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Authority and Trust

PageRank

Definition

PageRank is Google's foundational algorithm, originally developed by Larry Page, that measures the importance and authority of a web page based on the quantity and quality of pages linking to it-treating links as votes, with votes from important pages counting more. While PageRank remains a core component of Google's ranking systems, its public Toolbar PageRank was discontinued in 2016. Third-party metrics like Domain Authority and URL Rating approximate PageRank-like signals but are not the same measure.

Why It Matters

PageRank's core logic-that links from authoritative pages confer more authority than links from low-authority pages-remains central to how Google evaluates trustworthiness and ranking potential. Building high-quality inbound links from authoritative domains builds PageRank-equivalent authority that benefits both traditional search rankings and AI system trust evaluations, which use similar authority signals.

How It Works

PageRank is calculated iteratively: each page distributes its PageRank score equally among all pages it links to (following links only). This creates a system where pages linked to by many high-PageRank pages receive high PageRank themselves. The algorithm converges to a stable distribution reflecting the link graph's structure. Google's actual ranking system layers hundreds of additional signals on top of this PageRank foundation.

Use Cases

  • Link building campaigns prioritizing links from established domains with strong backlink profiles
  • Internal link audits ensuring highest-priority pages receive link equity from high-PageRank internal pages
  • Competitive analysis identifying why competitors rank despite lower content quality-often superior link authority
  • Domain acquisition evaluating whether target domains have strong historical PageRank accumulated through quality links
  • Content creation strategy focusing on link-earning formats to build PageRank-equivalent domain authority

Best Practices

  • Prioritize acquiring links from domains with high domain authority (DA/DR as PageRank proxies) in your topic space
  • Focus on relevance alongside authority-a link from a highly relevant mid-authority domain often outperforms an irrelevant high-authority link
  • Use internal linking to channel external PageRank to your most important commercial pages
  • Build a diverse, natural-looking link profile rather than concentrating links from single domains
  • Track domain authority trends using Ahrefs DR, Moz DA, or Semrush AS as PageRank proxies
  • Create linkable assets (data, tools, original research) that naturally earn high-authority inbound links

Frequently Asked Questions

Is PageRank still relevant in 2025? +
Yes. While Google has discontinued public PageRank scores and evolved far beyond the original algorithm, the foundational principle-that authoritative inbound links increase a page's trustworthiness and ranking potential-remains central to Google's systems. Internal Google documentation confirmed in recent years that PageRank-derived signals remain among the most important ranking factors.
What's the difference between PageRank and Domain Authority? +
PageRank is Google's internal algorithm measuring page authority based on its link graph. Domain Authority (DA) is Moz's proprietary metric that attempts to predict ranking potential by modeling PageRank-like signals from publicly available link data. DA correlates with ranking ability but is not the same as Google's internal PageRank-use it as a directional indicator, not an absolute measure.
Does PageRank affect AI citation selection? +
Indirectly yes. High-PageRank domains rank more strongly in organic search, and AI systems like Google AI Overviews draw heavily from highly-ranked content. Additionally, AI systems use domain authority signals (which correlate with PageRank) when evaluating source trustworthiness for citation. Building PageRank-equivalent domain authority improves both traditional search performance and AI citation probability.

Related Terms

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