A New Domain Outscored Ahrefs on AI Citation Rate. Here Is How We Measured It. A first-party baseline audit using the AI Visibility Readiness (AVR) Framework found citability.dev achieving a 15% AI citation rate in a 20-query ChatGPT test run April 7, 2026, while ahrefs.com measured 5% on the same protocol run March 31, 2026. The finding supports the hypothesis that AI infrastructure choices matter more than domain authority for AI discoverability, though both results carry LOW confidence labels due to small sample sizes. A New Domain Outscored Ahrefs on AI Citation Rate. Here Is How We Measured It. Domain Authority does not predict whether AI systems will cite your site. A first-party baseline audit using the AI Visibility Readiness AVR Framework showed citability.dev achieving a 15% AI citation rate while ahrefs.com measured 5% on the same 20-query protocol. Why this matters citability.dev a new, low-authority domain achieved a 15% AI citation rate in a 20-query ChatGPT baseline test run April 2026. ahrefs.com achieved 5% on the same protocol tested March 2026. The AI Visibility Readiness AVR Framework produced both measurements with 95% confidence intervals; both results carry LOW confidence labels due to small n. The finding supports the hypothesis that AI infrastructure choices matter more than domain authority for AI discoverability. citability.dev achieved a 15% AI citation rate on a 20-query ChatGPT baseline while ahrefs.com, one of the most authoritative SEO domains in the world, achieved 5% on the same protocol run one week earlier. The finding is direct: AI infrastructure choices matter more than domain authority for AI discoverability, and the gap is measurable with the AVR Framework. The standard playbook for search authority says high Domain Authority equals search visibility. The new SEO reality — where ChatGPT, Perplexity, and Google AI Overviews now answer queries that used to send traffic to article pages — does not follow that playbook. In April 2026, I ran a citation-rate baseline for citability.dev using the AI Visibility Readiness AVR Framework see chudi.dev/framework https://chudi.dev/framework , a first-party audit methodology I built to measure whether a website is discoverable, recommendable, and citable by AI systems. The result: citability.dev was cited in 3 of 20 ChatGPT queries — a 15.0% citation rate. For comparison, I had run the same 20-query citation protocol on ahrefs.com one week earlier, on March 31, 2026. Ahrefs — one of the most authoritative SEO tool domains in the world — was cited in 1 of 20 queries: a 5.0% citation rate. This document is the methodological record for both measurements. The measurements citability.dev citation baseline April 7, 2026 - Queries run: 20 - Platform: ChatGPT OpenAI , web search enabled - Cited: 3 - Citation rate: 15.0% - 95% confidence interval: 5.2, 36.0 percentage points - Confidence label: LOW - Verdict: PARTIALLY CITED source: avr-baseline-2026-04-07/citations citability.dev 20260407 074025 summary.json , field citation rate pct , test date 2026-04-07T07:40:25Z ahrefs.com citation baseline March 31, 2026 - Queries run: 20 - Platform: ChatGPT OpenAI , web search enabled - Cited: 1 - Citation rate: 5.0% - 95% confidence interval: 0.9, 23.6 percentage points - Confidence label: LOW - Verdict: PARTIALLY CITED source: sample-audits/citations ahrefs.com 20260331 160501 summary.json , field citation rate pct , test date 2026-03-31T16:05:01Z What “LOW confidence” means Both results carry a LOW confidence label. With n=20 queries, the 95% Wilson confidence intervals are wide — roughly plus or minus 15 to 20 percentage points. The citability.dev interval 5.2, 36.0 and the ahrefs.com interval 0.9, 23.6 overlap at the edges. What the data supports is directional: citability.dev is being cited where ahrefs.com is not, on queries in the same broad topic space. What it does not support is a precise ratio claim. Tight confidence intervals require larger n; the AVR protocol documentation recommends n=200 for a meaningful operational baseline. What drove the difference The AVR Framework distinguishes between VERIFIABLE checks infrastructure you can prove and BEST-EFFORT checks measured behavior that varies by session . The ahrefs.com infrastructure audit, also run in March 2026, found several gaps that correlate with reduced AI discoverability: no /llms.txt , no schema markup on 5 of 5 checked pages 0% coverage , and partial semantic HTML. These are all VERIFIABLE findings — they do not require querying an AI to observe. citability.dev, by contrast, was built from the start with AI-visible content structure in mind: structured data on key pages, clear heading hierarchy, llms.txt describing the service, and explicit AI crawler allowlisting in robots.txt . The AVR Framework also measured citability.dev’s visibility rate separately from its citation rate. In a 25-query visibility test on April 7, 2026: - Visible in 11 of 25 queries: 44.0% visibility rate - Of which, brand recognition 5/5 queries, 100% , concept attribution 2/10, 20% , and recommendation 4/10, 40% source: avr-baseline-2026-04-07/visibility citability.dev 20260407 074010 summary.json , fields visibility rate pct , by category What the framework measures The AVR Framework v1.1.0 repository: github.com/ChudiNnorukam/ai-visibility-readiness https://github.com/ChudiNnorukam/ai-visibility-readiness , which I also ran against chudi.dev in a full 13-section self-audit with Cloudflare Radar baselines /blog/avr-v1-1-0-cloudflare-radar-full-audit , runs up to 15 automated checks across two sections: Section 1 VERIFIABLE : SEO Foundation Technical crawlability, schema markup coverage, Core Web Vitals, content indexability, content-to-HTML ratio, and semantic HTML structure. These checks produce deterministic pass/fail results from public data. Section 2 VERIFIABLE : AI Infrastructure AI crawler access permissions GPTBot, ClaudeBot, PerplexityBot, Google-Extended , /llms.txt presence, structured data depth across 5 sampled pages, content structure for AI parsing, and semantic HTML depth. Section 3 BEST-EFFORT : Citation Monitoring Live citation tests across ChatGPT and optionally Perplexity, reported with n, citation rate, and 95% Wilson confidence intervals. Results carry a mandatory confidence label LOW / MODERATE / HIGH based on round count and the disclaimer that AI citation behavior varies by session, platform, and location. These are point-in-time observations, not audit verdicts. The three-band verdict AI-READY / FOUNDATION-READY / NOT-READY is driven by Section 1 and 2 findings only. It is not a composite score; it is a categorical readiness classification. Replicating these measurements Both citation baselines were produced by running scripts/citation auto.py in the AVR repository against the target domain with a set of 20 domain-appropriate queries. The script queries ChatGPT via the OpenAI API with web search enabled, checks whether the target URL appears in each response’s citations, and outputs the summary JSON with Wilson CI. To run your own baseline: - Clone github.com/ChudiNnorukam/ai-visibility-readiness https://github.com/ChudiNnorukam/ai-visibility-readiness - Install dependencies pip install -r requirements.txt - Set OPENAI API KEY in your environment - Run python scripts/citation auto.py