We Analyzed 11.8 Million Google Search Results: Ranking Factors

Backlinko partnered with Ahrefs, SEMrush, SimilarWeb, and MarketMuse to analyze 11.8 million Google search results, creating one of the most comprehensive ranking factor correlation studies ever conducted. While correlation doesn't prove causation, the study provides valuable insights into patterns that distinguish high-ranking pages from lower-ranked competitors.

Link Authority Correlations

Pages with more referring domains ranked significantly higher than those with fewer backlinks. The relationship between referring domain count and rankings was among the strongest correlations in the study. Notably, the diversity of linking domains mattered more than raw link count, suggesting that broad link acquisition outperforms concentrated link building from few sources.

Domain-level authority (measured by Domain Rating) showed positive correlation with rankings, but page-level link metrics showed stronger correlation. This suggests that while domain authority helps, individual pages still need their own link signals to rank well. New pages on authoritative domains may not automatically rank without page-specific link building.

Content and On-Page Factors

Longer content correlated with higher rankings, with the average first-page result containing approximately 1,447 words. However, the study authors cautioned against interpreting this as "write longer content to rank better." Longer content may simply cover topics more comprehensively, naturally attracting more links and engagement. Content length should be determined by topic requirements rather than arbitrary targets.

HTTPS adoption showed strong correlation with first-page rankings, with the vast majority of top results using secure connections. While HTTPS is a confirmed ranking factor, its near-universal adoption on top-ranking pages likely reflects correlation with overall site quality rather than the modest ranking boost HTTPS provides.

Technical and User Experience Factors

Page loading speed showed modest correlation with rankings. Sites loading in under 3 seconds ranked higher on average than slower sites. The study used time-to-first-byte and full page load metrics. While not the strongest correlation, speed's importance for user experience makes optimization worthwhile regardless of direct ranking impact.

Bounce rate and time on site showed weak correlations that may reflect reverse causation: pages ranking higher naturally receive more qualified traffic that bounces less, rather than low bounce rates causing higher rankings. The study highlighted the challenge of distinguishing cause from effect in engagement metrics.

Interpretation and Application

Correlation studies cannot identify ranking factors definitively. Google's algorithm uses hundreds of signals, many interacting in complex ways that aggregate studies cannot isolate. Use these findings as directional guidance rather than a ranking factor checklist. Focus on factors that improve user experience and naturally attract links rather than optimizing for correlation metrics.

Source: Backlinko