A comprehensive study by SE Ranking has shed light on the key factors influencing how often ChatGPT cites a website. Analyzing 129,000 unique domains and over 216,000 pages across 20 niches, the research reveals that traditional SEO signals like referring domains, website traffic, and domain trust scores are highly correlated with AI visibility. The findings offer valuable insights for publishers and SEO professionals aiming to optimize their content for generative AI platforms.
Backlinks and Trust Signals
The study identified the number of referring domains as the single strongest predictor of a site's likelihood to be cited by ChatGPT. Sites with a diverse backlink profile, boasting over 350,000 referring domains, averaged 8.4 citations, significantly higher than the 1.6–1.8 citations for sites with up to 2,500 referring domains. A notable threshold effect was observed at 32,000 referring domains, where citations nearly doubled from 2.9 to 5.6.
Domain Trust scores mirrored this pattern, with sites scoring 97–100 averaging 8.4 citations, compared to 1.6 for those below 43. Interestingly, Page Trust had less impact than overall domain authority. Pages with a Page Trust score of 28 or higher showed similar citation rates, suggesting ChatGPT prioritizes a website's broader credibility.
Contrary to common assumptions, the study found that .gov and .edu domains did not automatically outperform commercial sites. Government and educational domains averaged 3.2 citations, while sites without these designations averaged 4.0. The researchers emphasized that
“What ultimately matters is not the domain name itself, but the quality of the content and the value it provides.”
Traffic and Google Rankings
Domain traffic emerged as the second most crucial factor, though its correlation with ChatGPT citations only became significant at higher volumes. Websites with fewer than 190,000 monthly visitors showed little variation in citation rates (2 to 2.9), regardless of exact traffic. However, domains exceeding 10 million visitors averaged 8.5 citations. Specifically, homepage traffic played a vital role, with sites receiving at least 7,900 organic visitors to their main page exhibiting the highest citation rates.
A site's average Google ranking position also tracked closely with ChatGPT citations. Pages ranking between positions 1 and 45 averaged 5 citations, while those ranking 64 to 75 averaged 3.1. This suggests, as the authors noted, that
“While this doesn’t prove that ChatGPT relies on Google’s index, it suggests both systems evaluate authority and content quality similarly.”
Content Quality and Structure
Content depth consistently correlated with increased citations. Articles exceeding 2,900 words averaged 5.1 citations, outperforming those under 800 words (3.2 citations). Beyond raw length, structure proved important: pages with section lengths of 120 to 180 words between headings performed best, averaging 4.6 citations.
The inclusion of expert quotes boosted citations (4.1 vs. 2.4 for those without), as did comprehensive statistical data (5.4 citations for 19+ data points vs. 2.8 for minimal data). Content freshness was a clear indicator, with pages updated within three months averaging 6 citations, significantly more than outdated content (3.6).
Surprisingly, pages with FAQ sections received slightly fewer citations (3.8) than those without (4.1). However, the predictive model viewed the absence of an FAQ section as a negative signal, suggesting this discrepancy might arise because FAQs often appear on simpler support pages that naturally earn fewer citations. Furthermore, question-style headings (e.g., H1s or H2s) underperformed straightforward headings (3.4 vs. 4.3 citations), contradicting standard voice search optimization advice and implying AI models may prefer direct topical labeling.
Social Signals and Review Platforms
Brand mentions on discussion platforms like Quora and Reddit showed a strong correlation with ChatGPT citations. Domains with extensive Quora presence (6.6 million mentions) corresponded to 7.0 citations, compared to 1.7 for minimal presence. Reddit displayed similar trends. This finding is particularly relevant for smaller sites, as the authors stated:
“For smaller, less-established websites, engaging on Quora and Reddit offers a way to build authority and earn trust from ChatGPT, similar to what larger domains achieve through backlinks and high traffic.”
Presence on major review platforms such as Trustpilot, G2, Capterra, Sitejabber, and Yelp also correlated positively. Domains listed on multiple review platforms averaged 4.6 to 6.3 citations, while those absent averaged only 1.8.
Technical Performance
Page speed metrics were also linked to citation likelihood. Pages with a First Contentful Paint (FCP) under 0.4 seconds averaged 6.7 citations, significantly more than slower pages (over 1.13 seconds) which averaged 2.1. Speed Index showed similar patterns, with sites below 1.14 seconds performing well.
A counterintuitive observation was made regarding Interaction to Next Paint (INP) scores: pages with the fastest INP (under 0.4 seconds) received fewer citations (1.6 average) than those with moderate scores (0.8 to 1.0 seconds, averaging 4.5 citations). Researchers suggested that extremely simple or static pages might not signal the depth ChatGPT seeks in authoritative sources.
URL and Title Optimization
The report revealed that broad, topic-describing URLs outperformed keyword-optimized ones. Pages with low semantic relevance between their URL and target keyword (0.00 to 0.57 range) averaged 6.4 citations, whereas those with the highest relevance (0.84 to 1.00) averaged only 2.7. Titles followed this pattern, with low keyword matching titles averaging 5.9 citations compared to 2.8 for highly optimized ones. The researchers concluded:
“ChatGPT prefers URLs that clearly describe the overall topic rather than those strictly optimized for a single keyword.”
Factors with Minimal Impact
Several commonly recommended AI optimization tactics showed minimal or even negative correlation with citations. These included FAQ schema markup (pages with it averaged 3.6 citations vs. 4.2 without), LLMs.txt files, and outbound links to high-authority sites, all of which had negligible effects on citation likelihood.
Implications for AI Content Optimization
These findings suggest that a robust, existing SEO strategy largely aligns with the goals of AI visibility. Websites focusing on building referring domains, earning organic traffic, maintaining fast page speeds, and consistently updating high-quality content are already addressing the most predictive factors for ChatGPT citations. For smaller sites lacking extensive backlink profiles, the research highlights community engagement on platforms like Reddit and Quora as a viable alternative for building authority signals. The data also underscores the importance of content depth and value over strict keyword density.
It's crucial to remember that these factors are interdependent; optimizing one signal while neglecting others will reduce overall effectiveness. The study specifically analyzed ChatGPT, and other AI systems may weigh these factors differently. Furthermore, SE Ranking did not specify the ChatGPT version or timeframe, so these patterns should be interpreted as directional correlations rather than definitive rules for ChatGPT's internal ranking algorithm.
