split. Deliberately copied or mass-duplicated content is different, and can fall under spam policies.
Checking your own pages
Search a distinctive sentence from one of your pages in quotation marks. If many sites show the same text, it isn't unique. On your own site, Search Console's URL Inspection tool shows which URL Google chose as canonical. Crawling tools can flag pages with duplicate titles or near-identical body text.
Traps to avoid
- Using supplier descriptions unchanged across a whole shop.
- Leaving both "www" and non-"www", or HTTP and HTTPS, versions accessible without redirects.
- Publishing the same article on several of your own sites.
- Panicking about small amounts of repeated text such as legal disclaimers.
Related content terms
- Canonical URL: The preferred URL for duplicate or similar content, declared with rel=canonical.
- Canonicalisation: Choosing and declaring the preferred URL among duplicates.
- Thin content: Pages with little original value, a common problem with mass-produced pages.
- Doorway page: Pages built mainly to rank for similar queries and funnel users elsewhere.
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