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Google Search Quality Raters Guidelines

Definition

The Search Quality Rater Guidelines is a 175-page document published by Google that outlines the criteria human raters should use to evaluate the quality of websites and web pages. These raters assess pages on dimensions like expertise, authoritativeness, trustworthiness, and ability to meet the user’s needs.

Their job helps Google refine its algorithms by evaluating the quality of search results. The guidelines outline what Google considers lowest, low, high, and highest quality web content and helps rate search results based on factors such as usefulness, relevance, reliability, overall user experience, and ability to meet user’s needs.

The Google’s QRG also introduce interesting concepts like Page Quality (PQ), and Experience, Expertise, Authoritativeness, and Trustworthiness (E-E-A-T.)

Search Quality Raters Guidelines Relevance For SEO

While raters’ assessments do not directly impact search rankings, their input helps Google improve its algorithms over time. So understanding raters’ quality criteria offers insight into what Google’s systems may prioritize. Key relevant dimensions include E-E-A-T (experience, expertise, authoritativeness, and trustworthiness) and needs met. Optimizing for these can help sites fare better in search.

Google Search Quality Raters Guidelines Best Practices for SEO

Some best practices that align with raters’ guidelines:

  • Clearly communicate expertise in your space through content and design.
  • Highlight author credentials and trust signals like contact info and about pages.
  • Ensure content depth, accuracy and freshness meets or exceeds user needs.
  • Follow expert-recommended practices and standards for your field.
  • Avoid misleading design tactics, over-commercialization, or thin content.
  • Monitor aggregated user feedback and fix issues impacting satisfaction.

Adhering to raters’ standards, while not a direct ranking factor, can help sites create content aligned with Google’s ideals of quality. This makes positive algorithmic assessments more likely over time.

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