What is Rank, Domain from Rank, and Page from Rank in Backlinks API?

In the DataForSEO Backlinks API, Rank is the key metric for estimating the authority of a domain, page, or backlink based on its backlink profile. If you are looking for an alternative to Ahrefs Domain Rating (DR), Rank is the DataForSEO Backlinks API metric you should use. Other Ahrefs API backlink profile fields, such as domain rating, referring domains, and anchor text, also have equivalents among the backlink metrics returned by Backlinks API. You’ll find them in the field mapping below. It is the DataForSEO equivalent that serves the same purpose: helping you evaluate and compare backlink authority across domains and pages, build backlink analysis tools, SEO dashboards, reports, or optimization workflows. Please note that DataForSEO Rank and Ahrefs DR are calculated using different methodologies, so their values should not be expected to match directly.

The Logic Behind Backlinks API Rank Metrics

Every SEO professional is familiar with PageRank.

PageRank is Google’s algorithm designed to measure the importance of a webpage based on the quality and quantity of webpages that refer to it. Pages that have higher PageRank (i.e., a large number of quality backlinks) are perceived as more authoritative by Google and rank better than those with lower PageRank.

For a long time, PageRank was a public metric — an SEO could download the Toolbar PageRank Chrome extension and estimate the importance of their webpages. However, in 2016, Google removed the extension from its browser and made the score unavailable, much to the dismay of SEO experts. Soon after this, many software providers began designing their own backlink-related indicators, providing the alternative to Google’s original PageRank score that SEOs can rely on.

Using Backlinks API, you could also develop a backlink analysis tool with indicators closely related to PageRank.

In its endpoints, you will discover various metrics estimating the authoritativeness of a page or domain based on its backlink profile. These metrics are rank, domain_from_rank, and page_from_rank. They can become an acceptable alternative to PageRank, as we use Google’s original PageRank formula when calculating them.

What is Rank in Backlinks API? Rank, Domain from Rank, and Page from Rank Explained

Each of the three Rank fields scores something different in our API responses:

• rank is the authority score of whatever a given endpoint reports on. In Summary and Bulk Ranks, that is the target you sent. In endpoints that return lists of links, referring domains, networks, or anchors, it is the share of authority each list item passes to your target;
• domain_from_rank is the rank of the referring domain, the whole website where a link to your target was found. It measures the strength of the source site, however little of that strength reaches you;
• page_from_rank is the rank of the referring page, the single URL that contains the link to your target. Two links from the same website can get different page_from_rank values when one sits on a well-linked page and the other on a page with almost no inbound links.

Take one backlink from https://news.example.com/review/ to your product page. In the Backlinks endpoint response, domain_from_rank scores news.example.com, page_from_rank scores the /review/ URL, and rank shows how much of that page’s authority this one link passes to your product page. The referring page splits its authority across all of its outbound links, so the backlink’s rank is usually lower than the page_from_rank of the page it sits on.
 
The definition of rank depends on the specific endpoint

The rank values range from 0 (no backlinks detected) to 1000 (large number of quality backlinks).

Ahrefs to DataForSEO Field Mapping: Backlink Metrics Returned by Backlinks API

If you’re replacing another backlink checker API in an existing product, you need to know which of our fields fills each column your users already see. The backlink checker API fields people ask about most often are Domain Rating, URL Rating, referring domains, and anchor text. Each row puts the field name from Ahrefs API v3 Site Explorer responses next to the field our API returns, so you can map your data model column by column.

If you need an API for referring domains and anchor text, use Bulk Referring Domains for counts across up to 1,000 targets per request, Referring Domains for the list of linking sites, and Anchors, our anchor text API. Request examples that keep only dofollow links are in our guide on checking dofollow referring domains and backlinks.

Swapping Domain Rating for Rank in Your Product

Once the fields are mapped, a few product settings usually need adjusting:

• If your tables and filters expect 0–100 values, pass "rank_scale": "one_hundred" in every request. The conversion is explained below;
• Existing thresholds don’t carry over. A “DR 50+” filter (domain_rating ≥ 50 in Ahrefs API terms) has no fixed rank equivalent, so pull rank through Bulk Ranks for a sample of domains your users already know and set new cutoffs from that distribution;
• A referring site’s rank in Referring Domains can be lower than its rank in Summary, and both values are correct (here’s why). Give the two separate column names, since users may otherwise compare passed authority with site authority.

The metrics are calculated based on the original method for node ranking in a linked database — the core principle behind Google’s PageRank algorithm. The exact formula is provided below.

How is the Rank of a page calculated?

To calculate the rank of a page, we use the original PageRank formula.

Here it is:

PR(A) = (1-d) + d (PR(T1)/C(T1) + … + PR(Tn)/C(Tn))

To understand what variables are used in it, we have to refer to Google’s explanation:

We assume page A has pages T1…Tn which point to it (i.e., are citations). The parameter d is a damping factor which can be set between 0 and 1. We usually set d to 0.85. …Also C(A) is defined as the number of links going out of page A.

In a nutshell, Google considers the following factors when calculating PageRank:

• The quantity of inbound linking pages;
• The number of outbound links on each linking page;
• The PageRank of each linking page;
• The damping factor, simulating the probability of a random user continuing to click on links as they browse the web (it is perceived to decrease with each link click).

 
Note that “PageRank can be calculated using a simple iterative algorithm and corresponds to the principal eigenvector of the normalized link matrix of the web.” It means that Google’s PageRank algorithm can calculate the PR of a page without knowing the definitive PageRank of the referring pages. This is because PageRank isn’t an absolute score, but rather a relative measure of a webpage’s quality compared to every other page in the linking database (or simply the web). You can learn more about the mathematics behind the algorithm in this article.

Backlinks API uses the same formula and thus takes into account the identical factors when calculating rank.

However, we always set a damping factor to 0.5

Having a rapidly growing backlink index with more than 121,000,000,000 pages allows us to calculate rank virtually for any page on the web. Current index figures are on the Our Data page.

Assume this article has backlinks from 3 pages. We know that:

• The first page has a PR of 400 and 32 outbound links in total;
• The second page has a PR of 300 and 40 outbound links in total;
• The third page has a PR of 200 and 5 outbound links in total.

 
Let’s calculate the PR of this page using the above variables:

PR of this page = (1 – 0.5) + 0.5 (400 / 32 + 300 / 40 + 200 / 5), which would be 30.5. Then, we should convert the number to integer, which is 30. That would be the rank of this page.

The third page has the lowest PR of the three, yet it contributes 40 of the 60 points inside the brackets because it splits its authority among only 5 outbound links. You’ll see the same effect in real data: a link from a page with few outbound links can pass more rank than a link from a stronger page that links out to dozens of sites.

Please note that not all backlinks are equal. Depending on the types of backlinks, they may pass all of their PageRank or don’t pass it at all.

• A 301 link passes all of its PageRank to a destination page. For example, if the PR of Page A is 400 and this page is linked to Page B through 301 redirect, the PR of Page B will also be 400;
• A 302 link passes the same amount of PageRank as a regular backlink (see the formula above);
• a canonical URL passes all of its PageRank to a destination page;
• a link with the “nofollow” attribute doesn’t pass PageRank; however, it is still considered as a backlink by our system;
• a link with the “ugc” attribute doesn’t pass PageRank; however, it is still considered as a backlink by our system;
• a link with the “sponsored” attribute doesn’t pass PageRank; however, it is still considered as a backlink by our system.

How is the Rank of a domain calculated?

The rank of a domain is the normalized sum of PRs of its indexed pages. To provide it, the API first calculates the rank of each page the domain has, sums the values up, and then computes the log of the rank values to compress them to a narrow range on a logarithmic scale.
Each point on the scale is hence more difficult to achieve. For example, it is relatively easy to move from 100 to 101, but the 500 to 501 transition would require a lot more effort (and backlinks).

Domain Rank Scale

Here are typical rank scores for domains of different sizes, with their approximate values on the 0–100 scale from the next section, so you can set them next to DR-style scores.

Using the rank_scale parameter in Backlinks API

By default, the rank, domain_from_rank, and page_from_rank values are presented on a 0–1000 scale in the results. However, you can change the scale to 0–100 using the rank_scale parameter in the request.

When you specify the rank_scale parameter as one_hundred, all of the rank values in the response will be converted and displayed as values on a 0–100 scale. To convert and validate the rank values, we utilize the following formula:

sin(rank / 636.62) * 100

In this formula, rank stands for rank, domain_from_rank, or page_from_rank values calculated using the 0–1000 scale, and 636.62 is our proprietary coefficient for correctly interpreting the values on a 0–100 scale.

For example, if the domain rank is 694 on the 0–1000 scale, then after applying the formula it becomes: sin(694 / 636.62) * 100 = 88.6, which will be rounded to the nearest whole number and displayed as 89.

With this coefficient, a rank of 1000 converts to exactly 100. The curve rises fastest at the low end and flattens toward the top: 100 becomes 16, 300 becomes 45, and 500 becomes 71. Small and mid-size sites therefore spread across most of the 0–100 range, while the largest domains sit close together near the top. Converted values still won’t match Ahrefs DR for the same site, because the conversion changes the scale and leaves the underlying score as it is.

Backlinks API Metrics Glossary

Rank is one of several backlink metrics returned by Backlinks API. Here is what the related ones mean:

• Rank across endpoints: the same domain can show one value in Summary and a lower one in Referring Domains. Summary scores the site itself, while Referring Domains scores only the authority that site passes to your target, so both numbers are correct;
• Average backlink metrics: Labs API responses include an avg_backlinks_info object with the arithmetic means of rank, main_domain_rank, and link counts for the top-10 pages ranking for a keyword. You can use it to estimate how much link authority a keyword requires;
• Dofollow referring domains, backlinks, and anchors: dofollow links are links without the nofollow, UGC, or sponsored attribute. You can isolate them with filters or by subtracting the _nofollow totals from the overall counts;
• Referring pages vs backlinks: a referring page is a single URL linking to your target, while backlinks count every individual link. One page with three links to you adds 1 referring page and 3 backlinks;
• Spam Score: a 0–100 estimate of how likely a target or an individual backlink is to be spam. Here a higher value is worse, the opposite of rank;
• Broken backlinks and broken pages: broken backlinks point to pages of your target that return an error code such as 404. Broken pages are those URLs themselves, and authority sent to them can go unused until you fix or redirect them;
• Targets: whether you send a domain, subdomain, page, or path decides what rank and the other metrics describe. A domain target returns site-level values, while an absolute URL returns values for that single page.

 
In short, rank scores whatever an endpoint reports on, and domain_from_rank and page_from_rank score where a link comes from. If you run into a field question while moving from another provider, our support manager will do their best to help, so feel free to reach out. If you’re still choosing a provider, check our DataForSEO vs Ahrefs comparison that goes beyond rank and backlink fields.

Request parameters and response schemas for every endpoint in this article are in our Backlinks API documentation.