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What Is Keyword Difficulty? How to Read and Use the Score
Keyword difficulty is a score, usually on a 0 to 100 scale, that estimates how hard it would be for a new page to rank on the first page of...
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Keyword difficulty is a score, usually on a 0 to 100 scale, that estimates how hard it would be for a new page to rank on the first page of Google for a given search term. It’s a useful prioritization tool, but it’s important to understand from the outset that it isn’t a Google metric at all. Google does not publish a keyword difficulty score, and there’s no single official formula. Every keyword difficulty number a marketer sees comes from a third-party SEO platform’s proprietary model, most commonly Ahrefs, Semrush, or Moz, and each tool calculates it somewhat differently.
What the Score Is Actually Measuring
Despite differences in exact methodology, most keyword difficulty scores are built around a similar core idea: look at the pages currently ranking on page one for a keyword, and estimate how much backlink authority a new page would need to compete with them.
Ahrefs’ own documentation describes its Keyword Difficulty (KD) metric this way: it’s based on “the number of referring domains the Top 10 ranking pages… have,” plotted on a scale from 0 to 100, and explicitly does not factor in on-page SEO quality (Ahrefs Help Center: What does KD stand for in Keywords Explorer?).
Semrush’s Keyword Difficulty percentage works on similar raw material but with a broader input set. According to Semrush’s own knowledge base, the calculation considers the median number of referring domains pointing to ranking URLs, the ratio of dofollow to nofollow links among those, the median authority score of the ranking domains, and SERP-related characteristics of the keyword itself, such as whether it triggers featured snippets or other SERP features (Semrush Knowledge Base: Keyword Difficulty score).
Moz’s Keyword Difficulty score works on a comparable principle, evaluating the Page Authority and Domain Authority of the pages currently ranking for a term, though Moz’s specific weighting and exact methodology aren’t fully documented in public form the way Ahrefs’ and Semrush’s are.
Why the Same Keyword Gets Different Scores in Different Tools
This is one of the most common points of confusion for anyone who checks the same keyword in two different platforms and gets two different numbers. It happens because:
| Factor | Why it causes divergence |
|---|---|
| Different backlink indexes | Each tool crawls and maintains its own link database, which doesn't perfectly overlap with any other tool's database, so referring-domain counts for the same URL can differ between platforms |
| Different scoring formulas | Even with identical input data, each tool weights referring domains, domain-level authority, content signals, and SERP features differently |
| Different proprietary authority metrics | Ahrefs uses Domain Rating, Moz uses Domain Authority, Semrush uses Authority Score; none of these are the same scale or calculated the same way, so feeding them into a difficulty formula produces different outputs |
| Update frequency | Some tools refresh difficulty data for high-volume keywords more often (in some cases close to daily) than for low-volume keywords (sometimes closer to monthly), so two tools checked on different days may reflect different snapshots of the same SERP |
None of this means one tool is “wrong” and another is “right.” They’re different proprietary estimates of the same underlying competitive landscape, built from different data and different assumptions.
Worked Example (Hypothetical)
To illustrate how difficulty tends to shift with specificity, imagine three increasingly specific versions of the same search topic. These numbers are illustrative only, not pulled from any live tool or real measured ranking data:
- A broad head term like “project management software” might hypothetically score around 80-85, reflecting an assumption that established, high-authority software review sites and major brands dominate that result page.
- A narrower variant like “project management software for architecture firms” might hypothetically score in the 30s, since fewer established pages are likely to be precisely targeting that niche phrase.
- A long-tail variant like “best free project management software for small creative agencies” might hypothetically score around 20, under the general assumption that long-tail, highly specific phrases tend to face less concentrated competition than broad head terms.
The general direction in that example, that more specific phrases tend to carry lower difficulty than broad head terms, is a widely observed pattern in keyword research, but the specific numbers above are made up for illustration and shouldn’t be read as a claim about how any particular tool would actually score those exact phrases.
What Keyword Difficulty Scores Don’t Capture
A difficulty score is built almost entirely from backlink-related signals and some SERP characteristics. That means it systematically misses several things that affect whether a page actually ranks:
- Content quality and depth. A keyword difficulty score doesn’t evaluate whether a piece of content thoroughly answers the query better than what’s currently ranking.
- Your own site’s existing authority. A difficulty score describes the competitive landscape in the abstract; it says nothing about whether your specific site, with its specific backlink profile and topical history, is positioned to compete for it.
- Search intent alignment. A numerically “easy” keyword is still effectively unwinnable if the content format doesn’t match what’s actually ranking, for example targeting a product page when Google’s results are dominated by long-form how-to guides.
- On-page and technical factors. Page experience, internal linking, and technical health aren’t part of most difficulty calculations, even though they affect real-world ranking outcomes.
- SERP volatility. A snapshot score doesn’t indicate whether the current top 10 has been stable for years or is actively being contested and reshuffled.
- AI-driven SERP features. As Google increasingly surfaces AI Overviews and other generative result formats for some queries, a traditional backlink-based difficulty score doesn’t account for how visible a normal organic result will even be on that results page, since these features can push organic results further down regardless of how “easy” the keyword scored. Ahrefs’ own December 2025 analysis of roughly 300,000 keywords found that the presence of an AI Overview now correlates with about a 58% lower average click-through rate for the page ranking in position one, compared to similar keywords without an AI Overview (Ahrefs: AI Overviews Reduce Clicks, Update). A keyword can carry a low difficulty score and still deliver far less traffic than the score implies, simply because an AI Overview is absorbing most of the clicks before anyone scrolls to the organic results.
How to Use Difficulty Scores in Practice
A practical approach treats difficulty as one input into a prioritization decision, not the decision itself:
- Pull difficulty alongside search volume and business value. A low-difficulty keyword with near-zero search volume, or volume but no real connection to what you sell, usually isn’t worth prioritizing over a moderately harder keyword that converts.
- Read the actual SERP before trusting the number. Manually check who’s ranking, what content format dominates (listicle, product page, long-form guide, video), and whether your site has any realistic basis to compete with those specific pages.
- Weigh the score against your own site’s authority level. General industry practice suggests newer or lower-authority sites get more realistic traction targeting lower-difficulty terms first, while established, high-authority sites can reasonably pursue much higher-difficulty terms. There’s no fixed, universally-agreed threshold for what counts as “low” or “high” for a given site, since that depends heavily on the specific niche and competitive set.
- Check intent match, not just the number. A keyword scored as moderately difficult but with a SERP format your content can genuinely match is usually a better target than a lower-scored keyword where the dominant format doesn’t fit what you’re able to publish.
- Treat small differences as noise. A difference of a few points on a 100-point scale is rarely a meaningful signal given how much estimation and approximation goes into the underlying formula; it’s more useful to compare keywords in broad bands than to over-index on small numeric gaps.
Frequently Asked Questions
Is keyword difficulty a Google ranking factor?
No. It’s a metric created and maintained independently by SEO software companies. Google does not publish or endorse any keyword difficulty score, and the underlying inputs (mainly backlink data) come from each tool’s own independently crawled index, not from Google directly.
Which tool’s keyword difficulty score is most accurate?
There’s no single correct answer, since each tool is measuring against its own backlink index and its own definition of difficulty. The more useful practice is picking one tool and using its scores consistently and comparatively, rather than treating any one number as an absolute truth.
Should I avoid all high-difficulty keywords?
Not necessarily. A high score reflects backlink-heavy competition, not an impossibility. Sites with strong existing authority, or topics where a genuinely better piece of content has a real shot at outranking thin or outdated competitors, can still be worth pursuing even at higher difficulty levels.
Does keyword difficulty account for AI Overviews and other generative search features?
Traditional difficulty scores are built on backlink data tied to classic organic rankings, so they don’t directly measure how visible a result will be alongside AI-generated answers or other newer SERP features. That’s a separate consideration worth checking manually on the live results page.
How often should I re-check difficulty scores for a keyword?
There’s no fixed schedule that applies universally. Tools generally refresh difficulty data more frequently for higher-volume keywords and less frequently for lower-volume ones, so it’s reasonable to recheck higher-priority targets periodically rather than treating a single score as permanent.