Vincent JOSSE
Vincent is an SEO Expert who graduated from Polytechnique where he studied graph theory and machine learning applied to search engines.
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TL;DR
Keyword difficulty scores disagree because SEO tools use different formulas, backlink databases, search-result snapshots and definitions of competition. A score of 25 in one platform is not necessarily equivalent to 25 in another. Neither number tells you, by itself, whether your website can rank.
Key takeaway: Use difficulty scores to shortlist keywords within one tool, then inspect the current search results and your website’s ability to satisfy the query. Do not average conflicting scores or treat them as ranking probabilities.
What a keyword difficulty score actually measures
Keyword difficulty is a tool-generated estimate of how competitive an organic search query is. It is not a metric supplied by Google, and there is no industry-wide formula behind it.
Most tools display a score between 0 and 100. Depending on the provider, that number may reflect the backlink strength of ranking pages, the authority of competing websites, characteristics of the search results or some combination of those inputs.
A score of 60 does not mean you have a 40% chance of ranking. Unless a provider explicitly defines and validates its score as a probability, it should be treated as a relative indicator of competition.
Difficulty also answers a different question from search volume or business value:
Search volume: How much estimated demand exists for this query?
Keyword difficulty: How competitive does the tool estimate the organic results to be?
Business value: Would reaching this audience support your goals?
Ranking feasibility: Can your particular website produce a suitable page and compete?
A low-difficulty keyword can have little commercial value. A high-difficulty keyword can still deserve investment when it closely matches your product and you have relevant expertise.
Why keyword difficulty scores disagree
Tools measure different kinds of competition
The most important difference is methodological. Two tools can analyze the same search results and produce different scores because they are measuring different things.
For example, Ahrefs explains its keyword difficulty methodology primarily in terms of the referring domains linking to pages in the top 10 results. Its standard KD metric does not directly evaluate on-page content quality.
Semrush describes a broader keyword difficulty calculation that considers backlink-related signals, authority metrics and other keyword or search-result characteristics.
These are summaries, not complete formulas. Providers can change their models, so consult their current documentation before building a workflow around a particular score.
The disagreement is not necessarily an error. A backlink-focused model and a broader competition model may simply be answering slightly different questions.
Backlink databases contain different evidence
Even tools using similar formulas may start with different backlink data.
Each provider maintains its own crawl infrastructure and link index. Coverage, crawl frequency and decisions about which links to retain or filter affect the picture of a ranking page’s backlink profile.
One index might have discovered links that another has not. A tool may also count fewer referring domains because it filters certain sources or has not refreshed a page recently.
This matters when difficulty relies heavily on links. Different input data can produce different scores without either tool making a calculation mistake.
Treat the backlink database as a sample of the web, not a complete inventory. When links are central to a decision, inspect the strongest relevant referring domains rather than comparing totals alone.
The tools may be analyzing different search results
Difficulty calculations depend on which pages the tool considers competitors. Those pages can change with the country, language, location and collection date.
A query searched in the United States may produce a different competitive set from the same query searched in the United Kingdom. Local intent can create even larger differences.
Refresh timing matters too. One provider may have recalculated difficulty after a search-results change while another still uses an older snapshot. Do not assume the displayed search volume, ranking results and difficulty score were all refreshed together.
Before comparing estimates, check the selected database and inspect the ranking URLs behind each score. Our guide to why ranking-checking tools return different results explains the location and measurement issues that can also affect these comparisons.
Shared scales do not create shared meanings
A 0-to-100 scale looks standardized, but it is only a display convention.
Providers use different transformations and thresholds to convert their inputs into a number. Labels such as “easy,” “possible” or “hard” belong to each provider’s model, not to a universal SEO standard.
Consequently, a score of 30 in Tool A might represent a different level of competition from 30 in Tool B. There is also no reason to assume that moving from 20 to 40 means the required effort doubles.
Compare keywords within the same tool before comparing scores across tools. Internal consistency is more useful for prioritization than numerical agreement between platforms.
Generic difficulty is not difficulty for your website
A general difficulty score usually describes the competitive landscape without fully accounting for your starting position.
Your website might already cover the topic extensively, have relevant backlinks and rank for closely related queries. Another website targeting the same keyword might lack all three advantages.
Some platforms offer domain-specific estimates. Semrush, for example, distinguishes standard keyword difficulty from Personal Keyword Difficulty. A personalized estimate and a generic score should not be treated as interchangeable measurements.
Your intended page type matters as well. A strong educational article may still struggle when the results overwhelmingly favor product pages, category pages or interactive tools.
This creates a useful distinction: market competition is not the same as your ability to compete. A generic score helps describe the former. Your own site evidence helps assess the latter.
What difficulty scores leave out
Even a sophisticated model compresses a complicated search landscape into one number. That compression loses information.
Search intent is a major example. A query can have modest backlink competition but still demand something your planned article cannot provide, such as a calculator, a local service or an official support answer.
Content defensibility is another. A page supported by original testing, proprietary data or direct product experience may be hard to outperform even with relatively few links. A difficulty score cannot reliably tell you whether you can produce a genuinely better answer.
Search-result layout also affects the opportunity. Ads, featured answers, AI Overviews and other features can influence how users interact with results. A tool may account for some features in its model, but you should still assess traffic potential separately from ranking competition.
Finally, Google Ads “Competition” is a different metric. It concerns advertiser competition, not the difficulty of earning organic rankings. Check the column definition before interpreting a low value as an SEO opportunity.
A worked example: interpreting a large disagreement
Consider this hypothetical situation: you want to target “invoice automation software.” Tool A reports difficulty of 24, while Tool B reports 58. These numbers are illustrative, not actual measurements.
Averaging them to 41 would hide the information you need. Instead, inspect what each tool is analyzing.
Suppose the ranking URLs are similar, but many pages have relatively modest referring-domain counts while belonging to established software websites. A backlink-focused model could rate the query lower than a model that also emphasizes broader authority signals. That is a plausible explanation, not a conclusion you can draw from the numbers alone.
Next, inspect intent. If the results are dominated by software landing pages and comparison directories, publishing a general article about invoice processing may be the wrong approach regardless of difficulty.
The useful decision is conditional:
If you offer relevant software and have a strong product page, the query may warrant deeper competitive analysis.
If you only plan an educational article, a narrower informational query may fit better.
If the tools use different countries or ranking snapshots, align those settings before interpreting the gap.
The scores have done their job by highlighting uncertainty. The search results tell you what to investigate.
How to resolve conflicting scores without averaging them
Align the measurement conditions
Start by checking that both tools are evaluating the same query and market. Confirm country, language, device where configurable and any location settings relevant to local searches.
Then compare the ranking URLs and available refresh dates. If the competing pages differ substantially, you are not comparing the same competitive landscape.
Refresh the data if the provider supports it. Otherwise, note the mismatch and avoid treating the difference as purely methodological.
Inspect the pages you would need to compete with
Review several leading organic results and identify the dominant page type. Look for product pages, guides, directories, forums or tools.
Evaluate whether those pages solve the query well. Consider specificity, firsthand evidence, completeness and freshness where the topic requires it.
Backlinks still matter, but look beyond totals. Relevant editorial links may be more informative than a large collection of unrelated sources.
Your objective is not to prove that every competitor is weak. It is to identify a credible route into the results with the page you can actually create.
Assess your website’s starting position
Use your existing performance as evidence. Have you earned impressions or rankings for related queries? Do you already have a suitable page that needs improvement rather than a new article?
Check whether your website has relevant supporting content and sensible internal links. Those resources can help readers navigate the topic, but they do not guarantee rankings.
Also consider production requirements. A query that needs original testing or specialist review may be unsuitable for a low-effort publishing workflow, even when the displayed difficulty is low.
If you need alternative targets, our workflow for finding low-competition keywords with AI explains how to generate candidates and validate them against the search results.
Make a decision with explicit reasons
Assign the keyword an action such as “target now,” “improve an existing page,” “investigate further” or “defer.” Record the reason alongside the score.
A useful note might be: “Target after updating our comparison page because the results match our offer and we already rank for related searches.” Another might be: “Defer because the query requires an interactive tool we do not provide.”
This is more actionable than “difficulty: 38.” It also makes the decision easier to revisit when the results or your website change.
Build your own difficulty calibration
Choose one primary tool for routine shortlisting. Keep its scores consistent across your workflow and use a second provider when a consequential decision needs another perspective.
For each targeted keyword, record the original difficulty estimate, page type, publication or update date and your starting visibility. Later, compare those records with impressions, clicks and rankings in Google Search Console.
You can then develop a site-specific interpretation. Your website might perform well on certain moderately difficult topics while struggling with supposedly easy keywords whose intent does not fit your content.
Do not turn a few successes into a universal cutoff. Results also depend on execution quality, time, competition and changes to your website. Group observations by topic and page type so your comparisons remain meaningful.
The best calibration question is not “Which tool is always right?” It is “Which signals help us make better decisions for this website?”
Frequently asked questions
Which keyword difficulty score should I trust? Use a tool whose methodology you understand as your consistent baseline. Validate important targets through current search results and your own website’s performance. No generic score can reliably determine ranking feasibility on its own.
Should I average scores from multiple SEO tools? No. Different formulas and scales make the average difficult to interpret. Investigate why the scores differ instead, especially differences in ranking pages, backlink data and metric definitions.
Can a new website rank for a high-difficulty keyword? It is possible, but the score does not establish how likely it is. Search intent, page quality, relevant links and the website’s existing strengths all affect the opportunity. Prioritize targets you can serve convincingly.
Does low keyword difficulty guarantee traffic? No. A keyword may have little demand, limited click opportunity or the wrong audience for your business. Difficulty, traffic potential and business relevance need separate evaluation.
Final verdict
Keyword difficulty scores are screening tools, not final decisions. Disagreement is a reason to examine methodology and evidence, not to hunt for the most reassuring number.
Use one consistent baseline, inspect the current results and document why a keyword is worth pursuing. That approach remains useful even when providers change their formulas.
Turn keyword research into a publishing workflow
Once you have validated your targets, BlogSEO can support keyword research, AI-powered article generation, internal linking automation and scheduled publishing. Keep the targeting decision grounded in evidence, then use automation to reduce the manual work of producing and publishing your SEO content.
