Google Ads Quality Score: What It Is and How to Improve It

Google Ads Quality Score is a 1 to 10 rating of how relevant your ad, keyword, and landing page are to a search query, reported at the keyword level inside the Google Ads UI. It runs on three components: Expected Click-Through Rate (Expected CTR), Ad Relevance, and Landing Page Experience. The visible 1 to 10 number is a lagging diagnostic, not the value Google uses in the auction. The auction uses a granular auction-time Quality Score recalculated on every search, which is why the visible number can look fine while CPCs (Cost Per Click) climb. Improving the visible score is useful, but the wins that hold come from fixing the upstream causes, account structure, query-to-ad match, and landing page speed.

This guide covers what Quality Score is, why it still matters in 2026, which component actually moves the number at scale, the diagnostic most advertisers skip, and when Quality Score is not the right fight in the first place.

Quality Score is Google’s 1 to 10 keyword-level diagnostic of how relevant your ad, keyword, and landing page are to the query a user typed. It sits in the keywords tab in Google Ads, updated on a rolling basis as keywords accumulate impressions. The number summarizes three component ratings (Expected CTR, Ad Relevance, Landing Page Experience), each rated Above Average, Average, or Below Average against other ads competing on the same keyword [1].

The number you see in the UI is not the number Google uses to set your CPC. Google calculates an auction-time Quality Score on every search, factoring in device, location, time of day, the surrounding query context, and live engagement signals. The keyword-level 1 to 10 is a lagging summary of past performance. At $500,000 a month and above in Google spend, that distinction is the difference between a clean diagnostic and a misleading one. A keyword can show a 9 in the UI while losing money on mobile in non-business hours, because the visible score averages over the auctions where it wins.

Quick takeaways:

• 1 to 10 scale, keyword level, visible in the Google Ads UI.
• Three components: Expected CTR, Ad Relevance, Landing Page Experience.
• The visible score is a diagnostic. The auction uses a separate, real-time score that is finer-grained.

For programs running paid acquisition at scale, Quality Score is one input into a larger account architecture question. See our paid media practice for how the diagnostic feeds account-level decisions.

Quality Score still matters because it is the most direct mechanism Google gives an advertiser to lower CPCs without raising bids, and the effect compounds across an account. Higher scores produce cheaper clicks, cheaper clicks free budget, freed budget pays for more impressions, and more impressions raise Click-Through Rate (CTR), which feeds Quality Score back upstream. The compounding goes the other way too. An account ignoring Quality Score pays a tax on every click, whether the operator sees it in the UI or not.

The portfolio floor for non-brand Google Return On Ad Spend (ROAS) is 1.5x across Opascope’s managed accounts. Accounts below that floor almost always have a Quality Score problem underneath, usually structural. The fix is rarely a bid change. The cleanest version of this came from a cloud platform we managed: rebuilding attribution and pulling creative into tighter alignment with landing pages produced a 93% drop in Cost Per Acquisition (CPA) and 660% signup growth over four years [2]. Quality Score moved as a byproduct, not as a target.

Quick takeaways:

• Quality Score directly affects Ad Rank and effective CPC. Higher scores can pay less per click than higher bidders with lower scores.
• Performance Max (PMax, Google’s automated multi-format campaign type) hides Quality Score from the UI but does not remove the underlying logic. Accounts that neglect landing page quality see PMax decay even when the algorithm appears to be doing fine.
• Non-brand Google ROAS below 1.5x is a Quality Score signal across our portfolio. The accounts at that level rarely have a bidding problem; they have a structure or relevance problem.

The full account-level chain is documented in 660% signup growth on a cloud platform, which traces the structure question back through attribution, creative, and landing page work.

Quality Score is calculated from Expected CTR, Ad Relevance, and Landing Page Experience, each rated Above Average, Average, or Below Average. Expected CTR carries the most weight in Google’s documentation. In practice, Landing Page Experience is the biggest lever because most advertisers refuse to invest in it. Ad Relevance is the fastest to fix.

The component logic, in plain language:

• Expected CTR is Google’s prediction of how often your ad will be clicked when eligible, normalized against other ads on the same keyword [1]. It is a prediction, not your historical CTR. Position and ad format are factored out, so the rating reflects relevance, not real estate.
• Ad Relevance measures how closely the ad copy matches the intent behind the query, not the literal keyword string [3]. A keyword can match ten different intents; relevance asks whether the ad addresses the intent the user actually expressed.
• Landing Page Experience is Google’s read on the page the click lands on. Speed, mobile rendering, content match between ad and page, and transparency drive the rating [1].

Each component is graded by comparison, not by absolute thresholds. “Above Average” means above the median for the keyword’s competitive set. That makes Quality Score relative; raising your score depends on relative gains against the auction, not on hitting a fixed number.

Quick takeaways:

• Expected CTR carries the documentation weight; Landing Page Experience carries the real-world impact.
• Ad Relevance is the fastest lever because copy and ad-group structure can change in a day. Landing pages take weeks.
• All three components are graded against competitors. Improving in absolute terms while the field improves faster moves the rating down.

Expected CTR is Google’s prediction that your ad will get clicked when eligible, normalized against other ads on the same keyword. Raising it is less about clever copy and more about tight query-to-ad match. The biggest lifts come from splitting broad-match themes into single-intent ad groups and rewriting Responsive Search Ads (RSAs) against the actual queries users typed, not the keyword strings the planner suggested.

Two structural moves consistently lift Expected CTR. First, audit the search terms report and identify queries that share an intent. Build an ad group around each intent rather than around a keyword theme. Second, write RSA headlines against the verbatim query language. Search Query Reports (SQRs) are the source of truth here; they show how the user actually phrased the question, which is rarely how the keyword planner phrased it.

RSA pinning is the second-order question. Google’s published guidance discourages heavy pinning in favor of letting the system test combinations. Tested in managed accounts, pinning still works in practice. Generative models now optimize headlines at scale, producing variants matched to specific intents, which the system then mixes inside the constraints pinning sets [4]. The default of “let Google figure it out” tends to under-perform structured pinning when the ad group is single-intent.

Quick takeaways:

• Expected CTR is normalized against the keyword’s own competitive set. Position and format are factored out.
• Ad-group structure beats clever copy. Single-intent ad groups outperform themed ad groups in nearly every account we have audited.
• Pinning works in practice across managed accounts even though Google’s documentation suggests letting the system test. Treat the documentation as a hint, not a constraint.

For the structural mistakes that drag Expected CTR down silently, see 10 ways to ruin a performance marketing program.

Ad Relevance measures how closely your ad copy matches the intent behind the query, not the keyword string, and most advertisers write to the keyword and ignore the query. The fix is structural: split intents into separate ad groups, then write RSAs that speak directly to each. Theme-based ad groups built around keyword variants tend to score Average at best, because a single ad has to address several intents at once.

Two patterns drag Ad Relevance down across portfolio audits. Broad match without aggressive negatives lets the keyword pull queries with a different intent, and the ad cannot serve all of them well. Dynamic Search Ads (DSAs) generate headlines from page content, which sometimes matches query intent and sometimes does not; the relevance rating averages those cases together. Both are silent killers because they show as Average rather than Below Average, which advertisers often read as fine.

The structural fix is repetitive but it works. Pull the search terms report. Cluster queries by intent. Build an ad group per cluster. Write RSAs against the cluster’s verbatim language. Add negatives that exclude the other clusters. Quality Score on the keyword usually moves within two weeks, sometimes sooner.

Quick takeaways:

• Keyword string is not the target. Query intent is.
• Broad match and DSAs degrade Ad Relevance silently because they spray across intents and average out.
• Intent-based ad groups beat keyword-based ad groups in every account we have audited at $500,000 a month and above.

Landing Page Experience is the highest-impact component because most competitors refuse to invest in it, and the dominant signals in practice are page speed and the match between the ad copy and the first screen the user sees. Speed wins on its own, before content quality enters the picture. On a direct-to-consumer brand spending over $1 million a month on ads, slow landing page load was killing roughly 10% of leads before they saw the page; rebuilding the page in a modern framework cut top-of-funnel costs in half [5].

Two technical moves tend to drive the largest gains: framework migration off slow page builders, and a hard cut to the JavaScript payload on the first screen. Lazy-loading anything below the fold, removing third-party tags that block render, and shrinking the main-thread work before First Contentful Paint do most of the speed work. Content-side, the rule is simple: the first screen has to mirror what the ad promised. If the ad sells a product and the page leads with a category page, the message-match signal Google reads goes flat.

Landing Page Experience is rated separately for mobile and desktop, and mobile usually lags. A page that scores Above Average on desktop while sitting at Average on mobile is paying a CPC premium on the half of the auction that costs the most. Mobile speed and mobile-first content match are not the same project as desktop. Treat them as separate work.

Quick takeaways:

• Page speed is the dominant signal. Ad-to-page message match is the second lever.
• Mobile and desktop are rated separately. Mobile usually lags, and the CPC tax compounds on the channel that already costs more.
• Framework migration, lazy-loading, and JavaScript payload reduction handle the technical side. Mirroring the ad promise on the first screen handles the content side.

The full diagnostic on landing page rebuild economics lives in why low-code landing pages hurt conversions. The downstream conversion-rate piece sits in why CRO isn’t impacting your bottom line.

The fastest way to find Quality Score problems in an account is to add the Quality Score history columns to the keywords tab and filter to keywords spending above a threshold with scores below 6. That filter surfaces the highest-cost problems first. The overall Quality Score column hides problems at the query level, where the money actually goes.

The full diagnostic takes ten minutes. In the keywords tab, add the columns: Quality Score, Expected CTR, Ad Relevance, Landing Page Experience, plus the historical versions of each. Filter by spend over a threshold the account considers material (often $500 or $1,000 over the trailing 30 days). Then sort by Quality Score ascending. The top of the list is the keywords burning the most money on the lowest scores. Each row tells you which component is rated Below Average, which routes the fix.

Two follow-on cuts catch what the keyword view misses. Segment by device; mobile usually lags desktop and eats more spend than the account owner realizes. Then check the search terms report. Quality Score is keyword-level, but the spend is at the query level. A keyword with a 7 can be wasting most of its budget on queries that should never have matched in the first place. We see 50%+ underreporting of conversions across accounts we have audited over the last 18 months, which means the keywords showing acceptable scores often hide far worse economics than the UI displays.

Quick takeaways:

• Add the four history columns. Filter to spend above threshold and Quality Score below 6.
• Segment by device. Mobile usually lags and carries the higher CPC.
• Check the search terms report, not just keywords. Spend lives at the query level.

The audit-led version of this diagnostic, applied at scale, is documented in one week of consulting cut $34M in wasted spend.

Quality Score is a symptom, not always the disease. Accounts with weak attribution or mispriced offers can show respectable scores while burning money. Accounts with great scores still fail when product-market fit is off or the offer does not pay the CPC math. The decision rule we use across managed accounts is straightforward: fix Quality Score when CPCs are high and Conversion Rates (CVRs) are reasonable. Fix the upstream problem when CVRs are low.

Three patterns send accounts chasing Quality Score when the real problem is upstream. First, attribution leaks. If conversions are getting under-counted by GA4 or by the platform’s own conversion tracking, the optimization signal feeding the auction is wrong, and Quality Score will reflect a half-blind algorithm. Second, offer-market fit. A landing page can hit Above Average on every signal Google rates and still convert poorly because the offer does not match the audience. Third, PMax campaigns. The visible Quality Score levers do not exist there; the same underlying signals still drive performance, but the work happens through asset groups and audience signals, not keyword-level diagnostics.

Quick takeaways:

• Decision rule: high CPC plus reasonable CVR equals a Quality Score fix. Low CVR equals an upstream fix.
• Attribution leaks pretend to be Quality Score problems. Audit the measurement layer first.
• PMax changes the surface, not the substrate. Landing Page Experience still drives outcomes; the keyword-level UI is just hidden.

The CRO side of this question is in why CRO isn’t impacting your bottom line.

What is a good Google Ads Quality Score? A Quality Score of 7 or higher is generally considered good. A score of 8 to 10 suggests the ad, keyword, and landing page are well aligned. A 6 or below indicates at least one of the three components is rated Below Average. The 1 to 10 number is a rolling summary, so a sudden drop usually reflects a structural change in the account or the SERP, not a daily fluctuation.

How does Quality Score affect cost per click? Quality Score directly affects Ad Rank, which determines the effective CPC. Google’s Ad Rank formula multiplies bid by Quality Score, so a keyword with a higher score can pay less per click than a higher bidder with a lower score. In practice, raising Quality Score from 5 to 8 can cut effective CPC by 30% to 50% on the same bid, based on observed behavior across our managed accounts.

What is the difference between visible Quality Score and auction-time Quality Score? The 1 to 10 Quality Score in the Google Ads UI is a lagging, keyword-level summary. Google does not use that number in the auction. Google calculates an auction-time Quality Score for every search, factoring in device, location, time of day, and the user’s exact query. The visible score is a useful diagnostic, but the auction score decides the CPC on any given click.

Which Quality Score component matters most? Expected CTR carries the most weight in Google’s public documentation, but Landing Page Experience is the highest-impact component in practice because most advertisers ignore it. Ad Relevance is the fastest to fix. If only one component gets investment, invest in landing pages. The benefit compounds across every campaign in the account.

How long does it take to see Quality Score improvements? Ad Relevance and Expected CTR updates typically show in 7 to 14 days after changes are live, once ads have accumulated enough impressions for Google to recalculate. Landing Page Experience can take 4 to 8 weeks because Google re-crawls and re-evaluates pages on its own schedule. Patience is part of the cost.

Does Quality Score still matter in Performance Max and Advantage+ campaigns? Performance Max and Advantage+ hide Quality Score from the UI, but the underlying signals (ad relevance, landing page experience, predicted engagement) still drive Google’s decisions about where and how often to show ads. Accounts that neglect landing page quality see Performance Max performance decay even when the algorithm appears to be doing fine.

Can improving landing page speed really raise Quality Score? Speed is one of the dominant signals inside Landing Page Experience, and the effect is measurable. On a direct-to-consumer brand spending over $1 million a month on ads, slow landing page load was killing about 10% of leads before they saw the page. Rebuilding the page in a modern framework cut top-of-funnel costs in half.

What is the fastest way to diagnose Quality Score problems in an account? Add the Quality Score history columns (Quality Score, Expected CTR, Ad Relevance, Landing Page Experience) to the Google Ads keywords tab. Filter to keywords spending above a meaningful threshold with Quality Scores below 6. That filter surfaces the highest-cost problems first. Check device breakouts too; mobile usually lags desktop and eats more spend than the account owner realizes.

Does Quality Score apply to Display and YouTube ads? The 1 to 10 keyword-level Quality Score is specific to Search campaigns. Display, Video, and Shopping campaigns use related ad-quality signals, but the reporting and mechanics differ. When someone says “Quality Score” without qualifying, they almost always mean the Search version.

Should I pause keywords with low Quality Scores? Pausing is rarely the right move. A low score on a high-intent commercial keyword often points to a structural fix (wrong ad group, wrong landing page) that unlocks more value than pausing ever could. Pause when the keyword is off-intent or the query behind it is misaligned with the business, not because the score is low.

Can bid strategy affect Quality Score? Indirectly. Automated bid strategies like Maximize Conversions or Target ROAS do not change Quality Score directly, but they can change which queries the ads show on, which in turn changes the Expected CTR and Ad Relevance ratings. Switching bid strategies without re-auditing the search terms report is a common reason Quality Scores drift.

Is Quality Score worth the effort in 2026? Quality Score still controls the CPC math that determines how far an ad budget goes. Google has layered more automation on top of the auction, but the mechanism that rewards relevance with cheaper clicks has not changed. Accounts that neglect Quality Score pay the tax on every click, whether they see it in the UI or not.

1. Google Ads Help, About Quality Score for Search campaigns. https://support.google.com/google-ads/answer/6167118
2. Opascope insight, How we increased a cloud computing company’s monthly paid signups by 660%. https://opascope.com/insights/how-opascope-increased-a-cloud-computing-cos-monthly-paid-signups-by-660/
3. Google Ads Help, About ad quality. https://support.google.com/google-ads/answer/156066
4. Google Ads Help, 5 ways to use Quality Score to improve your performance. https://support.google.com/google-ads/answer/6167130
5. Opascope insight, Why low-code landing pages hurt conversions. https://opascope.com/insights/why-low-code-landing-pages-hurt-conversions/