How I reviewed 221 AI visibility publications

348 professionals from the TrustRadius buyer community and social channels; online survey August 2025

45% of all buyers and 51% of enterprise buyers used AI in software buying; use reached 65% among C-suite respondents. Among users, 94% found it helpful or very helpful.

Small, recruited sample with subgroup bases not fully visible on the public page; separate 2025 wave from B04.

Already admitted to the evidence register

Similarweb worldwide web and app panel; June 2025-May 2026; visits, unique visitors and app downloads are separate denominators.

Generative-AI platforms averaged 9.5B monthly web visits; ChatGPT category share fell from about 76% to 53% while Gemini and Claude grew.

does not measure buying influence.

Large behavioral panel directly establishes adoption growth and multi-platform fragmentation; does not measure buying influence.

Gemini app monthly active users reported in Alphabet Q2 2026 earnings remarks

Alphabet reported 950M monthly active Gemini app users in Q2 2026.

WAU and MAU are deliberately different denominators and may include different surfaces, account rules and geography. These figures prove scale, not discovery influence, and must never be used as a platform-share comparison.

Already admitted to the evidence register

Product-level weekly active ChatGPT accounts

OpenAI reported more than 900M weekly active ChatGPT users in May 2026.

WAU and MAU are deliberately different denominators and may include different surfaces, account rules and geography. These figures prove scale, not discovery influence, and must never be used as a platform-share comparison.

Already admitted to the evidence register

More than 50,000 sites, 17 industries; worldwide mobile and desktop; January-December 2025; channel shares calculated as medians across tracked domains

AI-referral traffic rose 66.02%, from 462M to 767M monthly visits, but represented only 0.14% of total traffic. Organic search represented 16.04%. Google AI Mode was 0.01%

AI means identifiable referrals, not exposure. Domain medians and aggregate volumes answer different questions. Computer software/development declined 26%, a warning against treating global growth as a SaaS benchmark. Likely related to Semrush's broader Traffic & Market data assets.

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More than 1B rows from a US mobile-and-desktop clickstream; October 2024-February 2026

Outbound ChatGPT referrals rose 206% in 2025; 21.6% of referrals went to Google in February 2026; the ten largest recipient domains received more than 30%. Web search was enabled for 34.5% of prompts in February 2026, down from 46% in late 2024

Actual panel-user base and weighting are not disclosed in the post. A referral is a next navigation, not necessarily incremental demand. Same Semrush/Datos panel family as other Semrush clickstream studies unless confirmed otherwise.

Already admitted to the evidence register

260B clickstream rows; US desktop; January 2024-June 2025. Treatment: users first observed using ChatGPT in Q1 2025; control: users never observed using it; Google sessions 90 days before/after, with a longer January 2024 cohort

No statistically significant fall in Google sessions after first ChatGPT use; the point pattern was slightly positive

Observational adoption cohorts, desktop only, self-selection and seasonality. “No reduction in Google sessions” does not mean no individual query substitution. Same Datos/Semrush panel; do not count independently from A2/A4 when making a market-level conclusion.

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Worldwide; web visits and unique visitors plus separately measured app downloads; June 2025-May 2026

Generative-AI platforms averaged 9.5B monthly web visits, +70% YoY; 655M monthly unique visitors, +57%; ChatGPT's share of category web visits fell from about 76% to 53%, while Gemini rose from under 9% to about 27-28% and Claude from about 2% to nearly 9%

Visits are not users, prompts, buying tasks or influence. Web and app measures are not interchangeable. Treat all Similarweb articles drawing from this edition as one rolling panel family.

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Multi-million-device panel; US desktop only; monthly and 10+-use thresholds; January 2023-June 2025

Nearly 40% used at least one named AI tool monthly and just over 20% did so 10+ times monthly; traditional search remained above 95% monthly and 86% at 10+ uses. Heavy AI use rose from about 3% to 21%

Excludes mobile browsers/apps; tool-domain visits are an imperfect proxy for use; not B2B. Datos is owned by Semrush, so this is not independent of Semrush/Datos clickstream work.

Already admitted to the evidence register

Similarweb web and mobile-app usage panel combining search-engine sessions with search-related AI prompts.

Adding app usage raises estimated AI activity sharply; the analysis estimates total discovery activity grew rather than simply shifting from search.

Important web-versus-app denominator correction; proprietary modeling means exact totals should not be pooled with clickstream-only studies.

Important web-versus-app denominator correction; proprietary modeling means exact totals should not be pooled with clickstream-only studies. JY source 2.

11,500 representative real-user queries across Google organic, AI Overviews and Gemini Flash 2.5

AI Overviews appeared for 51.5% of the benchmark queries and source overlap across search surfaces averaged below 0.2 Jaccard, with lower stability under reruns and minor query edits.

Large public benchmark directly showing that organic rankings do not map cleanly to generative visibility.

Large public benchmark directly showing that organic rankings do not map cleanly to generative visibility.

11,203 categorized US desktop keywords captured August 23 2024, October 17 2024 and January 17 2025; 2,104 had AIOs; shared spreadsheets/screens.

AI Overview source-page volatility averaged 0.68-0.73 over 8-13 weeks, higher than organic rankings; about 70% of AIO pages could change.

sparse time points and a selected keyword set limit platform-wide inference.

Transparent repeated-wave evidence; sparse time points and a selected keyword set limit platform-wide inference.

More than 100M keywords in Germany; SISTRIX CTR/traffic models; AIO prevalence, position and category loss analyzed.

About 20% of keywords showed AIOs; position-one CTR fell from 27% to 11% and estimated aggregate organic click loss was 6.6%.

modeled CTR/lost clicks and proprietary clickstream assumptions.

Large non-US market analysis with category heterogeneity; modeled CTR/lost clicks and proprietary clickstream assumptions.

10M+ keywords January-November 2025; 200K+ keywords for zero-click trends; 11K domains for industry visibility.

AIO prevalence rose from 6.49% in January to 24.61% in July then 15.69% in November, with more commercial/transactional coverage over time.

shares Semrush AIO infrastructure with IND-044 and is not an independent replication.

Large longitudinal update; shares Semrush AIO infrastructure with IND-044 and is not an independent replication.

10,000 categorized US desktop keywords across seven industries in December 2024; keyword and AIO exports shared through Google Drive.

AIOs appeared for 29.9% of keywords but 11.5% of search volume; problem-solving and specific-question intents triggered them most.

one month/desktop/US and hand-built keyword categories.

Transparent intent-based sample with shared data; one month/desktop/US and hand-built keyword categories.

200,000 keywords randomly selected from the Semrush US database, restricted to keywords triggering an AIO September 1-10, 2024; desktop/mobile cuts.

About 80% of desktop AIOs were informational and 82% occurred on keywords below 1,000 monthly searches.

conditioned on ever-triggering AIOs and now temporally old.

Large trigger/composition study; conditioned on ever-triggering AIOs and now temporally old.

Thousands of queries and top-performing websites including Fortune 100 brands; January-August 2025; North America/Europe context in BrightEdge AI Catalyst.

AI search accounted for less than 1% of referrals while organic search drove most conversions; AI referral growth varied sharply by platform.

site/query bases and sampling are described only broadly.

Important contradictory conversion result; site/query bases and sampling are described only broadly.

US consumer market-research panel fielded December 2025; public article provides workflow percentages but requires report for full sample details.

77% of AI-using consumers also used traditional search; 41% started with AI then validated through search and 35% began with search then used AI for synthesis.

consumer self-report and incomplete public base limit transfer.

Directly supports complementarity and validation; consumer self-report and incomplete public base limit transfer.

Survey of 2,509 recent B2B buyers; annual predecessor wave to 2025 Buyer Experience research.

69% of the purchase process occurred before seller engagement; 81% had selected a preferred vendor before speaking with sales.

annual wave shares the 6sense program and is not AI-specific.

Pre-AI-wave commercial baseline for shortlist formation; annual wave shares the 6sense program and is not AI-specific.

Forrester Buyers' Journey Survey 2025; public article reports adoption/change but not sample or full instrument.

94% of buyers reported AI use, and twice as many named generative/conversational search a meaningful source as any other source.

exact denominator, question wording and full methodology are behind the client report.

Direct decision-relevant B2B wave; exact denominator, question wording and full methodology are behind the client report.

Forrester Buyers' Journey Survey 2024; public article reports percentages but not sample size or full survey methods.

89% of business buyers reported GenAI use in at least one purchase-process area; 87% of users said it improved business outcomes, with the largest effect reported for purchases over $1M.

full client report should be obtained before strong quantification.

Highly relevant complexity/enterprise claim but public method is insufficient; full client report should be obtained before strong quantification.

17,014 prompts across six coding-task categories and 30 scenarios; seven LLMs and roughly 500 million tokens

Models showed systematic provider preferences, especially for Google and Amazon services, and sometimes rewrote code to include preferred vendors without being asked.

Exceptionally relevant B2B SaaS/cloud recommendation evidence, though code generation is not identical to explicit vendor evaluation.

Exceptionally relevant B2B SaaS/cloud recommendation evidence, though code generation is not identical to explicit vendor evaluation.

50,000 prompts across seven industries and multiple answer engines; unsolicited assertions/comparisons classified in responses.

Nearly half of AI responses included unsolicited comparisons, opinions or recommendations beyond the user's literal request.

proprietary prompt mix and classifier validation limit certainty.

Supports measuring description/sentiment, not just mention; proprietary prompt mix and classifier validation limit certainty.

Online survey in March-April 2024; 2,164 verified technology buyers and 243 technology vendors from the global TrustRadius network.

78% of shortlisting buyers selected products known before research, rising to 86% for enterprise; 56% spoke with a product user before purchase.

vendor-owned network sample and not focused on AI.

Strong pre-AI comparison for shortlist/brand effects; vendor-owned network sample and not focused on AI.

More than 25,000 US prompts across ChatGPT, Gemini, Copilot and Perplexity in January 2026; 113 brands in six consumer-facing sectors; April 2025 baseline.

Visibility was concentrated and specialists sometimes overperformed larger brands; referrals plateaued while mention-based visibility diverged.

consumer sectors and prompt-selection model limit B2B transfer.

Useful cross-platform category benchmark and bridge from traffic to mentions; consumer sectors and prompt-selection model limit B2B transfer.

112 Product Hunt startups tested across recognition and category-discovery prompts on two models

Models often knew individual startups when named but failed to surface them in unprompted category discovery, revealing a large recognition-to-shortlist gap.

Highly relevant to startup brand visibility, but only two models and a selected startup cohort were tested.

Highly relevant to startup brand visibility, but only two models and a selected startup cohort were tested.

Curated prompts across four brand categories tested on multiple LLMs

Models associated global brands more positively than local brands and produced country-of-origin and income-linked recommendation effects.

Direct brand-visibility and recommendation evidence, although it does not observe real buyers or live web retrieval.

Direct brand-visibility and recommendation evidence, although it does not observe real buyers or live web retrieval.

700,000 ChatGPT conversations with web citations from Q4 2025; conversation-turn and topic/source patterns analyzed.

Most citations appeared in turn one, Wikipedia functioned as a default knowledge layer and source clusters varied by topic.

only citation-bearing conversations and no behavior/outcome link.

Large real-conversation citation analysis; only citation-bearing conversations and no behavior/outcome link.

21,143 citations described with 72 observable features across AI search platforms

Citation presence and actual absorption into the generated answer diverged, and a multi-feature score could predict contribution, but the observational design cannot establish causal source use.

Important distinction between decorative citation and substantive influence, with no causal validation.

Important distinction between decorative citation and substantive influence, with no causal validation.

Feature-level optimization experiments spanning informational and lexical content features

Informational features were more useful than lexical tricks for citation visibility, although the approach was computationally costly and relied substantially on model judges.

Directly informs what content attributes may matter, with explicit evaluation caveats.

Directly informs what content attributes may matter, with explicit evaluation caveats.

Human audit of Bing Chat, NeevaAI, Perplexity and YouChat across diverse query sets

Only 51.5% of generated sentences were fully supported and 74.5% of citations supported their associated proposition, showing that visible citations are not equivalent to reliable evidence.

Audits early commercial engines and citation correctness, but does not measure source selection causally or any downstream click, choice or revenue outcome.

Direct audit of commercial generative-search citations and essential constraint on citation-as-visibility metrics.

100,000 distinct prompts run across ChatGPT and Perplexity; cited sources compared between engines.

The two engines cited substantially different parts of the web, supporting platform-specific source strategies.

only two platforms and proprietary prompt selection.

Clear large cross-engine comparison; only two platforms and proprietary prompt selection.

Approximately 10,000 websites collected from Google's generative and conventional search surfaces

Generative search cited pages with greater semantic similarity and higher language-model predictability than conventional search, indicating a distinct content-selection mechanism.

Early large cross-surface empirical audit, but tied to a changing Google product snapshot.

Early large cross-surface empirical audit, but tied to a changing Google product snapshot.

11.84B citations across eight models, 8,061 active categories April 16-July 16, 2026; 3.02M-domain classification map covering 98.3% of volume.

About 57% of citations were brand-owned sites overall; SaaS/software had only 11.4% earned-media share while model mixes varied widely.

vendor-customer category selection and observational scope remain.

Exceptionally large, well-described current citation dataset with a SaaS cut; vendor-customer category selection and observational scope remain.

26,283 source URLs for top-of-funnel ChatGPT queries; includes 1,100 blog lists and 3,000 cited lists analyzed by authority/category.

Recently updated best-of lists were prominent ChatGPT sources and third-party list placement correlated with brand inclusion.

correlational and focused on selected commercial prompts.

Large format/source analysis relevant to comparison content; correlational and focused on selected commercial prompts.

82,619 qualified prompts, 1,548,213 snapshots, six countries, three platforms and 17 weeks from December 17, 2025-April 8, 2026; 2,556 URLs manually/classifier categorized.

Weekly domain drift was about 56%; platforms differed by more than 80% for the same questions and URL-level drift was higher.

monitored prompts and ChatGPT source-attribution subset remain.

Strong transparent independent-vendor triangulation for instability; monitored prompts and ChatGPT source-attribution subset remain.

One month of browsing data from a representative panel of 900 US adults; mixed-effects logistic regression controlling for panelist and query attributes

Clicks to AIO-cited sources occurred in about 1% of AIO visits, and AIO exposure remained associated with fewer clicks and more session endings after query controls.

Representative behavioral panel with explicit modeling; observational exposure still limits pure causal interpretation.

Representative behavioral panel with explicit modeling; observational exposure still limits pure causal interpretation.

Randomized field experiment using a Chrome extension to show Google with or without AIOs

Conditional on appearing, AIOs reduced outbound organic clicks by 39.8% and increased zero-click searches by 34.5% without measurable improvement in perceived search quality.

Extension-mediated exposure and a short experimental window may differ from native rollout behavior; no purchase or revenue outcome is observed.

Direct randomized field evidence on traffic and experience, unusually strong for this literature.

Production deployment at Pinterest comparing an optimization framework with a control at platform scale.

The authors report about 20% production traffic lift versus control.

Rare production outcome evidence; assignment mechanics and full denominator are insufficiently disclosed for causal certainty.

Rare production outcome evidence; assignment mechanics and full denominator are insufficiently disclosed for causal certainty. Martinez matrix row 41.

About 18,000 consumers in 23 countries plus approximately 200 executives.

Forty-five percent of consumers reported using AI somewhere in the purchase journey.

Large multinational buyer-adoption evidence; self-report and retail scope mean it supports transfer hypotheses, not B2B causal claims.

Large multinational buyer-adoption evidence; self-report and retail scope mean it supports transfer hypotheses, not B2B causal claims. JY source 7.

Controlled pages tested on Bing, Perplexity and LLM browsing plugins

Adversarial page content can steer LLM search preferences across several commercial systems, establishing that retrieved webpages can manipulate downstream recommendations.

Cross-system evidence of commercial vulnerability, though controlled pages are not a normal marketing intervention.

Cross-system evidence of commercial vulnerability, though controlled pages are not a normal marketing intervention.

252,000 controlled trials injecting two competing documents across answer-engine settings

Topical relevance and context position dominated citation probability, while many surface-level content tactics were smaller or inconsistent.

Injected competing documents bypass organic crawling and retrieval, so the large controlled effects are not production visibility estimates.

Large controlled factor study with direct competitive relevance; injected documents still bypass organic retrieval.

54 intervention-domain cases across multiple actors and QA settings

Only three of 54 cases showed a positive effect, none of the QA cases did, and gains approached zero when many competitors adopted the same intervention.

Only 54 intervention-domain cases and largely benchmarked competition; production equilibrium and downstream outcomes remain unobserved.

Important counterevidence to universal GEO tactics and one of the few studies modeling competitive adoption.

Survey of 5,119 US adults conducted February 17-23, 2026; full topline and data downloads available.

44% reported chatbot use; 42% used chatbots to search for information; 38% of employed adults used them for work and 60% read AI search summaries.

self-report and broad consumer population.

Independent current adoption denominator with transparent survey base; self-report and broad consumer population.

Randomized online product-comparison tasks using LLM search or traditional search, plus confidence-highlighting intervention

LLM users finished faster with fewer and more complex queries and similar accuracy when answers were reliable, but over-relied on incorrect outputs; confidence highlighting improved error detection.

Direct decision experiment supporting both efficiency and overreliance mechanisms; initial preprint predates the window but was revised within it.

Direct decision experiment supporting both efficiency and overreliance mechanisms; initial preprint predates the window but was revised within it.

GEO-bench with 10,000 queries; five fixed Google-result documents; GPT-3.5 generations; nine rewrite strategies; 200 post-retrieval Perplexity tests

Quotations, statistics and cited sources can raise a document's relative answer share after it is already in context, with the famous roughly 40% result referring to relative position-adjusted word share rather than traffic or retrieval.

Foundational controlled GEO experiment, but its fixed retrieved context sharply limits organic-discoverability claims.

Foundational controlled GEO experiment, but its fixed retrieved context sharply limits organic-discoverability claims.

Structural page interventions tested across six generative engines

Headings, answer-first organization and other structural changes were associated with citation gains across six engines, but the external validation and human quality checks were limited.

Direct cross-engine structural test with practical value, retained as provisional until stronger validation.

Direct cross-engine structural test with practical value, retained as provisional until stronger validation.

Difference-in-differences exploiting SFW versus NSFW Reddit eligibility for Google AI Overviews

AIO eligibility increased daily comments and commenting users by about 12%, especially for experiential content, but subsequent AI Mode largely eliminated those gains.

Reddit eligibility is an imperfect proxy for overview exposure, and platform-specific community content may not generalize to B2B publishers.

Causal evidence that interface design and content type can reverse whether AI search complements or substitutes for a source platform.

More than 1T US retail visits plus a 5,000+ respondent US survey; January-March 2026; Adobe AI Content Visibility Checker benchmark.

In March 2026 AI-referred visits converted 42% better than non-AI visits; engagement was 12% higher and product-page machine-readability averaged 66%.

comparator mixes channels and remains retail-only.

Large transaction base and latest wave show the conversion reversal; comparator mixes channels and remains retail-only.

Large controlled audit across AI search platforms, verticals, languages and query paraphrases

AI search disproportionately surfaced earned-media sources over brand-owned and social sources, while source diversity, freshness and paraphrase stability varied materially by engine.

Direct multi-platform audit with clear practical relevance, but still an observational snapshot.

Direct multi-platform audit with clear practical relevance, but still an observational snapshot.

1,008 responses overall; 672-response Bing-Perplexity comparison phase

Bing and Perplexity used materially different source pools, with only about 26% domain overlap in the paired phase, undermining any assumption of a single universal AI ranking.

Direct commercial-engine source audit with a clearly reported comparison base.

Direct commercial-engine source audit with a clearly reported comparison base.

15,155 brand-category pairs tracked daily in May 2026; 2,346 complete prompts, 218,178 responses and 2.64B citations across three Google surfaces.

Brands faced a median 8-point visibility gap across Google models; pairwise entity overlap was only about one-third and citation mixes differed.

Large transparent within-provider comparison proves that one Google metric cannot represent all surfaces.

Large transparent within-provider comparison proves that one Google metric cannot represent all surfaces.

4,706 queries comparing Google organic with five generative systems from Google, OpenAI and Perplexity

Source footprints differed sharply by engine, and controllable surfaces changed 9% to 28% of repeated decisions, making AI visibility a distribution rather than a stable rank.

Cross-sectional overlap audit identifies differences but cannot explain causality, stability or downstream user response.

Strong multi-surface, repeated-query audit directly relevant to measurement strategy.

LLM-derived latent user demands used to generate and evaluate optimized content

Demand-guided optimization produced large reported visibility gains, but models generated much of both the demand signal and the evaluation.

Direct content-demand hypothesis with circularity risk from LLM-generated inputs and judges.

Direct content-demand hypothesis with circularity risk from LLM-generated inputs and judges.

350 strategic enterprise procurement participants

AI use was more common in discovery and evaluation than in final decision-making; public summaries report different rates by stage.

Vendor white paper and procurement-heavy population; exact question bases require full report extraction.

Already admitted to the evidence register

100 B2B SaaS leaders in a message-testing panel

42 mentioned LLMs during first-stage research, but only 11 used one as the absolute first step; vendor sites, reviews and peers remained important validation sources.

Small qualitative/quantified panel; useful for process texture, not prevalence estimation.

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Analytics classification rules rather than outcome research

Human AI-referral visits, zero-click influence and bot/agent traffic are separate classes. Its AI Assistant channel is not retroactive; historical visits remain in their original Referral/Direct classifications; server logs are required for bots that do not execute JavaScript

Measurement guidance, not evidence of market size or commercial impact. Useful for the instrumentation chapter only.

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More than 2M AI conversations and associated browsing; double-opt-in US panel; ChatGPT, Gemini and Google AI Overviews; January-June 2026. Exposure: brand introduced in the answer, not prompt. Outcome: own-site visit within seven days

Treated versus forecast visit rates: Gemini 5.42% vs 2.21%, +3.21pp; AIO 7.79% vs 4.83%, +2.96pp; ChatGPT 6.39% vs 4.33%, +2.07pp. Software lift: +4.0pp AIO, +3.0pp ChatGPT, +3.6pp Gemini. Only about 1-2.5% of ChatGPT downstream visits carried a matched AI-referral parameter; more than 97% did not. 42% of visits occurred within 24 hours

Observational, not randomised; page visit, not conversion; users/exposures/brands per cell and panel provider not disclosed. Commercial vendor interest. Independence from the Similarweb and Scrunch joined panels is not yet verified.

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Two undisclosed English-speaking markets; ChatGPT, Claude and Gemini; early 2026; consumer-brand lexicon. Aggregate panel size and cell sizes withheld. Outcome window: seven days

For recommendations to people with no recent observed brand engagement, branded Google search rose from 2.9% to 7.2%, +4.3pp; own-site visits 3.1% to 5.5%, +2.4pp; retailer-page visits 0.8% to 1.8%, +1.0pp. Neutral name-drops produced only +1.8/+1.1/+0.3pp. Unnamed same-category brands in the same response were near flat

Preprint, not peer reviewed; consumer brands; no transactions; a brand-specific within-session intent shock remains unidentified. Panel sizes/markets withheld. Stronger controls than vendor blog studies, but independence from D1/D3 must be confirmed.

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“Thousands” of real journeys in Finance, Travel and Beauty; public description indicates US desktop, six months, seven-day follow-up; excludes prior brand visits and prompts naming the brand

Users shown a ChatGPT-recommended brand were 2.5 times more likely to visit it than users shown a competitor recommendation; 55.9% of AI-influenced visits arrived through search; influenced visitors viewed about twice the pages and spent about twice the time

Exact exposed/control bases, CIs, date range and matching details are not in the public blog. Observational and no purchase/revenue outcome. The 2.5x headline resembles D1 but the estimand differs; do not call it an independent replication until panel lineage is confirmed.

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Tally onboarding surveys and internal growth reporting

Tally reported AI tools as its largest acquisition source by April 2026 via onboarding survey.

Methods, absolute counts and attribution wording are incomplete; company-specific and highly selected. Useful as existence proofs only, not benchmarks or causal evidence.

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Vercel internal acquisition analytics

Vercel reported ChatGPT referred about 10% of new signups in June 2025, up from 4.8% one month earlier and 1% six months earlier.

Methods, absolute counts and attribution wording are incomplete; company-specific and highly selected. Useful as existence proofs only, not benchmarks or causal evidence.

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13,747 consumer queries, ten Amazon listings each, five engines, seven rewriters and fifteen hand-written heuristics

Ten of fifteen common heuristics were neutral or harmful, while meta-optimized prompts performed better and converged on a more stable cross-domain structure.

Large direct product-visibility testbed with unusually relevant commercial tasks, though it uses fixed retrieved listings.

Large direct product-visibility testbed with unusually relevant commercial tasks, though it uses fixed retrieved listings.

More than 1T US retail visits plus a 5,000-person US survey; July 2024-February 2025.

AI referral traffic rose 1,200% from July 2024; conversion remained 9% below non-AI sources in February 2025, improving from a 43% gap.

same Adobe rolling family, not an independent confirmation.

Essential baseline showing conversion changed sign over time; same Adobe rolling family, not an independent confirmation.

Shopify Q1 2026 commerce data; AI-referred versus organic-search product-detail-page sessions across 25 merchant categories; January 2025-March 2026 growth window.

AI-referred PDP sessions converted nearly 50% better, had 14% higher AOV and outperformed organic in 23 of 25 categories.

merchant/session counts, absolute rates and selection method are not disclosed.

Large-platform commerce evidence with category consistency; merchant/session counts, absolute rates and selection method are not disclosed.

Reproducible full pipeline over a large web corpus retaining structural page information

Techniques that help downstream generation often degrade retrieval or reranking, while structural information partly mitigates the trade-off, demonstrating that citation optimization can reduce discoverability.

Runs in a reproducible non-commercial pipeline whose retriever, corpus and generator may not represent proprietary answer engines.

One of the strongest stage-separated end-to-end GEO studies, albeit in a non-commercial pipeline.

792 respondents; five questions fielded November 2025

Reports buyer-rated usefulness of AI in technology research and related evaluation behaviour.

Recruitment, geography, weighting and several denominator details are limited; directional only until full extraction.

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645 B2B buyers; 2026 newsroom summary

45% used generative AI in a recent purchase, while 69% preferred to validate AI-generated insights with a sales representative.

Public newsroom summary omits full questionnaire and sampling detail. Supports AI-plus-human validation, not AI causality.

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1,862 verified technology buyers plus 444 technology vendors; global network; online survey in January 2026 about a purchase in the prior year

63% of buyers used AI during a technology purchase; 94% of AI-using buyers fact-checked the output at least sometimes.

Self-reported behaviour from a review-platform network. Useful for verification behaviour, not causal pipeline impact.

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Random sample of 10,000 prompts over 14 days in late March-mid April 2026 across ChatGPT, Perplexity and Copilot; captured internal search queries.

91% of ChatGPT fan-out queries were unique across runs versus 14% for Perplexity; original-prompt word overlap was 13% for ChatGPT versus 88% for Perplexity.

models and platform implementation can change quickly.

Strong cross-engine retrieval evidence; models and platform implementation can change quickly.

24,000 queries in 243 countries producing 2.8 million AI and traditional search results across 2024 and 2025

AI-search exposure expanded sharply across countries and topics while surfacing fewer long-tail sources, less response variety and more low-credibility sources than traditional search.

Global query-result audits measure exposure and concentration, not whether users noticed, trusted, clicked or purchased.

Large global longitudinal audit connecting rollout policy to source concentration.

Cross-system comparison using Natural Questions-derived tasks and atomic content-unit coverage metrics

Generative and traditional search can provide similar topical coverage while exposing users to different and narrower combinations of sources and source content.

Adds coverage and exposure metrics beyond simple citation counts; dataset age limits current-market inference.

Adds coverage and exposure metrics beyond simple citation counts; dataset age limits current-market inference.

Similarweb desktop panel; ChatGPT referrals April 30-May 20, 2026 around a May 7 homepage-link interface change.

Week-on-week referrals rose 157.7% and homepage referrals 354.7%; homepage share moved to roughly 60%.

short uncontrolled window.

Strong demonstration that product UI can change measurable referrals without equivalent demand change; short uncontrolled window.

Controlled synthetic and real tasks across 12 LLMs from six providers

Several models had strong predictable source preferences that could outweigh content, changed with framing and persisted despite instructions to avoid bias.

Controlled source cues, including synthetic tasks, do not show live-web retrieval, stable production behavior or buyer outcomes.

Broad controlled confirmation that source identity itself can steer what agents present.

Adversarial experiments on LLM-based text-ranking tasks

LLM rankers contain a decision-making blind spot that lets optimized text hijack ranking outcomes without equivalent merit gains.

Mechanistically relevant to answer-engine reranking but not a production web audit.

Mechanistically relevant to answer-engine reranking but not a production web audit.

55,393 trending queries across 19 categories over 40 days; 98,020 atomic claims

AIO activation averaged 13.7% but 64.7% for question queries; nearly 30% of cited domains were absent from co-displayed results and 11% of claims lacked support from cited pages.

Forty-day trending-query window may overrepresent newsworthy demand, and the audit does not observe user clicks or commercial outcomes.

Large longitudinal audit covering activation, distinct source selection and citation fidelity.

3.25B citations across seven models, 14 countries and native-language prompts in March 2026; source types classified.

Social citation rates varied materially by engine and language; AI Overviews used social sources at 15.3% versus Gemini 3.6% overall.

customer prompt demand may not represent populations.

Large current evidence that English-only/global tracking is unsafe; customer prompt demand may not represent populations.

600 volunteers, 12 product categories, three AI tools and 2,961 completed prompt runs.

Brand recommendations varied substantially across repeated identical prompts and platforms.

Rare human-run repeated-measures evidence that one-shot visibility scores are unstable; convenience volunteers and limited categories remain.

Rare human-run repeated-measures evidence that one-shot visibility scores are unstable; convenience volunteers and limited categories remain. JY source 27.

Twin-Branch protocol across three engines using reusable strategy memory.

Reusable agent strategies improved visibility while attempting to preserve attribution fidelity.

Multi-engine optimization evidence; frozen evaluation contexts and automated metrics limit live-market inference.

Multi-engine optimization evidence; frozen evaluation contexts and automated metrics limit live-market inference. Martinez matrix row 24.

7,060 queries with at least three sources, 2,275 tokenized pages and 883,262 observed snippets from multiple client verticals.

Median grounding budget was about 1,929 words per query; rank-one sources received a median 531 words versus 266 for rank five, and long pages had lower coverage.

Detailed primary page and discussion clarify measurement; private client query selection, no confounder controls and no public data limit causal conclusions.

Detailed primary page and discussion clarify measurement; private client query selection, no confounder controls and no public data limit causal conclusions. JY source 32.

Multi-query optimization using instruction fusion and downside-risk estimation.

Optimizing across prompt sets can improve average visibility while controlling losses on conflicting queries.

Supports portfolio-level prompt measurement rather than single-prompt optimization.

Supports portfolio-level prompt measurement rather than single-prompt optimization. Martinez matrix row 23.

Fourteen baselines across GEO-Bench, MS MARCO and an Amazon-derived dataset on two open-weight engines.

Agentic optimization improved multi-objective visibility-quality frontiers over static baselines.

Broad benchmark evidence but open-model laboratory results may not transfer to commercial engines.

Broad benchmark evidence but open-model laboratory results may not transfer to commercial engines. Martinez matrix row 20; Cyrus overlap.

AutoGEO preference-learning system with five fixed documents, one optimized target and multiple generators.

Reported mean visibility gains of 35.99% in fixed-context tests while balancing utility constraints.

Rigorous optimization evidence, but fixed retrieved sets are not the open web.

Rigorous optimization evidence, but fixed retrieved sets are not the open web. Martinez matrix row 12; overlap with Cyrus Shepard sheet.

AgentGEO evaluated on MIMIQ documents and HTML pages with diagnosis and constrained edits.

Reported more than 40% relative citation gain while modifying about 5% of text, though reported counts require reconciliation.

Promising constrained-edit evidence; counting inconsistencies prevent high-confidence use.

Promising constrained-edit evidence; counting inconsistencies prevent high-confidence use. Martinez matrix row 19; Cyrus overlap.

Copilot audit on the 2024 Taiwan election: 200 prompt-level cases and 1,501 linked-statement cases in five languages

Nearly half of sampled answers contained factual errors, only about 63% of referenced content was both factually correct and accurately sourced, and performance varied sharply by language.

Single Copilot election snapshot in a political domain limits transfer to commercial recommendations and current models.

Detailed multilingual commercial-engine source audit with manual coding and strong intercoder reliability.

2,729 businesses, about 95 prompts each, five systems and 266,844 business-model-prompt observations enriched with web and platform signals

Off-page associations varied by engine rather than supporting one universal authority recipe, with signals such as reviews, directories and social presence showing model-specific effects.

Large directly commercial cross-platform audit, retained with independence and observational-confounding caveats.

Large directly commercial cross-platform audit, retained with independence and observational-confounding caveats.

More than 30B sessions from the 2,000 Clarity projects receiving the most LLM traffic; October 2025-March 2026; quick backs, duration, pages, scroll and rage clicks.

AI-referred traffic grew 22% and showed fewer early abandonment signals and deeper session intent than traditional channels, while using fewer pages.

deliberately selects top AI-traffic projects and does not measure pipeline.

Massive session base and explicit behavioral metrics; deliberately selects top AI-traffic projects and does not measure pipeline.

Ahrefs Web Analytics rolling sample of 81,947 sites; May-June 2025; AI referrals compared with search and all traffic.

AI visitors averaged 4.0 pages versus 5.2 for search and had higher bounce, contradicting a universal engagement premium.

same exact dataset as IND-008 and cannot count as independent.

Important negative finding from a large panel; same exact dataset as IND-008 and cannot count as independent.

More than 1T US retail visits and 100M SKUs; industry data October 2024-December 2025; survey of 1,000+ consumers in November 2025

2025 holiday AI retail traffic converted 31% better than non-AI and produced 32% more revenue per visit. Technology/software had the highest AI-driven visit share, +120% YoY, and AI visits showed +35% engagement, 43% lower bounce, +46% time and +22% pages

Tech/software outcome is engagement, not SaaS purchase or pipeline. Consumer and last-click. Overlaps O1 as an earlier wave; do not count the two Adobe percentages as independent studies.

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81,947 sites; May-June 2025; AI referrals versus search and all traffic

AI visitors averaged 4.0 pages versus 5.2 for search; 86 seconds versus 78; and 67.8% bounce versus 63.7% for search and 62.4% overall

Cross-site means conceal mix and landing-page differences; conversion not measured. Directly contradicts a universal “AI visitors are higher quality” claim. Same dataset as T3.

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Ahrefs.com; 30 days ending 16 June 2025

AI referrals were 0.5% of visits but generated 12.1% of signups, a reported 23-times higher signup-per-visit ratio than traditional organic search

One brand, no absolute counts, signup rather than paid revenue, likely high prior brand/product awareness and power-user selection. Do not generalise 23x.

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Ecommerce sites; June 2025

AI-referral visits reportedly converted at 11.4%, versus 9.3% paid search and 5.3% organic search

Public article gives insufficient sampling, site, geography and model detail. Referral only and likely part of Similarweb's State of Ecommerce/rolling panel.

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1.9M AI Overview citations matched to Google organic search positions in Ahrefs data.

76% of AI Overview citations came from pages in Google's top ten for the associated search.

AIO-specific and does not show causality or ChatGPT behavior.

Large direct overlap measure supports SEO as a foundation; AIO-specific and does not show causality or ChatGPT behavior.

URL-level Comscore US desktop clickstream comparing ChatGPT and Google, with access expansions used for causal estimation

Only 5.2% of ChatGPT conversation sessions produced an outbound click, and wider ChatGPT Search access reduced traditional search use by 9.4%, with largest referral losses in informational categories.

US desktop clickstream and staggered access shocks may not transfer to mobile, later product versions or B2B revenue journeys.

Rare clickstream and quasi-experimental evidence directly measuring the referral gap.

Privacy-preserving automated classification of a representative sample of consumer ChatGPT conversations through July 2025; product growth tracked from launch; Harvard IRB approval.

Practical Guidance, Seeking Information and Writing comprised nearly 80% of conversations; decision support was a major economic-use mechanism.

consumer ChatGPT messages do not identify brand visibility or buying outcomes.

Unusually strong first-party platform-use evidence and downloadable methodology; consumer ChatGPT messages do not identify brand visibility or buying outcomes.

Controlled ranking attacks plus Perplexity validation using explicitly supplied URLs

Injected ranking instructions can influence conversational search ordering and transferred to Perplexity when target URLs were directly provided.

Shows a real attack surface but does not demonstrate organic crawling or retrieval.

Shows a real attack surface but does not demonstrate organic crawling or retrieval.

Controlled experiments on fictitious product catalogs with strategic text sequences

Strategic additions to product text can move items upward in LLM-generated recommendations, but the result was produced in a synthetic catalog rather than a live search product.

Directly relevant product-visibility mechanism with limited external validity.

Directly relevant product-visibility mechanism with limited external validity.

Product-description interventions based on cognitive-bias cues across LLMs of several sizes

Social-proof language consistently increased recommendation rate and rank, whereas scarcity and exclusivity cues often reduced visibility, showing that familiar persuasion tactics transfer unpredictably.

Prompted product descriptions and model outputs do not establish organic web retrieval, durable visibility or actual purchases.

Direct controlled product-visibility evidence with clear implications for content experiments.

ProductBench with 15 categories and 200 products each; top-ten Amazon lists; four search-capable LLMs

CORE reported promotion success of 91.4% at top five and 80.3% at top one, but each model received fixed top-ten product lists and some review-based variants may introduce fabricated content.

Large direct product-ranking experiment with unusually high effects that require fixed-context and integrity caveats.

Large direct product-ranking experiment with unusually high effects that require fixed-context and integrity caveats.

Worldwide Cloudflare-served HTML requests; January-July 2025

July crawl requests per attributed referral: Anthropic 38,065.7:1, OpenAI 1,091.4:1, Perplexity 194.8:1, Microsoft 40.7:1, Google 5.4:1

Requests are not people, sessions, use or value. Ratios are unstable when referrals are sparse and bot identity is imperfect. Supply-side publisher economics must never be presented as buyer-influence evidence.

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1,277 publisher/news domains in Microsoft Clarity; eight months of traffic growth and one month of Smart Events conversion analysis.

AI referrals were below 1% of traffic but grew 155.6%; sign-up CTR was 1.66% versus search 0.15%, and 52% of domains recorded an AI conversion.

publisher-heavy selection and automatic Smart Events differ from SaaS pipeline.

Large cross-domain first-party conversion study; publisher-heavy selection and automatic Smart Events differ from SaaS pipeline.

Difference-in-differences across 161,382 matched Wikipedia article-language pairs using staggered AIO rollout

AIO exposure reduced daily English Wikipedia article traffic by about 15%, with larger relative declines in culture than STEM content.

Wikipedia is a distinctive publisher and the staggered language comparison depends on parallel-trends assumptions; results are not a universal site effect.

Strong quasi-experimental downstream traffic evidence with a transparent comparison design.

1,323 fan-out queries from 540 parent prompts across ChatGPT, Gemini and Perplexity, ten verticals and five intents

Intent and platform predicted fan-out type more than vertical; discovery prompts triggered 3.3 times more entity injection than informational prompts, while exact query strings were highly stochastic.

Directly measures the hidden retrieval queries that determine discoverability, with limited per-vertical power and independent provenance.

Directly measures the hidden retrieval queries that determine discoverability, with limited per-vertical power and independent provenance.

Laboratory purchase experiment assigning traditional search, GPT, Gemini or a steering GPT, plus large API audits

Conversational recommenders increased consumer spending, with the steering GPT highest; the effect reflected linguistic framing and premium-brand exposure rather than perceived quality or generalized trust.

Laboratory purchases and an intentionally steering model may overstate effects relative to natural, high-stakes B2B evaluation.

Rare controlled downstream purchasing evidence that connects model recommendations to transaction value.

56 participants completed 221 real shopping tasks in ChatGPT; behavior/transcripts coded and matched to Profound share-of-voice data.

Chosen brands had 24% answer share versus 11% for passed-over brands; choice correlation was 0.57 and 92.8% of tasks ended without an open-web click.

small consumer sample, task prompting and correlation prevent broad causality.

Rare direct observed link between AI visibility and choice; small consumer sample, task prompting and correlation prevent broad causality.

48 months of referral traffic for 8,082 news domains across five AI platforms and organic search, linked to bot-blocking records

AI referrals were more concentrated than organic search; blocking Perplexity's crawler reduced the blocking domain's referral traffic by 46-48% and redistributed traffic mainly to already large accessible outlets.

News-domain referral markets and crawler blocking are not B2B discovery; blocking decisions may also correlate with unobserved publisher strategy.

Rare multi-year referral and crawler-access evidence with direct publisher-market implications.

Adobe US retail and travel analytics; July 2024-May 2025; proprietary customer transaction base.

By May 2025 AI retail conversion was 22% below non-AI, while consumer-electronics AI traffic share was 4x apparel and home goods 3x apparel.

overlaps its rolling dataset and remains non-B2B.

Strongest Adobe wave for the considered-purchase mechanism; overlaps its rolling dataset and remains non-B2B.

More than 1T US retail visits; October 2024-December 2025; companion survey of 1,000+ US consumers.

Holiday 2025 AI referrals converted 31% better than non-AI traffic; technology/software had the highest AI-driven visit share, up 120% year over year.

overlaps the Adobe rolling panel and is not an independent replication.

Material earlier wave and cross-industry cut; overlaps the Adobe rolling panel and is not an independent replication.

More than 510,000 travel-platform users randomized between DeepSeek-R1 and DeepSeek-V3 assistants

The reasoning assistant reduced hotel bookings by 2.5%, alongside fewer searches, hotel views and clicks, while increasing later chat engagement.

One travel platform and two DeepSeek assistants make the direction and magnitude highly context-specific; hotel bookings are not B2B pipeline.

Large randomized commercial field test showing that better AI assistance can narrow search and reduce platform purchases.

Detailed 2022-2023 clickstream following individual LLM adoption

Traditional search eventually fell more than 20% below adopters' pre-use level; small websites, education sites, Stack Overflow and display-ad exposure declined while frequently visited sites were less affected.

Strong individual-level adoption design with downstream site effects, though it reflects an early ChatGPT period.

Strong individual-level adoption design with downstream site effects, though it reflects an early ChatGPT period.

Nationally representative Comscore panel data from 2019-2024 plus a session-level field experiment

LLM use was usually complementary to web exploration rather than LLM-only, and adopters visited more unique sites, complicating the simple zero-click displacement narrative.

Most behavioral data end in 2024 and capture early standalone-LLM adoption, before newer integrated AI-search interfaces.

Large behavioral panel plus field evidence that tests substitution and concentration directly.

3,311 short-tail keywords across four intents run through ChatGPT, Perplexity and Google's top 100, building on long-tail/fan-out experiments.

Citation overlap with Google remained low even when AI systems retrieved from search indexes, implying an additional selection layer.

one keyword sample and changing retrieval stack limit durability.

Well-defined cross-platform/query design; one keyword sample and changing retrieval stack limit durability.

1,076 global B2B software decision-makers and influencers surveyed March 2026

51% started software research with an AI chatbot more often than Google; 71% used chatbots in the process; 54% cited AI as a shortlist influence. On vendor selection: 33% chose a previously unconsidered vendor and 36% chose a familiar but different vendor.

Self-report and survey recruitment details constrain causal interpretation. The 69% combines two response categories and means a different vendor than initially planned, not AI-caused revenue.

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643 US B2B professionals surveyed Mar-Apr 2026; 21 quality failures removed; 622 valid; subsequent published results use 519 respondents who use AI at work

Among the 519 AI-at-work users: 66% regularly used AI for vendor research, 92% said it influenced the shortlist, 83% said it influenced the final decision, and 32% said the influence was major.

Question wording, response scale and raw numerators are not public. Published percentages condition on AI users; approximately 69% of all 622 is a rounded reconstruction, not a directly reported result.

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Main study: 3,744 B2B buyers across North America, Europe, APAC and UK/Ireland; purchases at least $25k. Companion: 766 respondents. Software median purchase roughly $200k-$300k.

94% used LLMs somewhere in the journey. Buyers considered 5.1 vendors and had 3.6 on the Day One shortlist; 95% bought from that shortlist, and the preferred pre-contact vendor ultimately won 77% of the time.

Does not observe AI visibility experimentally. Strong buying-mechanism bridge, not proof that an AI mention caused shortlist or revenue.

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100 claims across five misinformation-prone topics tested on GPT-4o, GPT-5, Perplexity and Qwen Chat

Perplexity used the most credible sources in this restricted test, while GPT-4o cited more non-credible sources on sensitive topics and groundedness varied separately from credibility.

Direct modern commercial-assistant audit, although restricted topics limit generalization.

Direct modern commercial-assistant audit, although restricted topics limit generalization.

AllSides-2024 with 1,340 queries, 2,680 paired passages and 169 media outlets; controlled source-name swaps

LLMs cited left-labelled outlets more than traditional retrievers, and swapping publisher names nearly reversed the bias, showing source identity can outweigh matched content.

Political passage pairs isolate source-name effects but do not test commercial recommendations, live retrieval or buyers.

Strong controlled evidence that publisher brand itself can drive citation selection.

Controlled ConflictingQA contexts testing evidence attributes and position across language models

Topical relevance and context position dominated many stylistic cues in determining which conflicting evidence a model adopted.

Uses controlled conflicting evidence already placed in context; it does not test organic retrieval, live answer engines or user behavior.

Strong mechanism evidence for why relevance and placement matter once content is retrieved.

Retrieved web contexts, LLM-generated article-centric queries and predominantly automated evaluation

The benchmark measures how source content shapes generated answers, but heavy use of generated queries and automated judges leaves open whether gains reflect real user demand or human-perceived quality.

Direct source-influence benchmark, useful with explicit judge and query-generation caveats.

Direct source-influence benchmark, useful with explicit judge and query-generation caveats.

712 real-world queries across politics, health and environment on ChatGPT, Copilot, Gemini and Perplexity; 19,154 retrieved classified textual pages

Roughly 16% of classified cited pages showed evidence of AI generation across all four engines, while source use combined a narrow repeatedly cited core with a long tail.

Direct cross-engine source-quality audit; detector error and inaccessible URLs require sensitivity treatment.

Direct cross-engine source-quality audit; detector error and inaccessible URLs require sensitivity treatment.

81,947 sites; May-June 2025; referrers from ChatGPT, Perplexity, Copilot and Gemini

Average AI traffic was 0.25% of site traffic; the three largest assistants were about 0.19%; Google sent about 210 times as much traffic as those three; ChatGPT supplied more than 80% of AI traffic

Voluntary Ahrefs analytics customers, site-level average unclear, no B2B weighting. The earlier 3,000- and 35,000-site articles are earlier waves of this same rolling dataset, not independent replications.

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1,215 US enterprise-customer domains; 3.3B sessions, including 35.7M LLM/chatbot sessions; May-September 2025

AI referrals were 1.08% of all sessions. Information Technology averaged 2.80%; software and services 3.37%; semiconductors 4.09%; hardware 0.99%. ChatGPT supplied 87.4% of AI referrals overall and 88.5% in IT

Enterprise-customer selection, older 2025 observation window, and referral-only measurement. The report also contains a separate synthetic-prompt/citation dataset; do not merge its denominator with traffic sessions.

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973 ecommerce websites, 24 categories and all continents; 10.51B sessions, 164.9M transactions and $20.6B revenue over 28 July 2024-2 August 2025; main model uses six months ending 2 August 2025

ChatGPT referrals were under 0.2% of traffic, about 200 times smaller than organic Google. The 12-month data contained 4.92M ChatGPT-referral sessions and 50,251 transactions

Ecommerce and last-click only; selection into Grips customer data; the first author worked for Grips. Still the strongest directly observed cross-site transaction dataset. Independent of the vendor panels above as far as public disclosures show.

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Worldwide top 1,000 sites; June 2025

AI platforms generated an estimated 1.13B referral visits, +357% YoY, versus 191B referrals from Google search; ChatGPT supplied more than 80% of AI referrals

Concentrated in the world's largest sites, so unsuitable as a typical-site share. Same rolling Similarweb referral family as the 2025 Generative AI Report and related “top sites” articles.

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300,000 keywords: 150,000 with an AI Overview in December 2025 and 150,000 informational controls without one; aggregated desktop GSC CTR; December 2023 versus December 2025

Position-one CTR fell from 0.073 to 0.016 for the later-AIO cohort. After applying the control trend, observed CTR was about 58% below the forecast no-AIO CTR. Estimated impact declined from -58% at position one to -19.4% at position ten

Matched observational cohorts, not randomised; geography/language not clearly disclosed; post-period AIO status defines the cohort. The earlier 34.5% article is the first wave of this same study, not a replication.

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900 consenting US adults; browser activity on personal desktop, laptop and mobile; 2,457,176 page visits during March 2025

AI summaries appeared on 18% of Google searches. Users clicked a traditional result on 8% of visits with an AI summary versus 15% without one; only 1% clicked a link inside the summary; 26% ended the session versus 16% without a summary

Observational: AI summaries appear on systematically different queries, especially longer ones. The 8/15 comparison is per Google-result page visit, not a keyword-position CTR. Independent primary panel.

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Nearly 69M US desktop Google sessions; 1 May-5 July 2025

AI Mode rose from 0.25% to just over 1% of Google sessions. Only 6-8% of AI Mode sessions reached an external domain, implying 92-94% zero-click

Early-adopter/post-launch period, desktop only and session definitions may differ from normal Google search. Same Semrush/Datos clickstream family.

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US Google searches; desktop plus mobile browser, excluding the Google mobile app; January-April 2026

68.01% of Google searches ended without any click, versus 60.45% in the authors' 2024 analysis; AI Mode itself represented only 0.34% of searches

Similarweb panel; mobile session endings use a ten-second inactivity rule and mobile paid-click share is modelled. Zero-click predates generative AI, so the 7.56-point increase cannot be assigned causally to AI. Not independent of Similarweb.

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Approximately 700,000 keywords across ten sites and five industries, comparing AIO and non-AIO click behavior.

Average organic click-through fell 15.49% in the sample, while branded queries rose 18.68%, revealing strong query-type heterogeneity.

Useful counterexample to a universal click-loss claim; small site cohort and observational design limit causal inference.

Useful counterexample to a universal click-loss claim; small site cohort and observational design limit causal inference. JY source 16.

Twelve months of AI Overview presence and size plus citation overlap across nine verticals using BrightEdge Generative Parser.

AI Overview presence and real-estate expanded while citation overlap with organic top ten remained low and highly vertical-specific.

Useful longitudinal and B2B-tech cut; proprietary tracked keyword composition is not published.

Useful longitudinal and B2B-tech cut; proprietary tracked keyword composition is not published. JY source 28.

More than 40,000 large US websites using Similarweb estimates, validated against Google Search Console with median correlation of 0.86.

Estimated SEO traffic declined 2.5% year over year overall while Google traffic rose 0.8%, with losses concentrated outside the very largest sites.

Large denominator and validation make this useful market context; proprietary panel and site-selection bias remain. JY retained study 1; overlaps existing project traffic register.

Large denominator and validation make this useful market context; proprietary panel and site-selection bias remain. JY retained study 1; overlaps existing project traffic register.

Server logs from one site with an internal control and interrupted time-series analysis.

Reported a 1.82-times referral ratio after intervention, but the placebo test was not conventionally significant at p=.16.

Rare quasi-experimental traffic evidence; single-site design and weak placebo result require low-confidence interpretation.

Rare quasi-experimental traffic evidence; single-site design and weak placebo result require low-confidence interpretation. Martinez matrix row 39.

1,963,544 identifiable LLM-referred sessions across 12 months and sites in SaaS, e-commerce, finance, legal, health and publishing.

AI referrals were 0.13% of sessions overall but disproportionately reached industry, tool and pricing pages; SaaS had 16.4% of AI traffic landing on pricing pages.

One of the strongest B2B-adjacent traffic-intent datasets; identifiable referrals miss zero-click influence and site selection is undisclosed.

One of the strongest B2B-adjacent traffic-intent datasets; identifiable referrals miss zero-click influence and site selection is undisclosed. JY source 24.

Chartbeat traffic data covering more than 2,500 publisher sites plus industry survey material.

Google organic traffic to the covered publisher cohort fell about 33% from November 2024 to November 2025.

Large publisher-specific outcome; do not generalize to all websites or B2B SaaS.

Large publisher-specific outcome; do not generalize to all websites or B2B SaaS. JY source 11.

Rolling client panel; current public edition reports 53 brands, 5.47 million tracked queries and 2.43 billion impressions.

Organic CTR fell materially on queries showing AI Overviews, with large differences by brand and query type.

Large first-party panel, but changing cohort means the current page differs from JY's earlier 42-organization, 25.1M-impression snapshot. Treat as rolling lineage, not two studies.

Large first-party panel, but changing cohort means the current page differs from JY's earlier 42-organization, 25.1M-impression snapshot. Treat as rolling lineage, not two studies.

Google Search Console data from a 64-site core panel; content classification on the top 15 national and local news brands.

Organic search traffic was 42% below the pre-AIO baseline while breaking-news traffic grew 103%, driven mainly by Google Discover.

High-volume first-party publisher evidence with a disclosed method; publisher and content-mix effects do not transfer directly to B2B SaaS.

High-volume first-party publisher evidence with a disclosed method; publisher and content-mix effects do not transfer directly to B2B SaaS. JY source 31.

About 12,000 queries across seven countries yielding about 80,000 results, plus a preregistered randomized US-representative experiment

Links and citations increased trust even when wrong or hallucinated, and higher trust predicted more clicking and less time evaluating the answer.

Controlled trust tasks establish interface causality, not sustained real-world buying behavior or pipeline impact.

Causal interface evidence showing why citation visibility can influence behavior without corresponding factual quality.

Three-person pilot, 21-person main qualitative study, plus automated audit of You.com, Perplexity and Bing Chat

Participants encountered 16 recurring answer-engine limitations, including hallucinated or misleading citations, and the automated audit reproduced many of those problems.

Small qualitative sample and early-generation products limit prevalence claims and current-platform transfer.

Rare human-centered evidence on how source-cited answers are actually interpreted and verified.

Online experiment assigning ChatGPT or Google for smartphone and holiday-choice tasks, plus qualitative interviews

ChatGPT users found the optimal option more often and faster while consulting significantly fewer external sites, consistent with AI functioning as a one-stop decision intermediary.

Short consumer-choice tasks under randomized tool assignment do not reproduce long-cycle, multi-person B2B buying.

Direct randomized comparison on complex consumer decisions with strong mechanism relevance.

75,000 selected brands with domain rating above 40 and a high-volume keyword; millions of AI responses across ChatGPT, AI Mode and AIO

YouTube mentions correlated about 0.737 with AI visibility; branded web mentions about 0.66-0.71; page volume only about 0.194. Output overlap across platforms was about 0.779

Highly selected established brands; correlational; common prompt pools and Google-owned YouTube may inflate relationships; no causal result.

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