Spam Score
A metric indicating the likelihood that a website exhibits characteristics associated with penalized or spammy sites.
💡 Think of it like this: Every link to your site is like a vote in an election. Spam Score determines how much weight each vote carries — a vote from a senator counts more than one from a stranger.
How Spam Score Works
Spam Score is a metric developed by Moz that estimates the likelihood of a domain being penalized or flagged as spammy by search engines. It is expressed as a percentage (0–100%) and is calculated based on the presence of 27 spam signals identified by Moz through analysis of thousands of penalized and banned websites. A high Spam Score does not automatically mean a site is bad — it means it shares characteristics commonly found on spammy sites.
Why Spam Score Matters for SEO
The 27 spam signals include factors such as thin content, excessive exact-match anchor text, very low domain authority combined with many external links, site-wide footer links, large numbers of low-quality referring domains, and patterns of link manipulation. Moz uses machine learning to weight these signals and produce a composite spam probability score. A score of 1–30% is considered low risk, 31–60% medium risk, and 61–100% high risk. If you’re unsure how Spam Score is impacting your site, working with an experienced SEO consultant can help you identify the problem and fix it efficiently.
Common Spam Score Mistakes
Spam Score is primarily useful during backlink audits. When reviewing a site’s link profile, a high Spam Score on a referring domain warrants further investigation before deciding whether to disavow the link. It is also used when prospecting for link building partners — avoiding high Spam Score sites prevents acquiring low-quality links that could dilute a backlink profile. Spam Score should always be considered alongside other metrics like Domain Authority, traffic, and content quality.
Do’s and Don’ts: Spam Score
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TL;DR: A metric indicating the likelihood that a website exhibits characteristics associated with penalized or spammy…
If you remember one thing — focus on how Spam Score affects your users first, then optimise for search engines second.