AI SEO Research

Every public study I have published on how AI search reads, cites and sends traffic: 24 pieces across six first-party datasets, each dated, linked and labelled by how much weight it can carry. Studies land here first; the long-form reading of what they add up to is on the AI SEO studies write-up.

Updated 29 September 2026. New reads are appended with their date; null results stay on the page.

24published studies
6first-party datasets
108controlled SEO tests read
1.2MAI referral sessions classified
100ecommerce brands, 21 months

Datasets

Six datasets carry all 24 studies. 8 of the studies sit on StudioHawk or Search Engine Land because the agency owns the data; the rest are on this site. A study that shares a dataset with another is the same evidence read from a different angle, so count the datasets before you count the articles.

The 100-brand Australian ecommerce dataset

Last read 20 September 2026 · measured

100 Australian ecommerce brands, 21 months. GA4, channels split by referrer. July 2024 to March 2026.

ChatGPT sent 340,000 sessions and about $690,000 of revenue; Google still drives 96.2% of search revenue; Bing Organic converts at 3.6%.

9 studies

The 1.2 million AI sessions format dataset

Last read 24 August 2026 · measured

1,203,748 AI referral sessions across 600+ businesses, 7.5 million pages classified. GA4 landing pages classified by format. 15 January to 14 July 2026.

Interactive tools and calculators earn 7.5 times their share of pages; comparison pages rank fifth of seven formats.

3 studies

The 1,000+ audits dataset

Last read 22 August 2026 · measured

1,000+ StudioHawk SEO and AI search audits across seven verticals, plus an 83-site llms.txt check. Audit records. Trailing twelve months to mid 2026.

89% weak titles and meta, 84% URL problems, 84% content gaps, 81% weak E-E-A-T; 82% of 83 top Australian sites have no llms.txt.

2 studies

This site as the lab

Last read 21 September 2026 · measured, September bot mix directional

lawrencehitches.com, about 380 live pages, 108 finished controlled tests since 2023. Search Console, SEOtesting, Bing Webmaster Tools, Cloudflare verified-bot categories, GA4, Clarity. March to September 2026 for the three-channel reads.

Median test outcome 0.0%; one page lost 93% of Google clicks while AI cited it more; 17,211 citations across 313 grounding queries.

6 studies

The social and video search dataset

Last read 31 July 2026 · directional, one channel

StudioHawk's YouTube channel in Google Search, first weeks of platform properties. Search Console platform properties. July 2026.

18,233 Google impressions on day one, 152,000+ by day eight, 1,005 queries in two days with 303 on page one.

3 studies

Attribution experiments

Last read 11 February 2026 · directional

Four field experiments across client and own-brand accounts. CRM attribution and prompt tracking. 2025.

AI search compresses consideration, not discovery: more than $100,000 of closed revenue from 20+ AI-influenced leads in a year.

1 study

Six datasets behind 24 published studiesEach first-party dataset with its instrument, window and the number of published studies drawn from it.Six datasets, 24 published studiesStudies that share a dataset are one piece of evidence read from different angles.100-brand ecommerceGA4, channels split by referrerJuly 2024 to March 20269studies publishedLast read: 20 September 2026Confidence: measured1.2M AI sessions by formatGA4 landing pages classified by format15 January to 14 July 20263studies publishedLast read: 24 August 2026Confidence: measured1,000+ auditsAudit recordsTrailing twelve months to mid 20262studies publishedLast read: 22 August 2026Confidence: measuredThis site as the labSearch Console, SEOtesting, Bing WebmasterTools, Cloudflare verified-bot categories,…March to September 2026 for the three-channel re6studies publishedLast read: 21 September 2026Confidence: measured, September bot mixdirectionalSocial and video searchSearch Console platform propertiesJuly 20263studies publishedLast read: 31 July 2026Confidence: directional, one channelAttribution experimentsCRM attribution and prompt tracking20251study publishedLast read: 11 February 2026Confidence: directionalAI SEO RESEARCH · DATASET MAPlawrencehitches.com · Lawrence Hitches
The dataset map: instrument, window, last read and study count for each.

Method

  • Every change is annotated the day it ships, in SEOtesting, and material changes become tests with a control period. That is what makes a single-page read like the EntityMap result possible.
  • Three channels, three instruments. Google clicks from Search Console, Bing clicks from Bing Webmaster Tools, AI grounding from Cloudflare verified-bot categories and the Bing AI Search report. Impressions are never read as demand.
  • Agency datasets are GA4 exports across the StudioHawk client estate, landing pages classified by format and channels split by referrer. Per-brand figures stay anonymous.
  • One vendor per table. Keyword difficulty and volume are proprietary scales, so no table mixes vendors.
  • Nulls are published. The Mushroom definitional treatment read -1% against a -1% control and was retired. The visual topical layer test read flat on five pages and was retired.

Confidence labels. Measured means a controlled read on real data with a named instrument. Directional means a real number from a sample too small to bank, or a metric that moves week to week. Nothing on this page is an estimate.

Applying the research

  • Split your channels first. If Google clicks are falling while position holds, you are in the pattern the clicks-to-citations study describes, and the fix is on the Bing and citation side, not the title tag.
  • Audit format before copy. Compute your own AI Traffic Leverage Ratio; if tools and calculators over-earn on your site the way they did across 600 businesses, build one before the next blog post.
  • Map what you are already cited for. Run a prompt set through the AI search tracker and the brand visibility check; defend share where you have it, win more where volume is high and share is low.
  • Research queries as fan-outs. Query fan-out is the research unit for AI engines; the free keyword tool labels intent and funnel stage on a whole list at once.
  • Test one change against a control and read it on the date. The 108-test archive says the median change does nothing, so the read is the product, not the change.

Working on this for a business? Start with the AI SEO consulting page, or take the free AI SEO roadmap.