Answer Capsule
Revenue Experts AI is a qualified but conditional fit for publishers and review websites seeking a one-time AI citation audit. Two of seven platforms named it during ranking discovery (deepseek and kimi), both at rank 2, giving it a 28.6% share of included platform responses and an average listed rank of 2.0. The strongest reason to consider it is its citation-validation method: it opens every cited page and checks whether the page actually supports the AI-generated claim, rather than counting mentions [1]. The main limitation is that the provider positions its methodology around B2B SaaS buyer behavior and states it has not been validated for non-B2B contexts, including publisher and review-site models [3].
Research Snapshot
| Field | Finding |
|---|---|
| Platform mentions in ranking stage | 2 of 7 platforms (deepseek, kimi) |
| Share of included platform responses | 28.6% (2/7) |
| Average listed rank | 2.0 |
| Best listed rank | 2 |
| Relevant product/model/plan | AI Citation Audit, including the Readiness Audit component |
| Overall use-case fit | Mixed to good: strong citation-verification method, unresolved publisher-specific fit and pricing conflicts |
| Research date | 2026-09-18 |
Why Revenue Experts AI Qualified for This Study
Questions This Section Answers
- Is Revenue Experts AI a good choice for AI Search Audits for Publishers and Review Websites?
- Why did only two of seven AI platforms name Revenue Experts AI for publisher AI search audits?
Revenue Experts AI qualified because it markets a named AI Citation Audit that maps directly onto the study's evaluation criteria: recommendation analysis, mention and citation measurement, competitor benchmarking, source-domain analysis, content and authority gaps, and a prioritized improvement roadmap [5]. It cleared the study's minimum-mention threshold with two platform mentions, from deepseek and kimi, both at rank 2 [7].
Qualification is not the same as consensus. Five of seven platforms did not name Revenue Experts AI during ranking discovery, and the platforms that did name it disagreed sharply on fit. Grok rated it a strong fit [6]; Google and OpenAI rated it good [10]; Perplexity rated it mixed [11]; Anthropic rated it weak [13]; DeepSeek and Kimi both rated it uncertain [7]. That spread is itself the headline finding for a publisher deciding whether to buy.
The company describes itself as built to help B2B companies accelerate growth through custom AI revenue specialists [15]. That positioning is the origin of most of the fit disagreement below.
The Product, Model, Plan, or Service Most Relevant to AI Search Audits for Publishers and Review Websites
Questions This Section Answers
- Which Revenue Experts AI product should a publisher buy for an AI citation audit, and what does the $995 AI Citation Audit include?
- Is the Revenue Experts AI Readiness Audit a separate purchase or included in the AI Citation Audit?
The relevant offer is the AI Citation Audit, a one-time engagement that the current product page lists at $995 with no retainer, and which includes a Readiness Audit of one important page as a bundled component [16]. The Readiness Audit is described on the product page as normally a $29 product, run by the provider and included free (official:C1).
The audit's stated deliverables include buyer-intent prompt generation, multi-engine querying across ChatGPT, Claude, and Perplexity, citation extraction with per-platform claim binding, citation validation, competitor citation benchmarking and share-of-citations analysis, a per-platform Citation Precision score, citation stability ratings, cited-versus-non-cited page comparison, gap analysis, a prioritized AEO Improvement Plan, a target list of zero-scoring questions, and a suggested action sequence [16].
The method page describes 50 buyer-intent prompts in four categories (commercial, transactional, comparison, decision), each run three times across each engine, producing 12 runs per prompt and 600 runs per audit [17]. Every result is classified by source, authority weight, and reproducibility, and citations that reproduce across runs score higher than one-off citations [19]. After each audit, every prompt lands in one of five buckets that determine where to invest [21].
Naming is not stable across the provider's own pages. Public materials also describe an "AI Visibility Audit," an "AI Citation Report," and a "Verified Visibility Platform" [23]. It is unclear whether these are distinct products, renamings, or overlapping packages [26].
What the AI Platforms Agreed About
Questions This Section Answers
- What do AI platforms agree Revenue Experts AI does well for publisher and review-site citation audits?
- Does Revenue Experts AI verify that cited pages actually support the AI claim?
Agreement was strongest on method design, not on publisher fit. Multiple platforms independently described the same core mechanics: multi-run prompt testing, citation extraction, and validation of cited pages.
The most consistently reported strength is citation validation. The provider states that it opens every cited page and checks whether the page actually backs the claim attributed to it, with human review for weak scores, and reports a platform-specific Citation Precision score rather than a blended number [27]. Google's response described this as distinguishing authentic citations from hollow mention counts [30]. Grok described manual validation of every citation by opening pages as a strength [31].
Platforms also agreed on the multi-run design. Running each prompt three times per engine is intended to separate reliable citation signals from transient noise [32]. An independent Medium analysis cited in the Google response supports the underlying premise that single-run AEO scores behave like coin flips [34].
Competitor benchmarking drew agreement as well. The audit includes competitor citation breakdowns, share-of-citations analysis, and comparisons of cited versus non-cited page cohorts [27]. The output is described as a numerical citation score, a competitor map, and a gap-to-action matrix [36].
Finally, platforms agreed the deliverable is a report and roadmap rather than a dashboard. The provider states the audit is a point-in-time measurement, not ongoing tracking, and does not trace individual buyers from an AI prompt through closed-deal or CRM outcomes [27].
Where the AI Platforms Disagreed or Were Uncertain
Questions This Section Answers
- Is Revenue Experts AI validated for publishers and review websites, or only for B2B SaaS companies?
- How much does the Revenue Experts AI Citation Audit actually cost, given conflicting public prices?
Fit ratings diverged more than any other dimension. Grok called it a strong fit and said the methodology applies to publishers despite B2B SaaS marketing [37]. Google called it a good fit while noting the service is explicitly positioned for B2B SaaS and high-intent commercial buyers, which "might require extra customization" for consumer-facing review sites [38]. OpenAI called it a good fit but flagged that publisher-specific fit is not demonstrated publicly [39]. Perplexity called it mixed [40]. Anthropic called it weak, citing the company's own statement that the 50 prompts, buckets, and scoring assume B2B buyer behavior and have not been validated for D2C, e-commerce, or non-B2B contexts [42]. DeepSeek and Kimi both rated it uncertain, with Kimi reporting that its search returned no retrievable product information for the entity at all [44].
Pricing is the second major conflict. Public pages across platform responses cite $497, $995, $1,495, and $29 per page for audit-related offers [40]. The current product page lists $995 one-time [39]. One FAQ mentions a partner platform subscription starting at $300 per month but does not clearly tie it to the audit product [49]. Google's response also references planned tracker pricing of $79 per month for Pro and $299 per month for Enterprise, plus a $5 tracker trial [50].
Platform coverage is a third area of partial disagreement. The current audit page states measurement covers ChatGPT, Claude, and Perplexity [39]. One methodology page describes an earlier four-engine method that included Gemini, while the updated method excludes Gemini because Google's grounding terms restrict collecting, storing, and analyzing citation URLs [52]. Anthropic's response also cited a $1,495 AI Visibility Audit figure [48], which conflicts with the $995 current page.
Influential source-domain analysis is a fourth uncertainty. OpenAI rated it neutral, noting the public page does not clearly specify a standalone ranking of influential source domains [39]. Perplexity reached the same conclusion [41]. DeepSeek found no public evidence confirming the feature at all [44].
Use-Case-Specific Features and Capabilities
Questions This Section Answers
- Does Revenue Experts AI measure citation stability and first-citation share for publisher content?
- Can Revenue Experts AI's audit identify which competing publishers are being cited instead of my site?
For publishers and review websites, the audit's most transferable capabilities are measurement and diagnosis rather than publisher-specific workflow features.
Recommendation and mention measurement: the audit reports mention rate, citation rate, citation stability, first-citation share, cross-platform coverage, and share of citations [57]. This maps to the buyer question of whether a site is named for category queries.
Citation validation: cited pages are opened and scored against the claim attributed to them, with a per-platform Citation Precision score [57]. For review sites, this is directly relevant to source eligibility, because it tests whether a cited page substantiates what the AI said.
Competitor benchmarking: competitor citation breakdowns, share-of-citations analysis, and cited-versus-non-cited page cohort comparisons are included [57]. This can show which competing publishers or reviewers are being surfaced instead.
Content and authority gaps: the audit promises page-level feature comparison, gap analysis for missed prompts, and recommendations across Citation Readiness, Content Structure, Authority Signals, Technical Accessibility, and Semantic Clarity [57]. The Readiness Audit component evaluates one important page across five corresponding categories and flags issues such as crawler blocks or content that may not render clearly [57].
Prioritized roadmap: the deliverable includes a prioritized AEO Improvement Plan, target lists, and a suggested sequence based on competitor-occupied questions versus open territory [57]. The provider expressly states that recommended actions are hypotheses to test, not guaranteed causal solutions [57].
What is not demonstrated publicly: publisher-specific benchmarks, editorial-source taxonomies, affiliate or subscription attribution, traffic impact, news freshness handling, product-feed coverage, or audience analytics [57]. The public offer is framed around buyers, companies, and category visibility rather than publisher workflows [57].
Pricing, Fees, Contracts, and Ongoing Costs
Questions This Section Answers
- How much does the Revenue Experts AI AI Citation Audit cost, and are there setup or cancellation fees?
- What ongoing costs apply after the Revenue Experts AI audit, such as tracker subscriptions or remediation sprints?
The current product page lists a one-time price of $995 with no retainer, and describes booking as opening a scheduling page rather than a sales call [63]. The included Readiness Audit is characterized on that page as normally a $29 product (official:C1).
Public pricing conflicts across the provider's own pages. Platform responses cite $497 for an AI Visibility Audit [64], $995 for an AI Citation Report or Verified Visibility Platform [66], $1,495 for an AI Visibility Audit [68], and $29 per page for a separate audit flow [69]. Google's response notes the $995 audit is credited in full toward a subsequent Fix engagement [70]. The provider's own product page lists a component-by-component value table totaling $3,879+ against the $995 investment (official:C1).
Ongoing costs are partially documented. Google's response cites planned tracker pricing of $79 per month for Pro and $299 per month for Enterprise, plus a $5 tracker trial covering 5 prompt tests across 4 LLMs [71]. One FAQ mentions a partner platform subscription starting at $300 per month but does not clearly tie it to the audit product [73]. Anthropic's response notes optional ongoing "AI search visibility services" to address gaps once mapped, with pricing not specified [68].
Contract and cancellation terms are largely unpublished. The current page describes a one-time purchase and no retainer but does not publish refund, cancellation, rescheduling, data-retention, confidentiality, or deliverable-revision terms [63]. Google's response states one-off audit purchases do not require long-term commitments and that the $5 trial is a one-time fee, with future monthly subscription plans described as non-refundable [72]. No cancellation or contract-term information was found in Anthropic's checked sources [68].
Pricing confidence is low to moderate across platforms. OpenAI rated it moderate [63]; Anthropic, DeepSeek, Perplexity, and Kimi rated it low [68]; Grok and Google rated it high [76]. The applicable price and scope should be confirmed in writing before purchase.
Best Suited For
Questions This Section Answers
- Who gets the most value from a Revenue Experts AI AI Citation Audit?
- Is Revenue Experts AI worth it for a publisher that needs a one-time citation baseline rather than ongoing monitoring?
Revenue Experts AI is best suited to a publisher or review website that wants a one-time, evidence-oriented baseline of how it appears in ChatGPT, Claude, and Perplexity, with competitor comparison and a prioritized action list [77].
Specific fits named across platform responses:
- Teams needing competitor citation comparisons, citation-precision checks, influential source analysis, and prioritized content or authority actions [77].
- Organizations that want a report and roadmap rather than a recurring software dashboard [77].
- Publishers and review sites that need empirical proof of citation visibility rather than generic technical SEO checks [78].
- Teams that want to isolate LLM non-determinism through multi-run prompt testing [79].
- Buyers comfortable verifying scope and pricing directly before purchase [80].
- Buyers willing to contact the vendor directly for detailed specifications [82].
The provider's own stated threshold is a caution for smaller publishers: it says that if monthly recurring revenue is under $50,000, the audit is probably premature because the upstream problem is sales, not visibility [83].
Probably Not Best Suited For
Questions This Section Answers
- Who should not choose Revenue Experts AI for AI Search Audits for Publishers and Review Websites?
- Is Revenue Experts AI a poor fit for publishers that need Gemini, Google AI Overviews, or Microsoft Copilot coverage?
Several buyer profiles are repeatedly flagged as poor fits across platform responses.
Buyers requiring ongoing monitoring, automated alerts, or CRM and revenue attribution [84]. The audit is point-in-time and does not trace buyers from prompt to closed deal [84].
Publishers needing platform coverage beyond ChatGPT, Claude, and Perplexity. Gemini is excluded under the current method because Google's grounding terms restrict collecting, storing, and analyzing citation URLs [85]. Microsoft Copilot, Bing, and other AI search products are also outside the tested scope [84].
Teams seeking independent evidence of traffic, rankings, affiliate conversions, or citation improvements after implementation [84]. No independent public study was located in the checked sources validating accuracy, market impact, or customer outcomes [84]. Anthropic's response notes no case studies, customer testimonials, or measured outcomes are publicly available for any Revenue Experts AI services [88].
Buyers who require transparent, stable pricing and published contract terms before purchase [89].
Non-B2B business models. The company states the methodology has not been validated for D2C, e-commerce, or non-B2B contexts and recommends asking before buying if you are outside B2B SaaS [92].
Buyers who need a large, well-documented publisher-focused platform with extensive published case studies and certifications [91].
When Another Option May Be Better
Questions This Section Answers
- What is a better alternative to Revenue Experts AI for a publisher that needs continuous AI citation monitoring?
- Which publisher-specific AI audit tools cover AdSense compliance, schema, or Gemini coverage that Revenue Experts AI does not?
Platform responses named several alternatives with different strengths. These are platform-reported comparisons, not independently tested findings.
For continuous monitoring: Profound provides continuous monitoring of citation share across ChatGPT, Perplexity, and Google AI Overviews, and identifies top-cited publishers and authors in a category [94]. OpenAI's response also recommends a continuous AI-visibility monitoring platform when the buyer needs recurring measurements, alerts, historical trend charts, or broad engine coverage [96].
For publisher editorial authority: Make Lemonade is described as purpose-built for publisher editorial authority audits across ChatGPT, Claude, Perplexity, and Gemini, testing how often a publisher is cited across relevant queries and benchmarking against comparable titles in the sector [97].
For integrated readiness: PublisherAudit scans sites for AI-citation readiness across ChatGPT, Claude, Perplexity, and Gemini, plus AdSense compliance, Core Web Vitals, and schema [100].
For published pricing and crawl limits: TurboAudit publishes tiers from $39.99 to $549.99 per month with crawl limits of 50 to 1,000 audits per month and 20 to 100 page site-wide audits [103]. Surva.ai publishes $49 to $299 per month with 75 to 1,000 pages per audit [104]. AuditAI offers a $29 paid tier and an AI Citation Simulation with direct LLM feedback [105].
For publisher-specific technical controls: SEOVentra covers E-E-A-T scoring, AI crawler robots.txt controls, and GEO/AEO citation probability [106]. Citare checks robots.txt AI crawler status, llms.txt, FAQPage schema, and JS-rendered content across 250+ technical SEO and AI readiness checks [107].
For traffic, rankings, audience behavior, affiliate conversion, subscription, or advertising attribution, OpenAI's response recommends a publisher-focused SEO, digital analytics, or content-intelligence provider instead [96].
Questions to Verify Before Buying
Questions This Section Answers
- What should a publisher confirm with Revenue Experts AI before signing or paying for an AI Citation Audit?
- Can Revenue Experts AI localize prompts to United States markets and publisher-relevant query types?
The following verification items are drawn from platform-reported questions and disclosed uncertainties. They are not answered by the supplied evidence.
- Is the quoted price exactly $995, and which deliverables and prompt volume does that quote include [108]?
- How many prompts, repeated runs, competitors, cited pages, and source domains are included for a publisher or review website [108]?
- Can the prompt set cover non-branded category, comparison, product-review, best-of, and freshness-sensitive queries relevant to the site [108]?
- Are results localized to the United States, including language, market, device, account, and search settings where relevant [108]?
- Which platforms are tested in the purchased engagement, and are Gemini, Google AI features, Microsoft Copilot, Bing, and other target systems excluded [108]?
- How are influential source domains, editorial quality, freshness, and competing review sites classified and ranked [108]?
- Does the Readiness Audit cover only one page, and can additional pages or article templates be added for a stated fee [108]?
- What privacy, confidentiality, data-retention, and permission policies apply to prompts, URLs, analytics, and unpublished editorial material [108]?
- Are refunds, cancellations, rescheduling, revisions, support, and report walkthroughs included [108]?
- What is the price and method for a 90-day re-audit, and will the same prompts and engine settings be reused for comparability [108]?
- Can the provider supply anonymized examples or references for publishers, review sites, affiliate sites, or media organizations [108]?
- Will the 50 buyer-intent prompts be customized to reflect publisher or editorial keywords rather than B2B SaaS software purchase intent [110]?
- Is the $995 audit price fully credited if the publisher executes technical remediations in-house rather than hiring the provider for a remediation sprint [111]?
- What is the current accurate pricing for the AI Citation Audit, and what is included at each price point [112]?
- What ongoing services would be required to act on audit findings, and what are the costs [112]?
Final AI Consensus Verdict
Revenue Experts AI is a conditional fit for AI Search Audits for Publishers and Review Websites. It qualified for this study with two platform mentions out of seven, both at rank 2, and its citation-validation method is the most consistently praised element across platform responses [113].
Consensus does not extend to publisher fit. Fit ratings ranged from strong (grok) to weak (anthropic), with good (Google, OpenAI), mixed (Perplexity), and uncertain (DeepSeek, Kimi) in between [116]. The provider's own materials state the methodology assumes B2B buyer behavior and has not been validated for non-B2B contexts [117].
Pricing conflicts are unresolved across the provider's own pages, with $497, $995, $1,495, and $29-per-page figures appearing in different places [119]. Platform coverage excludes Gemini under the current method [126]. No independent validation of accuracy, market impact, or customer outcomes was located [113].
A publisher or review website should treat Revenue Experts AI as a candidate for a one-time citation baseline, contingent on written confirmation of price, scope, platform coverage, publisher-specific prompt design, data handling, and re-audit terms. Buyers needing continuous monitoring, Gemini or Google AI Overviews coverage, or independently validated outcomes should evaluate the alternatives named above. The broader AI Search Audits for Publishers and Review Websites index compares this provider against the other finalists in the same study.
How This Review Was Produced
This review was produced from platform-reported research responses collected for the study "Best AI Search Audits for Publishers and Review Websites," with an authoritative run research date of 2026-09-18. Seven platforms contributed fit-research responses: OpenAI, Anthropic, Google, Grok, Perplexity, DeepSeek, and Kimi. Each platform evaluated Revenue Experts AI against the study's criteria and supplied citations to the pages it relied on.
Ranking statistics reflect the ranking-discovery stage only. Two of seven platforms named Revenue Experts AI during that stage, both at rank 2. All seven platforms evaluated fit, but platform mentions count only platforms that named the entity during ranking discovery.
Company-owned citations materially outnumber independent citations in the supplied evidence. Of 24 deduplicated sources, 20 are company-owned and 4 are independent. Company claims are labeled as such throughout and are not described as independently verified.
Methodology Limitations
Several limitations apply to this review.
Platform-reported research dates differ from the authoritative run date. DeepSeek's response carries a research date of 2026-06-11, while the other six platforms carry 2026-09-18. Platform-reported dates are provenance metadata and do not independently prove freshness.
Citations are platform-reported evidence, not independently verified facts. The supplied URLs were collected from platform responses and were not independently validated by the writer stage. No-search model claims require explicit verification before being described as current facts.
Pricing and product naming conflicts were not resolved. Public pages conflict on whether the core audit is priced at $497, $995, $1,495, or $29 per page, and it is unclear whether the "AI Citation Audit," "AI Visibility Audit," "AI Citation Report," and "Verified Visibility Platform" are distinct products, renamings, or overlapping packages [128].
Publisher-specific fit is not demonstrated publicly. No public evidence establishes publisher-specific benchmarks, editorial-source taxonomies, affiliate or subscription attribution, traffic impact, or revenue outcomes [132].
Platform coverage is limited. The current method tests ChatGPT, Claude, and Perplexity; Gemini was removed because of citation-URL collection restrictions, and platforms not tested cannot be measured [133].
The audit is point-in-time. Repeated AI results can vary, so the baseline may require periodic remeasurement [132].
The provider acknowledges that the causal effect of individual readiness factors and recommendations is not settled and that recommendations are hypotheses to test [132].
The public page does not specify sample size, exact prompt inventory, number of competitors included, geographic personalization, language settings, or reporting treatment for news and fast-changing product categories [132].
Kimi reported that its search returned no retrievable product information for the entity, and DeepSeek's response was based on a single partially extractable vendor page [137]. Those two platforms' uncertainty reflects evidence gaps, not confirmed disagreement.
Explore more ai search audits market intelligence guidance in the category directory.
Sources
Company-Owned Sources
- AuditAI — AI Search Visibility Auditor: https://auditaiseo.com/
- About - Revenue Experts AI: https://revenueexperts.ai/about/
- AI Citation Audit - Revenue Experts AI: https://revenueexperts.ai/ai-citation-audit/
- AI Citation Report - Revenue Experts AI: https://revenueexperts.ai/ai-citation-report/
- Most AI citation tools count. Ours opens every cited page and checks whether it actually backs the claim: https://revenueexperts.ai/ai-citation-tools/
- AI Citation Tracker: https://revenueexperts.ai/ai-citation-tracker/
- AI Visibility Audit: https://revenueexperts.ai/ai-visibility-audit/
- AI Search Visibility Archives - Revenue Experts AI: https://revenueexperts.ai/category/ai-search-visibility/
- The Revenue Experts AI Citation Audit Method: https://revenueexperts.ai/the-revenue-experts-ai-citation-audit-method/
- The Verified Visibility Platform: https://revenueexperts.ai/the-verified-visibility-platform/
- The Verified Visibility Platform - Revenue Experts AI: https://revenueexperts.ai/verified-visibility-platform/
- We audited our own AI visibility. Here's the method: https://revenueexperts.ai/we-audited-our-own-ai-visibility-heres-the-method/
- What a real AI visibility audit looks like — inside the Citation Audit Method: https://revenueexperts.ai/what-a-real-ai-visibility-audit-looks-like-inside-the-citation-audit-method/
- What the conversion gap between AI-cited and AI-invisible B2B companies actually says: https://revenueexperts.ai/what-the-conversion-gap-between-ai-cited-and-ai-invisible-b2b-companies-actually-says/
- Your AI visibility problem may not be a content problem: https://revenueexperts.beehiiv.com/p/your-ai-visibility-problem-may-not-be-a-content-problem
- SEOVentra for Publishers & Media — Protect Editorial Visibility in AI Search: https://seoventra.com/solutions/publishers
- TurboAudit — AI Search Audit & Visibility Platform: https://turboaudit.ai/
- Site Audit — 250+ technical SEO + AI readiness checks: https://www.citare.ai/site-audit
- AI SEO Audit - Crawl Your Website and Fix AI Visibility Issues: https://www.surva.ai/products/ai-seo-audit
Additional AI research evidence138 records
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record anthropic:22-14
- AI research evidence record anthropic:22-16
- AI research evidence record openai:citation_1
- AI research evidence record grok:0
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record grok:1
- AI research evidence record google:1.1.4
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record anthropic:22-14
- AI research evidence record anthropic:22-16
- AI research evidence record anthropic:28-4
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:1-4
- AI research evidence record anthropic:1-11
- AI research evidence record anthropic:1-5
- AI research evidence record anthropic:1-12
- AI research evidence record anthropic:1-19
- AI research evidence record anthropic:1-20
- AI research evidence record perplexity:2
- AI research evidence record perplexity:3
- AI research evidence record perplexity:4
- AI research evidence record perplexity:1
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record anthropic:2-6
- AI research evidence record google:1.2.5
- AI research evidence record grok:0
- AI research evidence record anthropic:1-11
- AI research evidence record anthropic:1-12
- AI research evidence record google:2.2.6
- AI research evidence record perplexity:2
- AI research evidence record anthropic:1-6
- AI research evidence record grok:0
- AI research evidence record google:2.1.1
- AI research evidence record openai:citation_1
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record anthropic:22-14
- AI research evidence record anthropic:22-16
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record perplexity:4
- AI research evidence record perplexity:5
- AI research evidence record anthropic:13-1
- AI research evidence record perplexity:6
- AI research evidence record google:3.1.3
- AI research evidence record google:1.2.3
- AI research evidence record openai:citation_2
- AI research evidence record anthropic:2-13
- AI research evidence record anthropic:2-14
- AI research evidence record perplexity:3
- AI research evidence record perplexity:8
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record grok:0
- AI research evidence record perplexity:2
- AI research evidence record google:3.2.1
- AI research evidence record anthropic:1-6
- AI research evidence record openai:citation_1
- AI research evidence record perplexity:1
- AI research evidence record perplexity:7
- AI research evidence record perplexity:2
- AI research evidence record perplexity:3
- AI research evidence record anthropic:13-1
- AI research evidence record perplexity:4
- AI research evidence record google:3.1.4
- AI research evidence record google:3.1.3
- AI research evidence record google:1.2.3
- AI research evidence record perplexity:6
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record grok:1
- AI research evidence record openai:citation_1
- AI research evidence record google:1.1.4
- AI research evidence record google:2.2.6
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record kimi:search_no_data
- AI research evidence record anthropic:22-11
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-13
- AI research evidence record anthropic:2-14
- AI research evidence record openai:citation_2
- AI research evidence record anthropic:13-1
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record deepseek:c1
- AI research evidence record anthropic:22-16
- AI research evidence record anthropic:22-17
- AI research evidence record anthropic:39-10
- AI research evidence record anthropic:39-13
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:46-14
- AI research evidence record anthropic:46-15
- AI research evidence record anthropic:46-16
- AI research evidence record anthropic:15-4
- AI research evidence record anthropic:15-6
- AI research evidence record kimi:publisheraudit_site
- AI research evidence record kimi:turboaudit_pricing
- AI research evidence record kimi:surva_pricing
- AI research evidence record kimi:auditaiseo_site
- AI research evidence record kimi:seoventra_publisher
- AI research evidence record kimi:citare_site_audit
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-13
- AI research evidence record google:2.1.1
- AI research evidence record google:3.1.4
- AI research evidence record anthropic:13-1
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record google:1.2.5
- AI research evidence record grok:0
- AI research evidence record anthropic:22-14
- AI research evidence record google:1.1.4
- AI research evidence record perplexity:1
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record anthropic:22-16
- AI research evidence record perplexity:2
- AI research evidence record perplexity:4
- AI research evidence record anthropic:13-1
- AI research evidence record anthropic:2-13
- AI research evidence record openai:citation_2
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record perplexity:3
- AI research evidence record perplexity:4
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-13
- AI research evidence record anthropic:2-14
- AI research evidence record openai:citation_2
- AI research evidence record google:3.2.1
- AI research evidence record kimi:search_no_data
- AI research evidence record deepseek:c1
Independent Sources
- For Publishers: Know Your AI Citation Authority | Make Lemonade: https://make-lemonade.co.uk/for-publishers/
- Your AEO Score Is a Coin Flip. Here's the Math: https://medium.com/@ekuzevska/your-aeo-score-is-a-coin-flip-heres-the-math-cbd239dca71b
- PublisherAudit — Audit your content site for AI citation, AdSense, performance & schema: https://publisheraudit.com/
- AI Citation Analysis Tool for AEO | Profound: https://www.tryprofound.com/features/answer-engine-insights/citations
Additional AI research evidence138 records
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record anthropic:22-14
- AI research evidence record anthropic:22-16
- AI research evidence record openai:citation_1
- AI research evidence record grok:0
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record grok:1
- AI research evidence record google:1.1.4
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record anthropic:22-14
- AI research evidence record anthropic:22-16
- AI research evidence record anthropic:28-4
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:1-4
- AI research evidence record anthropic:1-11
- AI research evidence record anthropic:1-5
- AI research evidence record anthropic:1-12
- AI research evidence record anthropic:1-19
- AI research evidence record anthropic:1-20
- AI research evidence record perplexity:2
- AI research evidence record perplexity:3
- AI research evidence record perplexity:4
- AI research evidence record perplexity:1
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record anthropic:2-6
- AI research evidence record google:1.2.5
- AI research evidence record grok:0
- AI research evidence record anthropic:1-11
- AI research evidence record anthropic:1-12
- AI research evidence record google:2.2.6
- AI research evidence record perplexity:2
- AI research evidence record anthropic:1-6
- AI research evidence record grok:0
- AI research evidence record google:2.1.1
- AI research evidence record openai:citation_1
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record anthropic:22-14
- AI research evidence record anthropic:22-16
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record perplexity:4
- AI research evidence record perplexity:5
- AI research evidence record anthropic:13-1
- AI research evidence record perplexity:6
- AI research evidence record google:3.1.3
- AI research evidence record google:1.2.3
- AI research evidence record openai:citation_2
- AI research evidence record anthropic:2-13
- AI research evidence record anthropic:2-14
- AI research evidence record perplexity:3
- AI research evidence record perplexity:8
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record grok:0
- AI research evidence record perplexity:2
- AI research evidence record google:3.2.1
- AI research evidence record anthropic:1-6
- AI research evidence record openai:citation_1
- AI research evidence record perplexity:1
- AI research evidence record perplexity:7
- AI research evidence record perplexity:2
- AI research evidence record perplexity:3
- AI research evidence record anthropic:13-1
- AI research evidence record perplexity:4
- AI research evidence record google:3.1.4
- AI research evidence record google:3.1.3
- AI research evidence record google:1.2.3
- AI research evidence record perplexity:6
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record grok:1
- AI research evidence record openai:citation_1
- AI research evidence record google:1.1.4
- AI research evidence record google:2.2.6
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record kimi:search_no_data
- AI research evidence record anthropic:22-11
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-13
- AI research evidence record anthropic:2-14
- AI research evidence record openai:citation_2
- AI research evidence record anthropic:13-1
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record deepseek:c1
- AI research evidence record anthropic:22-16
- AI research evidence record anthropic:22-17
- AI research evidence record anthropic:39-10
- AI research evidence record anthropic:39-13
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:46-14
- AI research evidence record anthropic:46-15
- AI research evidence record anthropic:46-16
- AI research evidence record anthropic:15-4
- AI research evidence record anthropic:15-6
- AI research evidence record kimi:publisheraudit_site
- AI research evidence record kimi:turboaudit_pricing
- AI research evidence record kimi:surva_pricing
- AI research evidence record kimi:auditaiseo_site
- AI research evidence record kimi:seoventra_publisher
- AI research evidence record kimi:citare_site_audit
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-13
- AI research evidence record google:2.1.1
- AI research evidence record google:3.1.4
- AI research evidence record anthropic:13-1
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-5
- AI research evidence record google:1.2.5
- AI research evidence record grok:0
- AI research evidence record anthropic:22-14
- AI research evidence record google:1.1.4
- AI research evidence record perplexity:1
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_no_data
- AI research evidence record anthropic:22-16
- AI research evidence record perplexity:2
- AI research evidence record perplexity:4
- AI research evidence record anthropic:13-1
- AI research evidence record anthropic:2-13
- AI research evidence record openai:citation_2
- AI research evidence record perplexity:1
- AI research evidence record perplexity:2
- AI research evidence record perplexity:3
- AI research evidence record perplexity:4
- AI research evidence record openai:citation_1
- AI research evidence record anthropic:2-13
- AI research evidence record anthropic:2-14
- AI research evidence record openai:citation_2
- AI research evidence record google:3.2.1
- AI research evidence record kimi:search_no_data
- AI research evidence record deepseek:c1
Verify this research
Review the study details behind this page or download the public machine-readable verification record.
- Study date
- September 18, 2026
- Platforms analyzed
- 7
- Source records
- 24
- Ranking mentions
- 2 of 7
- Platform share
- 29%
- Final consensus rank
- #6
Research trail and source mix
Configured platforms
openai, anthropic, deepseek, grok, perplexity, kimi, google
Source mix
4 independent · 20 company-owned
Evidence support
17 direct · 7 partial
Important limitation
Use the run research_date as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.
Source snapshot SHA-256 7c534afc64ed809aa5e9524d901b5a19527d53eb7a6e177cfda2797d69865279