Domain Authority Checker
Check and compare domain authority scores for competitive SEO analysis. Enter values for instant results with step-by-step formulas.
Calculator
Adjust values & calculateFormula
Domain Authority is estimated using a logarithmic model inspired by Moz's methodology. Each factor is scored on a weighted scale: backlinks (up to 30 points), referring domain diversity (up to 30 points), domain age (up to 15 points), content volume (up to 10 points), and organic traffic (up to 15 points). The logarithmic scale reflects the diminishing returns of additional links.
Last reviewed: December 2025
Worked Examples
Example 1: Mid-Size Business Blog
Example 2: New Startup Website
Background & Theory
The Domain Authority Checker applies the following established principles and formulas. Search engine optimisation and digital marketing performance is quantified through a hierarchy of interconnected metrics. Click-through rate (CTR) divides the number of clicks on a link by the number of times it was shown (impressions), expressing how compelling a headline, ad, or meta description is at a given position. Industry average organic CTR for the top Google result sits around 28 to 35 percent, declining sharply with rank. Cost-per-click (CPC) is the average amount paid each time a user clicks a paid advertisement, calculated by dividing total ad spend by total clicks. Return on ad spend (ROAS) divides total revenue attributed to advertising by total ad spend; a ROAS of 4 means $4 in revenue for every $1 spent. Conversion rate divides completed goal actions (purchases, sign-ups, downloads) by total sessions or unique visitors, bridging traffic metrics to business outcomes. Keyword difficulty scores (typically 0 to 100) estimate how competitive it would be to rank organically for a given search term, based on the authority of pages currently ranking in the top results. PageRank, the algorithm Google was originally built on, modelled the web as a directed graph and assigned each page an authority score proportional to the number and quality of inbound links, treating a link as a vote of confidence weighted by the linking page's own authority. The Flesch Reading Ease formula scores text legibility on a 0 to 100 scale using sentence length and syllable count per word. Higher scores indicate easier reading; most consumer-oriented web content targets scores above 60. Bounce rate measures the percentage of sessions in which a user leaves without triggering a second page view, though its interpretation depends heavily on page purpose. Email open rate benchmarks vary significantly by industry, averaging around 20 to 25 percent across sectors. Social media engagement rate divides total interactions (likes, comments, shares) by total reach or follower count, assessing content resonance beyond simple impression counts.
History
The history behind the Domain Authority Checker traces back through the following developments. Before algorithmic search engines, web navigation relied on manually curated directories maintained by human editors. Yahoo launched its categorised directory in 1994 and briefly dominated web discovery by organising sites into a hierarchical taxonomy. Early automated search engines including AltaVista and Excite ranked pages using keyword frequency in on-page content, which immediately spawned keyword stuffing as the first widespread manipulation tactic: publishers repeated target phrases hundreds of times, sometimes rendered in white text on a white background to hide them from readers while remaining visible to crawlers. Google's founding in 1998 by Larry Page and Sergey Brin at Stanford introduced PageRank, a link-graph authority algorithm that shifted ranking signals away from easily gamed on-page text toward the harder-to-fabricate structure of inbound links. This dramatically improved result quality and positioned Google as the dominant search engine within three years of launch. The growing commercial value of first-page rankings created a professional SEO industry that reverse-engineered ranking signals, built link farms, and pursued aggressive anchor text optimisation. Google responded to systematic manipulation with major named algorithm updates: Panda in 2011 penalised low-quality, thin, and duplicate content; Penguin in 2012 targeted unnatural link patterns and link schemes; and Hummingbird in 2013 introduced deep semantic parsing to match query intent rather than literal keyword strings. These updates collectively shifted SEO best practice toward genuine content quality, topical depth, and user experience signals. Facebook launched its self-service advertising platform in 2007, enabling granular demographic, interest, and behavioural targeting at scale for the first time. Social media marketing matured into a distinct professional discipline through the 2010s. Google formalised mobile-first indexing in 2016 and made Core Web Vitals official ranking signals in 2021. From 2023 onward, AI Overviews began surfacing synthesised answers atop search results, creating a zero-click environment that fundamentally challenged traffic-dependent content business models.
Frequently Asked Questions
Sources & References
Formula
DA = f(log(backlinks), log(referring domains), age, log(pages), log(traffic))
Domain Authority is estimated using a logarithmic model inspired by Moz's methodology. Each factor is scored on a weighted scale: backlinks (up to 30 points), referring domain diversity (up to 30 points), domain age (up to 15 points), content volume (up to 10 points), and organic traffic (up to 15 points). The logarithmic scale reflects the diminishing returns of additional links.
Worked Examples
Example 1: Mid-Size Business Blog
Problem: Estimate DA for a site with 2,500 backlinks, 180 referring domains, 4 years old, 200 pages, and 5,000 monthly organic visits.
Solution: Backlink score: log10(2501) x 8 = 27.2 (cap 30)\nReferring domains: log10(181) x 10 = 22.6 (cap 30)\nAge score: 4 x 1.5 = 6.0 (cap 15)\nPage score: log10(201) x 4 = 9.2 (cap 10)\nTraffic score: log10(5001) x 3.5 = 12.9 (cap 15)\nTotal raw = 27.2 + 22.6 + 6.0 + 9.2 + 12.9 = 77.9\nEstimated DA = 78
Result: Estimated DA: 78 — Strong authority, well-established site
Example 2: New Startup Website
Problem: Estimate DA for a site with 50 backlinks, 25 referring domains, 1 year old, 30 pages, no significant traffic yet.
Solution: Backlink score: log10(51) x 8 = 13.7\nReferring domains: log10(26) x 10 = 14.1\nAge score: 1 x 1.5 = 1.5\nPage score: log10(31) x 4 = 6.0\nTraffic score: 0\nTotal raw = 13.7 + 14.1 + 1.5 + 6.0 + 0 = 35.3\nEstimated DA = 35
Result: Estimated DA: 35 — Building phase, needs more referring domains
Frequently Asked Questions
What is Domain Authority (DA) and how is it calculated?
Domain Authority is a search engine ranking score developed by Moz that predicts how likely a website is to rank in search engine result pages (SERPs). Scored on a logarithmic scale from 1 to 100, DA is calculated using multiple factors including the number and quality of inbound links, referring domain diversity, domain age, and various other signals. The logarithmic scale means improving from DA 20 to 30 is significantly easier than improving from 70 to 80. It is important to understand that DA is a relative metric, not an absolute one — it is most useful for comparing websites in competitive analysis rather than as a standalone quality indicator. Google does not use DA as a ranking factor, but the underlying signals DA measures are important.
What is the difference between Domain Authority and Page Authority?
Domain Authority (DA) measures the overall ranking strength of an entire domain or website, while Page Authority (PA) measures the ranking strength of a single specific page. A website might have a high DA of 70 but individual blog posts with PA scores ranging from 20 to 50, depending on how many links each page has earned. When building links, you want links from high-DA domains pointing to your specific pages. A homepage link from a DA 50 site is typically more valuable than an internal blog link from a DA 80 site. Both metrics use similar calculations but at different scope levels. For competitive analysis, DA helps identify strong competitor domains, while PA helps identify their strongest individual content pieces.
How can I improve my domain authority score?
Improving DA requires a sustained, multi-faceted approach to link building and content strategy. First, create exceptional linkable assets — original research, comprehensive guides, free tools, and infographics that naturally attract backlinks. Second, pursue strategic guest posting on relevant, high-authority sites in your niche. Third, build relationships with journalists and bloggers through platforms like HARO (Help A Reporter Out) to earn editorial mentions. Fourth, conduct broken link building by finding dead links on authoritative sites and offering your content as a replacement. Fifth, ensure your technical SEO is solid: fast loading times, mobile responsiveness, proper site architecture, and clean internal linking. Disavow toxic or spammy backlinks that could drag your score down.
Why is referring domain diversity important for SEO?
Referring domain diversity — the number of unique websites linking to yours — is one of the strongest ranking signals in modern SEO. Having 100 backlinks from 100 different domains is significantly more valuable than 100 backlinks from a single domain. Search engines interpret links from diverse sources as broader validation of your content quality and relevance. A natural backlink profile typically shows a ratio of 2-5 total backlinks per referring domain. Extremely high ratios (like 50:1) might indicate link schemes or sitewide footer links that carry less value. Focus your link building efforts on acquiring links from new domains rather than multiple links from domains you already have, as each additional link from the same domain provides diminishing returns.
How does domain age affect search rankings and authority?
Domain age contributes to authority through several mechanisms. Older domains have had more time to accumulate backlinks, build brand recognition, and establish trust signals. Google has confirmed that domain age itself is not a direct ranking factor, but the accumulated history and link profile of an older domain provides indirect benefits. A 10-year-old domain with a consistent history of quality content and natural link growth will typically outrank a 6-month-old domain on similar topics, all else being equal. However, domain age alone does not guarantee rankings — a new domain with excellent content and strong link building can outperform an aged but neglected competitor. The key is the cumulative quality of signals built over time, not the calendar age itself.
Is my data stored or sent to a server?
No. All calculations run entirely in your browser using JavaScript. No data you enter is ever transmitted to any server or stored anywhere. Your inputs remain completely private.
References
Reviewed by Daniel Agrici, Founder & Lead Developer · Editorial policy