How to Read This Data
Click-through rate (CTR) measures the percentage of searchers who click on a given result after seeing it on a search engine results page (SERP). A position 1 CTR of 39.8% means that roughly 40 out of every 100 people who see that result in the top spot will click on it.
The data on this page is drawn from five major studies, each using a different methodology:
- First Page Sage (2026) — Aggregated client data across multiple verticals. Reports the highest position 1 CTR (39.8%), likely because their methodology filters for cleaner organic SERPs.
- Backlinko (4 million keywords) — Analysis of clickstream data across 4 million Google search results. One of the most widely cited CTR studies in the SEO industry.
- SISTRIX (80 million keywords) — Largest keyword sample in this dataset. Based on tracking 80 million keywords in Google search results over time.
- GrowthSRC (200,000 keywords, 2025) — Focused on year-over-year CTR changes using Google Search Console data. Covers positions 1-2 in depth.
- seoClarity (750 billion impressions) — The largest impression-based dataset. Reports lower CTR figures because it includes all SERP types, including those with AI Overviews, featured snippets, and ads.
There is no single "correct" CTR for any position. The number depends on the SERP layout, search intent, device type, industry, and whether SERP features (ads, featured snippets, AI Overviews) appear. A clean organic SERP yields position 1 CTRs near 40%. A SERP with an AI Overview may push position 1 below 15%. The composite table below presents all five studies side-by-side so that readers can choose the benchmark most relevant to their context.
For context on why this data matters for rankings specifically, see Does CTR Affect Rankings? and What is NavBoost?
Positions 1–10: Page 1 CTR Benchmarks
The following table presents organic CTR data for Google page 1 results (positions 1 through 10) from all five studies. Numbers prefixed with "~" are approximations derived from graphical data in the original studies.
| Position | First Page Sage 2026 | Backlinko (4M kw) | SISTRIX (80M kw) | GrowthSRC 2025 (200K) | seoClarity (750B imp.) |
|---|---|---|---|---|---|
| 1 | 39.8% | 27.6% | 28.5% | 19.0% | 8.17% (desktop) |
| 2 | 18.7% | 15.7% | 15.7% | 12.6% | — |
| 3 | 10.2% | 11.0% | 11.0% | — | — |
| 4 | ~7.2% | 8.98% | ~8.0% | — | — |
| 5 | ~5.1% | 9.21% | ~6.5% | — | — |
| 6 | ~4.1% | 6.73% | ~5.0% | — | — |
| 7 | ~3.2% | 7.61% | ~4.0% | — | — |
| 8 | ~2.8% | 6.92% | ~3.5% | — | 1.32% |
| 9 | ~2.4% | 5.52% | ~3.0% | — | 1.10% |
| 10 | ~2.1% | 7.95% | 2.5% | — | 0.98% |
Sources: First Page Sage (2026), Backlinko/Brian Dean, SISTRIX, GrowthSRC (2025 Google Search Console study), seoClarity (2024, desktop). Click column headers to sort.
Analysis: What the Page 1 Data Shows
Several patterns emerge from the composite data:
Position 1 dominates, but the magnitude varies dramatically. First Page Sage reports 39.8%, while seoClarity reports just 8.17%. The difference is not a contradiction — it reflects different SERP compositions in each dataset. First Page Sage's data skews toward cleaner organic SERPs, while seoClarity's 750 billion impressions include every SERP type, including those crowded with ads, AI Overviews, and knowledge panels.
The drop from position 1 to position 2 is the steepest in all datasets. Across all five studies, position 2 captures between 40% and 66% fewer clicks than position 1. This is not a gradual decline — it is a cliff. The implication for NavBoost is clear: the feedback loop between ranking and clicks is most powerful at the very top of the SERP.
Backlinko's position 5 anomaly (9.21%) and position 10 anomaly (7.95%) are worth noting. In Backlinko's data, position 5 outperforms position 4, and position 10 outperforms positions 6 through 9. This has been attributed to SERP layout effects — position 5 often appears just below a visual break, and position 10 sits at the very bottom of page 1, where it can capture "last visible result" attention before a searcher decides whether to scroll further or refine their query.
The bottom of page 1 still matters. Even position 10 receives somewhere between 0.98% (seoClarity) and 7.95% (Backlinko) of clicks. As the data for page 2 shows, there is a massive cliff between position 10 and position 11.
Why CTR Numbers Vary So Much
One of the most common questions about CTR data is why different studies report such different numbers for the same positions. The answer is SERP features. Modern Google search results are not a simple list of ten blue links — they include ads, featured snippets, knowledge panels, video carousels, AI Overviews, shopping results, People Also Ask boxes, and more. Each of these features reshapes how clicks are distributed.
SISTRIX's data on CTR variation by SERP type provides the clearest evidence of this effect:
| SERP Layout | Position 1 CTR | Typical Trigger |
|---|---|---|
| Sitelinks (navigational) | 46.9% | Brand-name searches (facebook login, amazon) |
| Pure organic (no features) | 34.2% | Informational queries with no dominant intent |
| Featured Snippet present | 23.3% | Question-based queries (how to..., what is...) |
| Google Ads present | 18.8% | Commercial queries with active advertisers |
| Knowledge Panel present | 16.7% | Entity queries (Eiffel Tower, Barack Obama) |
| Google Shopping present | 13.7% | Product searches with price comparison intent |
Source: SISTRIX (80 million keywords). Figures represent position 1 organic CTR within each SERP type.
The range is stark: from 46.9% for navigational queries with sitelinks down to 13.7% when Google Shopping results appear. This 33-percentage-point gap means that the "average" position 1 CTR is largely meaningless without knowing the SERP context.
The AI Overview Factor
AI Overviews (formerly Search Generative Experience) represent the newest and most disruptive SERP feature. When an AI Overview appears, it pushes organic results below the fold and provides a synthesized answer that may satisfy the query without a click. Early research suggests position 1 CTR drops to roughly 11–15% when an AI Overview is present — a reduction of 50–70% compared to a clean organic SERP.
This is not captured in the composite table above because most of the underlying studies predate widespread AI Overview rollout or do not segment by this feature. For a deeper analysis, see AI Overviews & CTR Impact.
As AI Overviews expand, total organic click volume decreases. But NavBoost still operates on the clicks that do happen. Fewer total clicks means each individual click carries more relative weight in the click signal. The NavBoost system does not need high absolute click volumes — it needs a statistically meaningful ratio between expected and observed clicks for a given position.
Positions 11–20: The Page 2 Anomaly
The data for page 2 results tells a story that surprises many SEO practitioners. While the overall click rate for page 2 is extremely low — only 0.63% of searchers click on any page 2 result, according to seoClarity — the distribution within page 2 is not what most people expect.
| Position | Estimated CTR | Notes |
|---|---|---|
| 11 | 1.0% | Top of page 2 — highest initial visibility |
| 12 | 0.8% | |
| 13 | 0.7% | |
| 14 | 0.6% | |
| 15 | 0.4% | Lowest CTR zone on page 2 |
| 16 | 0.3–0.4% | Lowest CTR zone on page 2 |
| 17 | 0.5–0.7% | CTR begins increasing |
| 18 | 0.6–0.8% | Approaching bottom-of-page effect |
| 19 | 1.36% | Higher than positions 12–16 |
| 20 | 1.47% | Highest page 2 CTR (bottom-of-page effect) |
Source: seoClarity (750 billion impressions). Ranges reflect variance across query types. Positions 17–20 highlighted in green to indicate the anomalous CTR increase.
The Bottom-of-Page-2 Effect
Positions 17–20 receive higher CTR than positions 11–16. This is one of the most counterintuitive findings in CTR research. The conventional assumption is that CTR decreases monotonically with position — each position lower should receive fewer clicks than the one above it. On page 2, that assumption breaks down.
Position 20, at the very bottom of page 2, receives an estimated 1.47% CTR — higher than position 11 at the top of page 2 (1.0%). Position 19 receives 1.36%, also exceeding positions 11 through 16.
The most likely explanation is behavioral. Users who scroll to page 2 and continue scrolling past position 15 or 16 are highly committed searchers. They have already rejected page 1 and the top of page 2. By the time they reach positions 17–20, they are more willing to click because they are nearing the end of their scrolling tolerance and feel urgency to find a satisfactory result. This is the same "last visible result" effect observed with position 10 on page 1.
The page 2 anomaly matters for NavBoost because the system uses expected CTR as a baseline. If Google's model expects position 16 to receive fewer clicks than position 20, then a page in position 16 that receives unexpectedly high CTR sends a stronger positive signal than the same CTR at position 20, where it is expected. The squashing function normalizes these signals relative to positional expectations.
Positions 21–100: Pages 3 Through 10
Data for positions beyond page 2 is sparse. Most CTR studies focus on pages 1 and 2 because the vast majority of clicks occur there. However, the available evidence allows reasonable estimation of CTR ranges for deeper positions.
The overriding finding: 75% of searchers never scroll past page 1. Of the remaining 25%, most stop at page 2. The total organic click share for pages 3 through 10 is negligible in aggregate.
| Page | Positions | Estimated CTR Range (per result) | Aggregate Page Click Share |
|---|---|---|---|
| 3 | 21–30 | 0.1–0.5% | <1.0% |
| 4 | 31–40 | 0.05–0.3% | <0.5% |
| 5 | 41–50 | 0.01–0.15% | <0.3% |
| 6–10 | 51–100 | <0.05% | Negligible |
Estimates based on extrapolation from seoClarity page 2 data and Backlinko's long-tail analysis. These figures should be treated as rough approximations, not precise benchmarks.
These positions are functionally invisible to most searchers. However, they are not irrelevant for NavBoost. Pages that rank on page 3 or beyond still accumulate impression data, and a sudden spike in CTR at position 25 (perhaps driven by a viral social media link or brand recognition) sends a powerful signal precisely because the expected CTR at that position is so low.
For strategic guidance on moving from deep positions to page 1, see How to Improve Organic CTR.
CTR by Search Intent
Not all searches are alike. The intent behind a query is one of the strongest predictors of how clicks are distributed across the SERP. SISTRIX's dataset of 80 million keywords provides the most granular public data on how different SERP types — which serve as a proxy for search intent — affect organic CTR.
| SERP Type / Intent Signal | Position 1 CTR | What It Tells Us |
|---|---|---|
| Sitelinks (navigational) | 46.9% | Searcher already knows what they want. Clicking position 1 is almost automatic. |
| Pure organic (no features) | 34.2% | Classic "ten blue links" SERP. Position 1 captures roughly a third of all clicks. |
| Featured Snippet present | 23.3% | Featured snippet absorbs some clicks and also satisfies queries without a click. |
| Google Ads present | 18.8% | Ads push organic results below the fold, reducing visibility and CTR. |
| Knowledge Panel present | 16.7% | Entity-based queries often answered directly by the panel, suppressing organic clicks. |
| Google Shopping present | 13.7% | Product queries split attention between shopping results and organic listings. |
| AI Overview present | ~11–15% | Synthesized answer reduces need to click. Largest CTR suppression effect observed. |
Source: SISTRIX (80 million keywords) for positions 1–6. AI Overview estimate from early 2025 research; see AI Overviews & CTR Impact for details.
What Intent Data Means in Practice
Navigational queries are winner-take-all. When a searcher types a brand name, position 1 captures nearly half of all clicks. The sitelinks SERP layout — where position 1 expands to show sub-page links — further concentrates clicks. For NavBoost, this means that navigational queries produce overwhelming click signals for the dominant brand, making it extremely difficult for competitors to gain traction through click behavior alone.
Informational queries distribute clicks more evenly. With a pure organic SERP (34.2% for position 1), positions 2 through 5 still capture meaningful click share. This is where CTR optimization has the most leverage — small improvements in title tags, meta descriptions, and structured data can shift the click distribution in measurable ways.
Commercial queries are the most competitive. When ads, shopping results, or knowledge panels appear, organic position 1 drops to 13–19% CTR. These queries have the most SERP features competing for attention, and the organic results that do earn clicks must work harder to stand out visually.
For a deeper examination of how zero-click searches intersect with this data, and why the trend matters for any system that depends on user clicks, see the zero-click research page.
Year-over-Year CTR Trends
CTR benchmarks are not static. They shift as Google modifies the SERP layout, introduces new features, and changes how much screen real estate is allocated to organic results. The GrowthSRC 2025 study, which tracked 200,000 keywords using Google Search Console data, provides the clearest year-over-year comparison.
| Position Group | YoY Change | Direction | Interpretation |
|---|---|---|---|
| Position 1 | -32% | Decline | CTR fell from ~28% to ~19%. Largest absolute decline of any single position. |
| Position 2 | -39% | Decline | Steepest percentage decline. Position 2 is most affected by SERP feature expansion. |
| Positions 1–5 (avg.) | -17.92% | Decline | Top of page 1 is losing clicks to SERP features and zero-click behavior. |
| Positions 6–10 (avg.) | +30.63% | Increase | Bottom of page 1 is gaining click share as scrolling behavior shifts. |
Source: GrowthSRC (2025), 200,000 keywords tracked via Google Search Console. Year-over-year change in average CTR.
Two Diverging Trends
The data reveals two simultaneous but opposite trends:
1. The top of page 1 is losing clicks. Positions 1 through 5 experienced an average CTR decline of 17.92%. Position 2 suffered the worst decline at 39%. The cause is straightforward: Google is placing more elements above and among the top organic results — AI Overviews, featured snippets, People Also Ask boxes, and ad placements. Each additional feature pushes organic results lower and gives searchers more reasons to find answers without clicking.
2. The bottom of page 1 is gaining clicks. Positions 6 through 10 saw a 30.63% average CTR increase. This is counterintuitive but logical. As SERP features push the top organic results further down the visible page, users must scroll more to see any organic results at all. This scrolling behavior exposes positions 6–10 to more users than before. In effect, the "above the fold" line has moved, and what was once the bottom of the page is now the middle of the visible content.
If a page ranks in positions 6–10, the CTR opportunity is actually growing, not shrinking. This has implications for NavBoost-aware SEO strategy: pages at the bottom of page 1 have an increasing chance of accumulating the click signals needed to move up. Meanwhile, pages at the very top may see their click dominance erode even as they maintain their rank.
What This Means for NavBoost
NavBoost is Google's click-based re-ranking system. It uses aggregated user click behavior — collected over a 13-month rolling window — to adjust search result rankings. The CTR data on this page provides the raw material that NavBoost operates on. Several implications follow from the data.
Fewer Total Clicks, More Signal per Click
With 58.5% of US searches ending in zero clicks, the total pool of organic clicks is smaller than ever. But NavBoost does not need a large absolute number of clicks — it needs a statistically significant pattern. When total clicks decrease, each remaining click represents a more deliberate, more intentional user action. A click in a world of AI Overviews and instant answers carries more informational signal than a click in the era of ten blue links, because the user chose to click despite having other ways to get the answer.
This is why CTR decline does not mean NavBoost is becoming less important. The opposite may be true: as clicks become scarcer, they become more valuable as ranking signals.
Position Bias and the Squashing Function
The steep CTR curve from position 1 to position 10 illustrates position bias — users click higher results partly because they are higher, not only because they are more relevant. Google accounts for this through what the leaked API documentation refers to as a squashing function. This function normalizes click signals by the expected CTR for each position, so that a click at position 8 is weighted differently than a click at position 1.
Without this normalization, NavBoost would simply reinforce existing rankings (a "rich get richer" effect). The squashing function is what allows NavBoost to detect genuine relevance signals — cases where a lower-ranked result is getting more clicks than expected for its position, suggesting it deserves to rank higher.
SERP Features Complicate the Signal
The wide variance in CTR by SERP type (from 46.9% down to 13.7%) means that NavBoost cannot use a single expected-CTR curve for all queries. The system must account for the specific SERP layout shown to each user. A position 1 CTR of 20% is below average on a clean organic SERP but above average when an AI Overview, ads, and a knowledge panel are all present.
The five click types revealed in the Google API leak — including good clicks, bad clicks, and last longest clicks — suggest that NavBoost goes well beyond simple CTR counting. It evaluates the quality and pattern of clicks, not just their frequency.
Methodology Notes
Understanding how each study collected its data is essential for interpreting the numbers. Methodological differences explain most of the variation between studies.
Sample: Proprietary client data across multiple verticals.
Method: Aggregated Google Search Console data from client accounts. Filtered for organic results and excluded branded navigational queries in some analyses.
Strengths: Up-to-date (2026 figures). Includes vertical-specific breakdowns.
Limitations: Client base may skew toward specific industries. Sample size not publicly disclosed. Highest position 1 CTR of any study, possibly due to SERP composition filtering.
Sample: 4 million Google search results.
Method: Clickstream data analysis. Examined click patterns across a broad keyword set without filtering by SERP type.
Strengths: Large sample. Widely cited and peer-reviewed by the SEO community. Includes analysis of position-specific anomalies (e.g., the position 5 and position 10 effects).
Limitations: Clickstream data can overrepresent certain demographics. Study dates to an earlier period and may not fully reflect current SERP layouts.
Sample: 80 million keywords tracked in Google search results.
Method: Proprietary ranking data combined with clickstream analysis. Provides CTR segmented by SERP type (sitelinks, featured snippets, ads, etc.).
Strengths: Largest keyword sample. Most granular SERP-type breakdown publicly available. Covers navigational, informational, and commercial intent.
Limitations: Methodology for combining ranking data with click data not fully disclosed. European market may be overrepresented.
Sample: 200,000 keywords tracked via Google Search Console.
Method: Direct Google Search Console data analysis with year-over-year comparison. Focused on positions 1 and 2 and on CTR trends over time.
Strengths: Uses first-party Google data (Search Console), which is the most reliable source for actual CTR. Year-over-year trend data is unique among these studies.
Limitations: Smaller keyword sample. Limited positional coverage (primarily positions 1–2). Client base composition may influence results.
Sample: 750 billion impressions across Google search results.
Method: Aggregated Google Search Console data from a large enterprise client base. Reports desktop-specific CTR figures. Includes page 2 data (positions 11–20).
Strengths: By far the largest impression-based dataset. Includes page 2 positional data that most studies omit. Enterprise client base provides commercial-intent keyword coverage.
Limitations: Reports the lowest position 1 CTR (8.17% desktop), reflecting the inclusion of all SERP types including heavily featured ones. Enterprise-skewed data may not represent long-tail queries accurately. Desktop-only figures may not reflect mobile behavior.
Reconciling the Data
When using this data for planning or benchmarking, the following heuristics may be helpful:
- For navigational/branded queries: Use the higher end of the range (First Page Sage or SISTRIX sitelinks data). Position 1 CTR of 35–47% is realistic.
- For informational queries with minimal SERP features: Use mid-range estimates (Backlinko or SISTRIX pure organic). Position 1 CTR of 27–34% is reasonable.
- For commercial queries with ads and SERP features: Use the lower end (seoClarity or SISTRIX with ads). Position 1 CTR of 8–19% reflects reality for competitive terms.
- For queries with AI Overviews: Apply a further 50–70% reduction from the clean organic baseline. See AI Overviews & CTR Impact.
The Zero-Click Context
All of the CTR data above exists within a broader trend: the growth of zero-click searches. According to Semrush (2025), 58.5% of US Google searches end without a click on any result — organic or paid. SparkToro's research puts the figure even higher for mobile searches.
This has two implications for interpreting CTR data:
First, CTR figures are calculated on impressions, not on searches. A CTR of 39.8% for position 1 does not mean 39.8% of all searches result in a click on position 1. It means 39.8% of searchers who see a result in position 1 click on it. If the result is below an AI Overview and a user never scrolls down to see it, that impression may not even register.
Second, the zero-click trend is accelerating. 75% of searchers never scroll past page 1. When 58.5% of searches produce zero clicks and 75% never see page 2, the organic click pool is concentrated in a narrow band: positions 1 through 10, on queries where the SERP does not provide an instant answer. This is the exact territory where NavBoost operates.
For the complete analysis, see Zero-Click Searches: What the Data Shows.
Frequently Asked Questions
What is a "good" CTR for my position?
There is no universal answer. A "good" CTR depends on the SERP layout for your target query. If your keyword triggers a clean organic SERP with no ads or features, a position 3 CTR of 11% is roughly average. If your keyword triggers an AI Overview, ads, and a People Also Ask box, then 5% at position 3 may be above average. Compare your Google Search Console data to the benchmarks above, but match the comparison to your specific SERP context.
Which study should I trust most?
No single study is "best" — each answers a different question. Use seoClarity for the most conservative, all-inclusive baseline. Use First Page Sage for the most optimistic, clean-SERP scenario. Use SISTRIX for the most granular intent-based analysis. Use GrowthSRC for year-over-year trend direction. Use Backlinko for the most widely cited general benchmarks.
Does CTR differ between mobile and desktop?
Yes. Mobile CTR for position 1 is generally lower than desktop CTR for position 1, because mobile SERPs display more features (local packs, carousels) and less organic content above the fold. seoClarity's 8.17% figure is desktop-specific; mobile position 1 CTR is likely lower. Most other studies in the composite table do not segment by device, so their figures represent a blended average.
Does NavBoost use raw CTR or adjusted CTR?
Based on the Google API leak documentation, NavBoost uses an adjusted form of click data, not raw CTR. The squashing function normalizes click signals by position to account for position bias. Additionally, NavBoost tracks multiple click types (good clicks, bad clicks, last longest clicks) rather than treating all clicks equally. Raw CTR is an input to the system, not the signal itself.
How can I improve my CTR?
The primary levers are title tag optimization, meta description copywriting, structured data markup (for rich snippets), and URL structure. For a comprehensive guide, see How to Improve Organic CTR. The key insight from NavBoost is that CTR improvements do not just increase traffic — they may also improve rankings through the click signal feedback loop.
How often does this data change?
CTR benchmarks shift gradually as Google modifies the SERP layout. Major changes (like the introduction of AI Overviews) cause abrupt shifts. The year-over-year data from GrowthSRC shows that changes of 17–39% per year are possible for individual positions. This page is updated as new studies are published. The underlying data sources are re-evaluated at least annually.
Is it worth targeting page 2 keywords?
From a pure traffic perspective, page 2 delivers minimal clicks (0.63% of searchers click any page 2 result). However, from a NavBoost perspective, a page 2 ranking means Google already considers the page somewhat relevant. The 13-month aggregation window means that consistent, even small, click activity on a page 2 result accumulates over time. The strategic play is not to optimize for page 2 — it is to use page 2 rankings as a stepping stone to page 1, where the click volume needed for meaningful NavBoost signals exists.
For the complete list of studies referenced on this page and throughout the site, see NavBoost Research Sources.