Between 20 and 26 July 2026, AI assistants sent kingy.ai 88 visits. Over the same seven days, AI crawlers requested 59,643 pages from us.
That is 678 pages taken for every visit returned. We are publishing the number because almost nobody publishes their own, and because the argument about AI and web traffic has been running for two years on figures that disagree by more than an order of magnitude.
Today we are launching the Kingy AI Referral Index: a quarterly, versioned reconciliation of every published study measuring AI-driven referral traffic. It catalogues the primary research, explains where the studies actually disagree, and publishes what survives.
Our own books first
An index that grades other people’s measurement should show its own. Ours:
- 1.3% of our pageviews came from AI assistants (20–26 July 2026).
- 678 : 1 crawl-to-refer ratio over the same seven days.
The share figure is not a fluke of the window. The trailing twelve months to 30 June give 1.329%, against 1.328% for that week — two independent periods agreeing to three decimal places.
Two caveats travel with those numbers, and both cut against us. Our pageview counter is a JavaScript beacon, so it undercounts readers running blockers, while crawlers are counted server-side and cannot be undercounted — the true ratio is therefore lower than 678:1. And any assistant that strips the referrer header is invisible in the numerator, so 1.3% is a floor rather than an estimate. We publish the ratio because the direction is unambiguous even after those corrections, not because the number is precise.
The studies disagree by more than an order of magnitude
Depending on which research you cite, AI referrals are a rounding error or a structural shift:
- Conductor puts AI at 1.08% of all website traffic across 13,770 domains and 3.3 billion sessions.
- Chartbeat reports less than 1% of pageviews across its network of news and media sites — while Google Search fell 34% and Google Discover fell 16% over the same period.
- Pew Research Center found users clicked a search result on 8% of visits where an AI summary appeared, against 15% where none did.
- Ahrefs measured a 34.5% lower click-through rate for top-ranking pages across 300,000 keywords.
- Cloudflare published a crawl-to-refer ratio for Anthropic of 70,900:1 in a single week — and 0.1:1 for Mistral. Five orders of magnitude, same week, same method.
These are not all wrong. Most of the spread resolves into seven recurring differences in what was measured — what we call the Seven Deltas. Three examples.
The denominator
Share of what? Our own week is 1.3% of pageviews and 2.8% of referred traffic. Same data, two numbers, both correct. Most published figures do not say which question they answered.
Category mix
Inside one study, one method and one dataset, Conductor reports Information Technology at 2.80% and Communication Services at 0.25% — an eleven-fold spread with no methodological difference at all. A cross-industry average tells you very little about your own industry.
The small-base problem
Chartbeat reports ChatGPT referrals growing more than 200% year over year and AI accounting for less than 1% of pageviews. Both are true. Quoted alone, the first implies a transformation the second rules out: tripling a sub-1% channel leaves it a sub-3% channel. Growth figures without their base are the most common way these numbers mislead — and they mislead in the direction of whoever is quoting them.
What Wave One does not claim
The index tiers every study. Tier A means method, sample, denominator and window can each be established from a primary source. Tier B is quarantined — catalogued in full, excluded from every reconciled figure. Quarantine is not an accusation that a number is wrong; it is a statement that we cannot check it.
By that standard, Wave One is thin, and the page says so rather than hiding it:
- Retail and commerce publishes no figure. The widely quoted retail numbers all trace to a single vendor’s analytics, and we could not reach that primary source to verify sample, window and denominator. We would rather show a gap than repeat a figure we have not read at source.
- Publishers and B2B each rest on one measurement method, so both cards say plainly: treat as one study with error bars, not a reconciliation.
Every value is recorded exactly as published. A range stays a range and is never collapsed to a midpoint. “Less than 1%” is charted as a bounded span, not the point 1%. Where a source published a comparison rather than a figure — as Pew did — it is catalogued and excluded from the chart, and the exclusion is counted on the page. We would rather the chart be visibly incomplete than quietly wrong.
Use it
The full catalogue is downloadable as CSV, the chart as SVG and PNG, all under CC BY 4.0 — republish, chart and build on it, including commercially, with attribution and a link.
The methodology is versioned and every change is logged rather than applied silently. Waves are quarterly; each is archived at publication and never altered afterwards, so a figure cited today stays checkable. Wave Two lands October 2026, and its first job is the retail gap.
Read the Kingy AI Referral Index →
Corrections and methodology questions are welcome. If you believe a record misstates your study, tell us and we will check it against the primary source.