Link Graph Encyclopedia

Domain metrics

Auditing vendor metrics

Checking Semrush and Majestic numbers from one day of GoDaddy's auction inventory against Common Crawl's open graph. A referring-domain floor made of the same few domains, a Majestic feed that is mostly empty, and a nearly constant Authority Score.

Link metrics are only useful if they vary with the thing they claim to measure. This entry tests the third-party metrics in GoDaddy’s public auction inventory against an independent reference, Common Crawl’s 2026 domain graph. The results are specific to one day and one population, auction listings, and to the vendor values as delivered in GoDaddy’s feed, but the method applies to any metric and any list of domains.

Data and method

Common Crawl is not ground truth: it is one crawl, it counts more link types than most vendors, and it ignores nofollow. It is, however, independent, open and the same for every domain, which is what a reference needs.

Finding 1: a Semrush referring-domain floor

Semrush reports referring domains for nearly every listing, including domains that no page in Common Crawl’s crawl links to:

Common Crawl in-degree Listed domains Semrush referring domains: 25th / 50th / 75th percentile
not in the graph 948,788 64 / 96 / 148
0 (in the graph via out-links only) 24,943 136 / 163 / 188
1 55,813 113 / 158 / 189
2–5 28,652 155 / 179 / 205
6–20 6,842 179 / 228 / 301
21–100 2,527 249 / 342 / 525
over 100 676 483 / 775 / 1,328

Domains with no observed links carry a hundred-odd referring domains, and the first four rows barely differ. The feed’s top-three lists show where those links come from. bye.fyi is among the top three referrers of 79.6% of all listings, southfwb.com of 48.0%, metamagic.top of 36.9% and shortenurls.eu of 34.7%. Among domains absent from Common Crawl’s graph the shares are higher still: 82%, 50%, 38% and 36%. Only from about six Common Crawl referring domains up do recognisable sites such as wikipedia.org, medium.com and google.com replace them at the top of the lists.

A small set of domains that link to, or list, nearly every expiring domain adds the same hundred or so referring domains to almost every row. That floor tells you nothing about any particular domain.

Finding 2: signal above the floor

Above the floor, Semrush’s counts do track Common Crawl:

Population Spearman ρ, Semrush referring domains vs Common Crawl in-degree
all 119,453 listed domains in the graph 0.27
Common Crawl in-degree at least 1 (94,510) 0.35
at least 2 (38,697) 0.38
at least 6 (10,045) 0.45

Ranking all listings by Semrush referring domains puts a random in-graph domain above a random absent one 76% of the time. The count is informative; the floor blunts it for the weakly linked majority.

Finding 3: a mostly empty Majestic feed

Population Majestic referring domains = 0 Trust Flow = 0
all listings 82.7% 98.6%
over 100 Common Crawl referring domains (676) 54.6% 66.9%
1,000 or more Common Crawl referring domains (17) 88.2% 94.1%

More than half of the best-linked listings show no Majestic data. Where values exist, they correlate with Common Crawl in-degree about as well as Semrush’s do above the floor (ρ = 0.41 for Trust Flow, 0.35 for Citation Flow, over 31,472 in-graph domains with nonzero Citation Flow), but referring domains rank in-graph above absent domains only 57% of the time, barely above chance, because of the zeros. The pattern points to coverage of the feed rather than of Majestic’s own index (see Trust Flow). Either way, a zero in this column means “unknown”.

Finding 4: a nearly constant Authority Score

87.7% of listings have Semrush Authority Score 2 and 9.3% have 0. The median is 2 in every group of the table above, and the Spearman correlation with Common Crawl in-degree is 0.16. For ranking auction listings the column carries almost no information (see Authority Score).

Finding 5: a duplicated column

The feed’s Semrush “Indexed Pages” value lies within 2% of its Semrush backlink count on 94.0% of rows, and equals it exactly on 42.9%, with a Spearman correlation of 0.999. Despite its name, the column repeats the backlink count.

Caveats

How to apply this

Before trusting any metric on a list of domains, check how it varies with an independent reference, what share of values are zero or at a common floor, and which linking domains appear on most rows. The reading domain metrics entry turns these findings into a buyer’s checklist, and spam mass gives the theory behind subtracting links that come from outside the web you trust.

References

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