An algorithm that estimates the importance of pages based on link structure.
PageRank evaluates the importance of a page by considering both the quantity and quality of links pointing to it. Though Google now uses hundreds of signals, PageRank remains a foundational concept explaining how authority flows through links. Strong internal linking and earning reputable backlinks help concentrate and distribute authority to priority pages.
| Criteria | Recommended | Notes |
|---|---|---|
| Intent Alignment | Map $pagerank to user journeys and topics | Validate with SERP and on-site behavior |
| Consistency | Encode in components and content standards | Use CMS validations and preview QA |
| Measurement | Track internal CTR, sync signals, conversions | Set guardrails to catch regressions |
Linking from a high-authority page to a new product page to boost visibility
Reducing unnecessary sitewide links that dilute authority
Explains authority flow across a site
Informs internal linking strategy
Guides prioritization of link acquisition
Link from authoritative hubs to key targets
Fix broken and redirecting links that leak authority
Avoid excessive, low-value links on a page
Links that connect one page of a website to another page on the same domain.
A metric predicting how well a specific page will rank in search engine results.
The value or authority passed from one page to another through hyperlinks.
Excess low-value or duplicate URLs in the index that dilute quality and signals.
Meta tag directives like index, noindex, follow, nofollow that guide crawling and indexing.
A file that instructs search engine crawlers which URLs they can or cannot access.
Mathematical representations of text that capture semantic meaning in multi-dimensional space.
RankVectors uses AI-powered semantic analysis to help you implement intelligent internal linking strategies automatically.
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Pages with little unique value, depth, or originality for users.
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