Every SEO blog quotes a zero-click statistic from someone else's study. We had a 16-month Search Console export sitting in the repository, so we ran the numbers on ourselves instead. The result was worse than the headlines we had been citing — and the shape of it was not what we expected.

TL;DR — four findings

1. 763 of 995 non-brand queries (77%) earned zero clicks, across 474,117 impressions.
2. Ranking top-10 did not rescue them: 72 queries sat inside the top 10 and still earned zero clicks across 30,449 impressions.
3. Question-shaped queries were hit hardest. At positions 1–5 they earned 0.144% CTR versus 2.749% for conventional short queries — a ~19× gap at the same positions.
4. Geography mattered more than we assumed: the US returned 876,622 impressions at 0.07% CTR while India returned 28,702 at 3.35% — about 48×.

Editorial disclosure

theStacc sells SEO automation software, so we have a commercial interest in how you read this. We have tried to keep that out of the numbers: every figure below is computed directly from our Search Console export, the method is described so you can reproduce it on your own data, and the limitations section lists what this data cannot tell you — including the fact that it cannot prove AI Overviews are the cause.

The dataset

One property, thestacc.com, exported from Google Search Console on 2026-08-14 over a 16-month window. The query-level export contains 1,000 rows totalling 557,424 impressions and 975 clicks. We separated brand queries (any containing "stacc") from non-brand, because brand traffic behaves nothing like discovery traffic and mixing them hides the effect entirely.

SegmentQueriesImpressionsClicksCTR
Brand51,89064334.0%
Non-brand995555,5343320.060%

Five brand queries produced 66% of all clicks from 0.3% of impressions. Everything interesting is in the other 555,534.

Finding 1 — position stopped predicting clicks

The classic CTR curve says position 1–3 earns somewhere around a quarter of clicks. Our non-brand data does not resemble that curve at any point.

Avg positionQueriesImpressionsClicksCTR
1–3162,876120.417%
3–5312,529281.107%
5–1012030,3601080.356%
10–20192141,813920.065%
20–40320201,303530.026%
40+316176,653390.022%

Two things stand out. Most of our impressions (68%) sit below position 20, which is a content-quality and authority problem we own. But the top of the curve is the surprise: positions 1–3 returned 0.417% CTR. Sixteen queries, 2,876 impressions, twelve clicks.

Finding 2 — 72 top-10 queries earned nothing at all

Filtering to non-brand queries with an average position better than 10 gives 167 queries. Of those, 72 earned zero clicks across 30,449 impressions. The largest:

QueryAvg positionImpressionsClicks
social media scheduling tools free9.91,3400
what is a content audit2.41,2950
free social scheduling tools6.81,1130
characteristics of ai written blog posts 20266.91,0700
free scheduling tools for social media6.59770
free social scheduler6.09210
which ai sales rep is best for discovering and messaging…2.98920

A query at average position 2.4 with 1,295 impressions and not one click is the single most useful number in this study. Whatever is happening, it is not a ranking failure.

Finding 3 — question-shaped queries were hit hardest

We split non-brand queries into two groups: conversational (starts with what / which / how / why / is / can, contains a question mark, or runs seven words or longer) and conventional (everything else — the short keyword phrases SEO has optimised for since 2010). Then we compared CTR within the same position bands, so position is held roughly constant.

Position bandConversational CTRConventional CTRGap
1–50.144% (13 q, 4,168 imp)2.749% (34 q, 1,237 imp)~19×
5–100.073% (32 q, 10,974 imp)0.516% (88 q, 19,386 imp)~7×
10–200.312% (17 q, 3,840 imp)0.058% (175 q, 137,973 imp)inverted

At the top of page one — where it matters — a question-shaped query converted roughly 19× worse than a conventional query at the same position. Below position 10 the relationship inverts, but with only 17 conversational queries in that band we treat that row as noise rather than a finding.

The honest reading: the better a query looks like something you would ask an assistant, the less a good ranking is worth. We cannot prove why from this data (see limitations), but it is consistent with answer surfaces resolving the question before the user reaches a result.

Finding 4 — the same content, 48× different outcomes by market

CountryImpressionsClicksCTRAvg position
United States876,6226460.07%26.5
United Kingdom112,9392150.19%31.0
Germany67,7061370.20%22.7
India28,7029623.35%17.3
Pakistan8,1981581.93%12.8

India delivered more clicks than the United States from 3% of the impressions. Part of that is position (17.3 vs 26.5), but position alone does not explain a 48× CTR spread. If you plan international SEO on impression volume, this is the trap: the market that shows you the most impressions may be the one returning the least traffic.

Method — reproduce this on your own data

  1. Search Console → Performance → Search results, set the date range to 16 months, export Queries, Pages, Countries and Devices as CSV.
  2. Split queries into brand and non-brand by substring match on your brand name. Report them separately; do not average them together.
  3. Bucket non-brand queries by average position and compute clicks ÷ impressions per bucket.
  4. Classify each query as conversational (leading question word, question mark, or ≥7 words) or conventional, then compare CTR within each position band so position is controlled.
  5. Count the queries with clicks = 0 and sum their impressions. That total is your zero-click exposure.

What this data cannot tell you

Limitations — read before citing

One site, one niche. This is thestacc.com only, in SEO/marketing software. It is a case study, not an industry benchmark, and our absolute CTRs are low partly because most of our impressions sit below position 20.

The export is truncated. The Search Console UI returns at most 1,000 rows per dimension, so the query table is the top 1,000 by impressions, not the full long tail.

No query-to-page pairing. The UI export does not join queries to landing pages, so we cannot attribute a query's performance to a specific page.

AI Overviews are not measured. Search Console does not report whether an AI Overview appeared. The link between conversational queries and near-zero CTR is a correlation in our data. We are not claiming a proven cause, and neither should anyone citing this.

Small samples at the top. The position 1–5 conversational bucket is 13 queries. It is directionally striking, not statistically robust.

Aggregate, not a time series. A 16-month total cannot show when the change happened, so we make no before/after claim about any algorithm update.

What we changed because of it

We are acting on our own data rather than filing it. Concretely: we stopped treating impression growth as progress, because 474,117 of our impressions produce nothing; we started measuring commercial queries separately from informational ones, since the informational side is where the clicks vanish; and we stopped expanding into locales on impression counts alone — our best non-English market earned 99 clicks in 16 months, which is a signal to consolidate rather than translate more.

If you want the shorter version of the lesson: rankings are no longer the deliverable. If you are buying SEO on a ranking report, ask what it earned.

Want the same analysis on your own Search Console data?

The method above is deliberately reproducible by hand. If you would rather it ran continuously — with commercial and informational queries tracked separately — that is what theStacc does.

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Data & sources

Primary source (first-party)
  1. [01]Google Search Console performance export for thestacc.com, 16-month window, pulled 2026-08-14 — queries, pages, countries, devices.
  2. [02]Figures computed from that export: 557,424 impressions / 975 clicks at query level; 1,329,155 impressions / 4,107 clicks at page level (the two exports cover different row limits, so totals differ).
  3. [03]Method and limitations as stated above. No third-party study, estimate, or modelled figure is used anywhere on this page.
Siddharth Gangal

Siddharth Gangal

Founder · theStacc · IIT Mandi · Ex-Arka 360

Siddharth founded theStacc after watching good local businesses lose Map Pack and blog traffic to competitors who simply published more, more often, across more channels. He writes about SEO at scale, multi-location growth, and the unglamorous tactics that actually move rankings.