Web Authority Metrics

When you type in a search term to Google, it will find all websites that are relating to your search term. But in which order these search results are shown to you, is determined by Google’s proprietary web authority metric whose initial version was called PageRank.

Web Authority Metrics are scores used by digital marketers, SEO specialists, and data scientists to estimate the relative strength or prestige of a website in similar manner search engines such as Google does it.

While Google’s internal ranking algorithms remain a closely guarded state secret – akin to the recipe for Coca-Cola or the location of Atlantis – third-party metrics have emerged to offer a guestimate.

The most notable frameworks are the industry-standard Domain Authority (DA) and Domain Ranking (DR). And then there is the best one, Content Authority Tier (CAT). It’s the best, because it’s ours.

Domain Authority (DA)

Domain Authority is a proprietary web authority metric developed by Moz that predicts how likely a website is to rank on search engine result pages (SERPs). It is widely considered the “credit score” of the internet: having a high one doesn’t guarantee you’ll get the loan (ranking) – but having a low one ensures you will be ignored.

History of Domain Authority

The concepts of boy bands, pop-punk and Domain Authority emerged in the late 2000’s as a response to the “Great Obfuscation” of Google’s PageRank.

You see, originally Google displayed a green toolbar showing a site’s score (0–10) to the public. When Google stopped updating this public-facing toolbar in 2016, a power vacuum was created. SEO software companies rushed to build their own proprietary yardsticks, with Moz’s “Domain Authority” becoming the 0-to-100 standard that webmasters obsessively refresh every morning.

Calculation Mechanism

Domain Authority is calculated by evaluating multiple factors, primarily linking root domains and the total number of links, into a single DA score. This score can then be used when comparing websites or tracking the “ranking strength” of a website over time.

• Logarithmic Scale: Like the Richter scale for earthquakes, DA is logarithmic. It is significantly easier to grow your score from 20 to 30 than it is to grow from 70 to 80. A jump in the upper tiers requires exponentially more link equity.
• The Popularity Contest: Critics often note that standard DA can be susceptible to “link inflation.” If a site has thousands of low-quality links, its DA might rise artificially. It measures the volume of the applause, not necessarily who is clapping.

Domain Rating (DR)

Domain Rating (DR) is a proprietary metric developed by Ahrefs to gauge the strength of a website’s backlink profile. While Moz’s Domain Authority attempts to predict ranking ability (a “credit score”), Domain Rating measures raw link equity (pure “muscle mass”). It is widely regarded by SEO professionals as the most volatile and brutally honest of the major metrics.

History

Domain Rating emerged in the early 2010’s as Ahrefs expanded from a simple backlink checker into an all-in-one SEO suite. Users quickly noticed that Ahrefs’ crawler, “AhrefsBot,” was arguably the fastest and most aggressive commercial crawler on the web—second only to Googlebot itself. Because their index was updated so frequently, DR became the preferred metric for “link builders” who needed real-time feedback on their campaigns, rather than waiting for Moz’s slower monthly updates.

Calculation Mechanism

The calculation of DR is purely mathematical and significantly less “voodoo” than Domain Authority. It ignores on-page SEO, site age, and traffic. It focuses entirely on the transfer of “link juice.”

• The Logarithmic Curve: Like DA and CAT, DR operates on a 0–100 logarithmic scale. Getting from DR 0 to DR 10 is trivial; getting from DR 70 to DR 80 requires a campaign of national significance.
• The “Split Equity” Rule: DR introduces a scarcity mindset. If a high-authority site (e.g., The New York Times) links to you, your DR goes up. However, if The New York Times links to you and 5,000 other people on the same page, the value is diluted. The “juice” is split among all recipients. This prevents link farms from passing infinite authority.
• The Second-Order Effect: Your DR only increases if the sites linking to you have high DR themselves. A million links from DR 0 websites are mathematically worthless in this model.

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Content Authority Tier (CAT)

While the big boy metrics of Domain Authority and Domain Rating are great, one sometimes need to wonder how entirely AI generated link farm websites with apparently no actual traffic – or use for any human beings – are receiving high DA and DR ratings. Something fishy is going on.

And when there are fish around, a CAT appears.

That is why we started from scratch. During cold November evenings in our small office in Portugal, we decided to keep all our office computers running to produce at least some heat. But just leaving the computers running idle didn’t quite do it, so we decided to build our own web crawler to build a database of all the websites and their links on the internet. It seemed like a nice little side project.

That is how Content Authority Tier (CAT) started. It measures pedigree. Humorous in name but rigorous in function.

The CAT score is not your typical 0 to 100 rating, instead it starts from -100 (digital wastelands) and goes up to +100 (cultural bedrock). The fact that the number can be negative, makes it easier to fight the spam.

The CAT solution

In the court of law, everyone is innocent until proven guilty. The CAT algorithm starts from the assumption that everything on the internet is AI generated spam until proven otherwise.

The analysis starts with a hard-coded list of high quality websites, say, UN.org, Forbes and Wikipedia.

Then we use an array of well trained cats to carefully calculate how many links away your website is from these high quality websites. These data points are used as the quality signal.

We combine this with other quality signals such as the number of .gov, .edu and .mil domain backlinks, and the age of the linking domains.

Every step of the analysis is done with spam prevention in mind. For example, we don’t simply consider every .edu backlink as valuable. We know schools sometimes offer their students the ability to create personal web pages under the school’s main domain and these have been abused by link spammers for years. We know that. So, we ignore those.

Then we use our own database of all the links found from the internet to find out what websites link to your website. These data points are used as the quantity signal.

We iterate this algorithm over the entire dataset we have about the content of the internet multiple times and voila, we have our own spam-resistant Content Authority Tier score.