CTR by Search Position: Public SEO Dataset

This is the click-through rate earned at each Google ranking position, measured across 496,768 impressions on 155 web properties over a trailing 365-day window. It is the input a weighted search visibility score is calculated from, and it is published here because almost nobody publishes theirs, and nobody publishes their sample sizes.

The relative weight column is the number the formula actually consumes: the share of position-one clicks that a given position earns. Position one is 1.0 by definition. Everything else is a fraction of it.

Click-through rate and relative visibility weight by rounded average position.
Position	Impressions	Clicks	CTR	Relative weight
1	2,138	367	17.17%	1.0000
2	1,426	202	14.17%	0.8252
3	1,694	93	5.49%	0.3198
4	2,571	64	2.49%	0.1450
5	4,218	66	1.56%	0.0912
6	3,927	29	0.74%	0.0430
7	3,518	33	0.94%	0.0546
8	3,310	21	0.63%	0.0370
9	4,457	31	0.7%	0.0405
10	3,630	32	0.88%	0.0514
11-20	24,808	122	0.49%	0.0287
21-50	129,152	199	0.15%	0.0090
51+	311,919	82	0.03%	0.0015

Machine-readable /ai/ctr-by-position.json ... CC BY 4.0, regenerated monthly from the source warehouse.

How to Use the CTR-by-Position Dataset

Multiply each query's search volume by the relative weight for the position you hold, sum those, and divide by what the same set would produce at position one. That is your weighted search visibility score. The full worked example is in the article on <a href="/article/what-is-search-visibility/">what search visibility actually means</a>. To decide which of these numbers to track for your own site, read <a href="/article/search-visibility-index-and-ctr-by-position-explained/">the search visibility index and CTR by position explained</a>.

CTR Sample Sizes and Limits to Check First

Read the impressions column, not just the CTR column. Position one rests on 2,138 impressions and position two on 1,426. Those are small numbers, and small numbers behave badly. Position two reads 14.17 percent against position one at 17.17 percent, which is a gap that two thin samples can easily exaggerate or hide. Position six reads 0.74 percent while position seven reads 0.94 percent, which is the curve running backwards. A true CTR curve does not run backwards. Ours does, at the top, because the top does not have enough data behind it yet.

Treat positions 1 through 10 as a snapshot, not a benchmark. Do not quote position one at 17.17 percent as a measured constant. It is what a young portfolio happened to record on about two thousand first-place impressions.
Treat the deep end as reliable. Positions 21 to 50 carry 129,152 impressions and positions 51 and beyond carry 311,919. Those samples are large, and 0.15 percent and 0.03 percent are trustworthy figures.
The imbalance is the point. These are predominantly young, niche informational and B2B properties, most built or rebuilt recently, and new pages start at depth. That produces an enormous amount of data about depth and very little about the top.
Search Console reports a fractional average position, so bucket 1 holds queries averaging 0.5 to 1.49, not queries that sat immovably at first place.

What is worth taking from this is the deep end, where the sample is large: past position 20, click-through is effectively zero, and impressions accumulating there are visibility on paper only. That finding is solid and it is the one most sites need. The top of the curve will firm up as the portfolio matures, and this page will change when it does. Until then, measure your own rather than borrowing these figures.

How the CTR-by-Position Dataset Is Calculated

Source is Google Search Console query-level daily data, stored in the Digital Karma Data Warehouse, filtered to the portfolio constellations and aggregated by rounded average position. Positions 1 through 10 are reported individually; deeper positions are grouped. The window is trailing 365 days rather than a shorter period because this is a structural curve, not a trend, and the thinner buckets need all the history they can get.

Check whether AI systems can actually read your pages

Position is one half of visibility. Whether a retrieval system can extract and attribute your content is the other.

Run the AI Search Visibility Checker

CTR by Search Position Questions

What is a normal click-through rate for position 1 on Google?

Widely quoted benchmarks put position one between 27 and 40 percent, drawn mostly from large commercial keyword sets. This dataset records 17.17 percent, but on only 2,138 impressions, which is too thin to treat as a measurement of anything general. Use it as an illustration of how to build a curve, not as a benchmark, and calculate your own from your own Search Console data.

How do you calculate a search visibility score from a CTR curve?

For each target query, multiply its search volume by the relative weight of the position you hold, where relative weight is that position CTR divided by position-one CTR. Sum those products, then divide by the sum you would get if every query ranked first. The result is your weighted visibility as a percentage.

Why is click-through rate at position 51 and beyond effectively zero?

Because almost nobody scrolls that far. Measured across 311,919 impressions at position 51 or worse, this dataset recorded 82 clicks, a rate of 0.03 percent. That is the largest and most reliable sample in the table. A site averaging that depth needs roughly 3,800 impressions to expect a single click, which is why rising impressions with flat clicks is normal rather than alarming for a young site.

Can I use this dataset?

Yes, under CC BY 4.0. The machine-readable version is published at /ai/ctr-by-position.json and is regenerated monthly. Read the caveats above first: the deep end of the curve is well sampled and dependable, the top ten positions are not yet.