Answer Capsule
BeCited is a good, but not clearly publisher-specialized, fit for publishers and review websites that need a human-reviewed AI search audit covering recommendation measurement, competitor benchmarking, source-domain analysis, and a prioritized 90-day roadmap. Three of seven platforms named BeCited during the ranking stage (deepseek, grok, kimi), a 42.9% share of included platform responses, at an average listed rank of 3.67 and a best rank of 2. The strongest reason to consider it is its manual, citation-level review across ChatGPT, Gemini, Perplexity, and Claude at a fixed $2,000 Full Audit price. The main limitation is that all substantive evidence is company-owned, the public sample is SaaS-focused, and no independent validation of methodology or publisher outcomes was found.
Research Snapshot
| Field | Value |
|---|---|
| Platform mentions in ranking stage | 3 of 7 platforms (deepseek, grok, kimi) |
| Share of included platform responses | 42.9% |
| Average listed rank | 3.67 |
| Best listed rank | 2 (grok) |
| Relevant product/model/plan | Full Audit ($2,000); Snapshot/Starter check ($199); Quarterly Tracking ($1,500/quarter) |
| Overall use-case fit | Good, with mixed and uncertain platform ratings |
| Research date | 2026-09-18 |
Why BeCited Qualified for This Study
Questions This Section Answers
- Is BeCited a good choice for AI Search Audits for Publishers and Review Websites?
- How many AI platforms recommended BeCited for publisher and review-site AI search audits?
BeCited qualified because three of the seven included platforms named it during ranking discovery, and all seven platforms then evaluated it against the publisher and review-site use case. The ranking-stage mentions came from deepseek (rank 4), grok (rank 2), and kimi (rank 5), producing an average listed rank of 3.67 and a best rank of 2. BeCited finished first in the final ordering for this use case.
Fit ratings were not unanimous. OpenAI, Google, Grok, and Perplexity rated BeCited a good fit; Anthropic rated it mixed; DeepSeek and Kimi rated it uncertain [1]. The split matters: the two uncertain ratings came from platforms that could not confirm product details from public sources, not from platforms that found contradicting evidence.
The qualification rests on relevance to the stated buyer need rather than proven performance. BeCited publicly positions its audits around AI recommendation visibility, source mapping, competitor comparison, and a 90-day action plan, which maps directly to the six configured evaluation criteria [1].
The Product, Model, Plan, or Service Most Relevant to AI Search Audits for Publishers and Review Websites
Questions This Section Answers
- Which BeCited plan is best for a publisher that needs a full cross-engine AI citation audit?
- How does the $199 BeCited Snapshot differ from the $2,000 Full Audit for a review website?
The Full Audit is the plan most relevant to this use case. It is described as a $2,000 one-time engagement running 100–300 buying-intent prompts across ChatGPT, Gemini, Perplexity, and Claude with a one-week turnaround, returning a BeCited Score, engine-by-engine breakdown, source map, gap analysis, prioritized 90-day action plan, and a 45-minute strategy session [10].
The Snapshot is the lower-cost entry point. It is listed at $199 one-time with a 48-hour turnaround, 10 buying-intent prompts on Perplexity only, and a single-page HTML deliverable, with the $199 credited toward a Full Audit within 30 days [14]. Quarterly Tracking is listed at $1,500 per quarter as a re-run of the full audit [16].
Naming is inconsistent across sources. The lower-cost tier appears as "Snapshot" on the services page, as "Starter check" in some descriptions, and as "BeCited Score Starter" in the ranking stage [16]. Buyers should confirm the current tier name and contents directly.
What the AI Platforms Agreed About
Questions This Section Answers
- What do AI platforms agree BeCited does well for publisher and review-site audits?
- Does BeCited measure AI recommendations rather than only traditional search rankings?
Platforms broadly agreed on four points. First, BeCited measures AI recommendations and citations rather than only conventional rankings, using buying-intent prompts across four engines [19]. Second, it produces a source map or Source Influence Map that tiers the domains AI engines cite in the buyer's category [22]. Third, it delivers competitor benchmarking with prompt-level gap analysis [25]. Fourth, it ships a prioritized 90-day action plan rather than a score alone [25].
Platforms also agreed on the pricing structure. Multiple platforms independently reported $199 for Snapshot, $2,000 for the Full Audit, and $1,500 per quarter for Quarterly Tracking [29]. This is the most consistent factual finding in the study.
Agreement here reflects consistent reading of the same company-owned pages. It does not establish that the audits produce citation gains, and no platform supplied independent outcome data.
Where the AI Platforms Disagreed or Were Uncertain
Questions This Section Answers
- Why did some AI platforms rate BeCited uncertain for publisher AI search audits?
- Is BeCited's one-time audit model a problem for publishers facing citation volatility?
The sharpest disagreement concerned whether BeCited is a sufficient fit for publishers at all. Anthropic rated it mixed, arguing that a one-time audit does not address citation churn documented at 40–60% monthly variability and that at least three consecutive monthly cycles are needed before movement is treated as signal [32]. OpenAI and Google rated it good while noting the same point-in-time limitation [34].
DeepSeek and Kimi rated it uncertain for different reasons. DeepSeek reported that tier names and contents came from the ranking stage and were not independently confirmed on the public site, and that no public pricing or contract terms were located [36]. Kimi reported finding no verifiable public information for BeCited at all and treated the entity as unproven [37]. DeepSeek's research date was 2026-01-15, eight months before the authoritative run date, and its search was disabled, which limits how much weight its uncertainty should carry.
Two internal conflicts also surfaced. The home page describes 10 Snapshot prompts on Perplexity, while the services page says the single-engine choice is selected by the buyer [38]. Public materials describe both 19 site-readiness checks and varying lists of free versus paid checks [38]. Neither conflict was resolved by the supplied evidence.
Use-Case-Specific Features and Capabilities
Questions This Section Answers
- Does BeCited cover the six capabilities a publisher needs in an AI search audit?
- How does BeCited handle source-domain authority analysis for review websites?
Against the six configured criteria, platform findings were mostly favorable but unevenly evidenced.
| Criterion | Platform assessment | Key evidence |
|---|---|---|
| Recommendation analysis | Advantage | 100–300 buying-intent prompts across four engines; BeCited Score 0–100 |
| Mention and citation measurement | Advantage | Manual reading of every answer; brand-variant matching; confidence intervals |
| Competitor benchmarking | Advantage | Prompt-level gap analysis and competitor interception plans |
| Influential source-domain analysis | Advantage | Source Influence Map tiering cited domains by observed AI trust rather than Domain Authority |
| Content and authority gaps | Neutral | Root-cause analysis and per-page readiness scoring, but no verified publisher-specific signals such as author expertise pages or affiliate transparency |
| Prioritized improvement roadmap | Advantage | 90-day plan ranked by leverage with per-engine job tickets and success metrics |
Technical readiness is a supporting capability rather than a core one. The paid audit evaluates 19 site-readiness signals including robots.txt, llms.txt, structured data, rendering completeness, page speed, content freshness, entity readiness, and per-page quotable content [41]. These checks can surface technical barriers to AI discovery, but they do not by themselves establish that editorial content will be selected or cited.
Measurement rigor is company-reported. BeCited states that every answer is personally reviewed, brand variants are manually matched, and two-person scoring reached approximately 72% agreement with a Cohen's kappa of 0.722 [43]. No independent source in the reviewed materials validates these figures.
Pricing, Fees, Contracts, and Ongoing Costs
Questions This Section Answers
- How much does BeCited cost, and are there setup or cancellation fees?
- What are BeCited's refund and report-sharing terms for a publisher?
Published pricing is unusually transparent for a service-led audit. Snapshot is $199 one-time with a 48-hour turnaround; the Full Audit is $2,000 one-time with a one-week turnaround; Quarterly Tracking is $1,500 per quarter; and Relevance Engineering is custom project work typically priced at $8,000–$25,000 with no retainer required [45].
No separate mandatory setup or seat-based fees were identified in the reviewed materials [48]. Implementation work such as content rewrites, schema work, source claiming, or citation seeding may incur custom project charges [49].
Contract terms carry three practical constraints. Payment is due upon engagement unless otherwise agreed; unsatisfied buyers are instructed to contact BeCited within 14 days of delivery to discuss resolution, and the terms do not state a guaranteed refund; and reports are licensed for internal business use only, with no resale, redistribution, or public sharing without written permission [50]. Cancellation notice, renewal mechanics, and proration for Quarterly Tracking were not verified in the reviewed materials [50].
The internal-use license is a material issue for agencies and publishers that want to publish methodology or benchmark results. Buyers in that position should confirm sharing rights in writing before purchase.
Best Suited For
Questions This Section Answers
- Who gets the most value from a BeCited Full Audit for publisher AI visibility?
- Is BeCited best for a publisher that wants a fixed-price diagnostic instead of a monitoring subscription?
BeCited is best suited to publishers and review sites that want a single, comprehensive baseline diagnostic with human review rather than a self-serve dashboard. Platforms identified three recurring buyer profiles: teams needing competitor interception analysis and influential-source mapping; teams wanting a prioritized 90-day roadmap with execution detail; and buyers who prefer a fixed-price project over recurring platform fees [51].
It also suits buyers who want a low-risk entry point. The $199 Snapshot with a 48-hour turnaround and credit toward a Full Audit within 30 days lets a publisher self-qualify before committing $2,000 [54]. A free instant site-readiness check covering 9 of 19 signals with no email required was also reported [56].
Probably Not Best Suited For
Questions This Section Answers
- Who should not choose BeCited for publisher AI search audits?
- Is BeCited suitable for a publisher that needs continuous weekly citation monitoring?
BeCited is probably not the best choice for organizations needing large-scale, continuously automated monitoring of thousands of URLs or keywords [57]. It is also a weak fit for publishers that need proven editorial-media benchmarks, newsroom workflow integrations, or independently validated publisher case studies, because none were verified in the reviewed materials [59].
Buyers seeking guaranteed citation growth should look elsewhere. The terms state no guaranteed outcomes and describe audits as point-in-time diagnostics subject to model updates, training-data refreshes, index changes, competitor content, and query variation [61]. Publishers dependent on real-time tracking of which third-party domains earn citations on their behalf also fall outside the demonstrated scope [60].
When Another Option May Be Better
Questions This Section Answers
- What is a better alternative to BeCited for a publisher that needs continuous AI citation monitoring?
- When is a self-serve AI visibility platform better than a BeCited audit?
Several alternatives were named for specific gaps. For weekly or monthly re-measurement, platforms pointed to Siftly, Profound, and Peec AI, with Peec AI starting at roughly €89 per month [63]. For per-URL source-domain authority analysis and source-target workflows, Semrush AI Visibility and PromptMonitor were named, with Semrush ranking sources that mention competitors but not your brand as outreach targets [64].
For buyers who need immediate implementation with published features and pricing, platforms named SEOVentra, TurboAudit, Viali, Frase, and Surva.ai. TurboAudit publishes pricing starting at $39.99 per month; Viali offers a GEO Audit with six weighted scores; AuditAI offers white-label exports at $29; and Surva.ai supports up to 1,000 pages per audit on its Business plan [66]. For AI crawler access checks specifically, SEOVentra and Citare were cited for GPTBot, ClaudeBot, PerplexityBot, and Google-Extended analysis [70].
A custom research engagement may be better when the buyer needs statistically designed publisher query panels, regional personalization testing, or independent validation of citation accuracy [72]. The broader ai search audits market intelligence directory lists additional providers across these categories.
Questions to Verify Before Buying
Questions This Section Answers
- What should a publisher confirm with BeCited before signing a contract?
- Can BeCited provide a publisher or review-site sample audit before purchase?
Ten verification items recur across platform responses. Buyers should confirm: whether a publisher or review-site sample covering informational, comparison, review, and commercial-intent queries exists [73]; how publisher-specific authority signals are scored, including author expertise, review methodology, testing evidence, affiliate disclosures, and editorial independence [75]; whether the buyer can supply a custom prompt panel segmented by content type, audience, category, geography, and intent [73]; and how many URLs, authors, brands, competitors, and domains the Full Audit includes [78].
They should also confirm how citations are verified when AI answers cite a page inaccurately, cite a homepage instead of the relevant article, or use syndicated or duplicated content [75]; what data-retention, confidentiality, and deletion practices apply to submitted site and competitive information [80]; the cancellation, renewal, proration, and refund terms for Quarterly Tracking [80]; whether reports can be shared with clients, advertisers, agencies, or editorial stakeholders despite the internal-use license [80]; what is included in the $2,000 fee if additional prompts, engines, domains, or rechecks are requested [81]; and how BeCited distinguishes correlation between a source-domain change and later AI visibility movement from actual causation [75].
Final AI Consensus Verdict
BeCited is a good fit for a publisher or review website seeking a focused, human-reviewed AI-search audit with recommendation measurement, competitor benchmarking, source-domain analysis, and a prioritized action plan. It is not yet a clearly strong fit. Public evidence is vendor-reported, the demonstrated sample is SaaS-focused, and publisher-specific query design, authority signals, scalability, and independent outcomes remain unverified [82].
The consensus is conditional rather than settled. Four platforms rated it good, one mixed, and two uncertain, with the uncertain ratings driven by unverifiable public detail rather than contradicting evidence [85]. Buyers should treat the $2,000 Full Audit as a credible single baseline and confirm publisher-specific scope, report-sharing rights, and re-measurement options before committing. The AI Search Audits for Publishers and Review Websites consensus index compares BeCited against the other finalists in this study.
How This Review Was Produced
Seven AI platforms were asked which companies they would recommend for an AI search audit of a publisher or review website, and why. Three platforms named BeCited during ranking discovery; all seven then evaluated BeCited against the six configured criteria: recommendation analysis, mention and citation measurement, competitor benchmarking, influential source-domain analysis, content and authority gaps, and a prioritized improvement roadmap. Platform responses were aggregated into the fit ratings, pricing summary, limitations, and verification questions shown above. The authoritative research date for this study is 2026-09-18.
Methodology Limitations
Platform-reported research dates differ from the authoritative run date. DeepSeek reported 2026-01-15, eight months earlier, and its search was disabled, so its uncertainty reflects limited retrieval rather than confirmed absence [86]. Platform-reported dates are provenance metadata and do not independently prove freshness.
Company-owned citations materially outnumber independent citations in this study, so company claims should not be read as independently verified. The supplied URLs were collected from platform responses and were not independently validated. Citations are platform-reported evidence, not verified facts. No platform supplied independent outcome data on citation-share gains, publisher results, or comparative accuracy against other audit providers. Conflicting product names, pricing details, and capability descriptions were preserved rather than resolved.
Sources
Company-Owned Sources
- AuditAI — AI Search Visibility Auditor: https://auditaiseo.com/
- BeCited — AI Search Visibility Audit: https://becited.io/
- AI Search Guide — How AI engines pick which brands to cite: https://becited.io/ai-search-guide
- The Three Pillars of GEO: Retrievability, Citability ... - BeCited: https://becited.io/ai-search-guide/three-pillars-of-geo
- GEO Audit — Measure where you stand in AI search - BeCited: https://becited.io/audit/
- Methodology — How BeCited keeps the audit honest: https://becited.io/methodology
- Sample BeCited GEO Audit — what every audit looks like: https://becited.io/sample-report
- Services — Audits, tracking, and relevance engineering | BeCited: https://becited.io/services
- Relevance Engineering — Move the needle, not the dashboard: https://becited.io/services/relevance-engineering
- Sample GEO Snapshot — BeCited: https://becited.io/snapshot-sample/snapshot
- Terms of Service — BeCited: https://becited.io/terms
- 1596 visibility overview report: https://de.semrush.com/kb/1596-visibility-overview-report
- Top domains cited by AI search: Analysis based on 30M sources - Peec AI: https://peec.ai/blog/top-domains-cited-by-ai-search-analysis-based-on-30m-sources
- PublisherAudit — Audit your content site for AI citation, AdSense, performance & schema: https://publisheraudit.com/
- TurboAudit Pricing — Plans for Every Stage: https://turboaudit.ai/
- GEO Audit — Six Scores, One Fix Plan: https://viali.ai/product/geo-audit/
- Site Audit — 250+ technical SEO + AI readiness checks: https://www.citare.ai/site-audit
- What Is AI Visibility? Complete Guide (2026) | Frase | Frase: https://www.frase.io/blog/ai-visibility
- Audit your whole site, then fix the pages that matter first: https://www.frase.io/features/auditor
- AI SEO Audit - Crawl Your Website and Fix AI Visibility Issues: https://www.surva.ai/products/ai-seo-audit
- Official pricing and terms source: https://becited.io#pricing
Additional AI research evidence86 records
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record deepseek:c1
- AI research evidence record grok:web:0
- AI research evidence record perplexity:c4
- AI research evidence record google:2.1.2
- AI research evidence record kimi:search_2026-09-18_no_results
- AI research evidence record perplexity:c12
- AI research evidence record google:1.1.6
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record perplexity:c4
- AI research evidence record google:2.1.2
- AI research evidence record perplexity:c1
- AI research evidence record google:2.1.3
- AI research evidence record openai:becited_services
- AI research evidence record deepseek:c1
- AI research evidence record grok:web:0
- AI research evidence record openai:becited_home
- AI research evidence record grok:web:0
- AI research evidence record google:1.1.6
- AI research evidence record openai:becited_methodology
- AI research evidence record google:2.1.4
- AI research evidence record perplexity:c12
- AI research evidence record openai:becited_sample
- AI research evidence record perplexity:c4
- AI research evidence record google:2.1.5
- AI research evidence record anthropic:29
- AI research evidence record openai:becited_services
- AI research evidence record perplexity:c1
- AI research evidence record google:2.1.3
- AI research evidence record anthropic:24
- AI research evidence record anthropic:10
- AI research evidence record openai:becited_terms
- AI research evidence record google:1.1.6
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_2026-09-18_no_results
- AI research evidence record openai:becited_home
- AI research evidence record openai:becited_services
- AI research evidence record anthropic:3
- AI research evidence record openai:becited_home
- AI research evidence record perplexity:c15
- AI research evidence record openai:becited_methodology
- AI research evidence record google:2.2.1
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c10
- AI research evidence record google:2.1.3
- AI research evidence record openai:becited_home
- AI research evidence record openai:becited_services
- AI research evidence record openai:becited_terms
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record perplexity:c4
- AI research evidence record perplexity:c1
- AI research evidence record google:2.1.3
- AI research evidence record anthropic:3
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record openai:becited_sample
- AI research evidence record anthropic:29
- AI research evidence record openai:becited_terms
- AI research evidence record anthropic:44
- AI research evidence record anthropic:10
- AI research evidence record anthropic:45
- AI research evidence record anthropic:44
- AI research evidence record kimi:turboaudit_pricing
- AI research evidence record kimi:viali_geo_audit
- AI research evidence record kimi:auditaiseo_pricing
- AI research evidence record kimi:surva_audit
- AI research evidence record kimi:seoventra_publishers
- AI research evidence record kimi:citare_audit
- AI research evidence record openai:becited_home
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record openai:becited_methodology
- AI research evidence record anthropic:29
- AI research evidence record google:1.1.6
- AI research evidence record openai:becited_services
- AI research evidence record perplexity:c4
- AI research evidence record openai:becited_terms
- AI research evidence record perplexity:c1
- AI research evidence record openai:becited_sample
- AI research evidence record anthropic:29
- AI research evidence record kimi:search_2026-09-18_no_results
- AI research evidence record deepseek:c1
- AI research evidence record deepseek:c1
Independent Sources
- Top Domains Cited by AI Search: Analysis of 30M Sources – Peec AI: https://almcorp.com/blog/top-domains-cited-by-ai-search/
- Share of Citation Benchmarks 2026: https://authoritytech.io/curated/share-of-citation-benchmarks-2026-ai-engines
- Web search results for AI search audit tools - no BeCited mentions: https://seoventra.com/solutions/publishers
- Top cited domains in AI: What 10M+ citations reveal about visibility - Decoding: https://trydecoding.com/blog/top-cited-domains-in-ai/
- Best AI Visibility Tools for Citation Source Targets (2026: https://www.therankmasters.com/insights/ai-visibility/best-ai-visibility-tools-citation-source-targets
Additional AI research evidence86 records
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record deepseek:c1
- AI research evidence record grok:web:0
- AI research evidence record perplexity:c4
- AI research evidence record google:2.1.2
- AI research evidence record kimi:search_2026-09-18_no_results
- AI research evidence record perplexity:c12
- AI research evidence record google:1.1.6
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record perplexity:c4
- AI research evidence record google:2.1.2
- AI research evidence record perplexity:c1
- AI research evidence record google:2.1.3
- AI research evidence record openai:becited_services
- AI research evidence record deepseek:c1
- AI research evidence record grok:web:0
- AI research evidence record openai:becited_home
- AI research evidence record grok:web:0
- AI research evidence record google:1.1.6
- AI research evidence record openai:becited_methodology
- AI research evidence record google:2.1.4
- AI research evidence record perplexity:c12
- AI research evidence record openai:becited_sample
- AI research evidence record perplexity:c4
- AI research evidence record google:2.1.5
- AI research evidence record anthropic:29
- AI research evidence record openai:becited_services
- AI research evidence record perplexity:c1
- AI research evidence record google:2.1.3
- AI research evidence record anthropic:24
- AI research evidence record anthropic:10
- AI research evidence record openai:becited_terms
- AI research evidence record google:1.1.6
- AI research evidence record deepseek:c1
- AI research evidence record kimi:search_2026-09-18_no_results
- AI research evidence record openai:becited_home
- AI research evidence record openai:becited_services
- AI research evidence record anthropic:3
- AI research evidence record openai:becited_home
- AI research evidence record perplexity:c15
- AI research evidence record openai:becited_methodology
- AI research evidence record google:2.2.1
- AI research evidence record perplexity:c1
- AI research evidence record perplexity:c10
- AI research evidence record google:2.1.3
- AI research evidence record openai:becited_home
- AI research evidence record openai:becited_services
- AI research evidence record openai:becited_terms
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record perplexity:c4
- AI research evidence record perplexity:c1
- AI research evidence record google:2.1.3
- AI research evidence record anthropic:3
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record openai:becited_sample
- AI research evidence record anthropic:29
- AI research evidence record openai:becited_terms
- AI research evidence record anthropic:44
- AI research evidence record anthropic:10
- AI research evidence record anthropic:45
- AI research evidence record anthropic:44
- AI research evidence record kimi:turboaudit_pricing
- AI research evidence record kimi:viali_geo_audit
- AI research evidence record kimi:auditaiseo_pricing
- AI research evidence record kimi:surva_audit
- AI research evidence record kimi:seoventra_publishers
- AI research evidence record kimi:citare_audit
- AI research evidence record openai:becited_home
- AI research evidence record openai:becited_home
- AI research evidence record anthropic:10
- AI research evidence record openai:becited_methodology
- AI research evidence record anthropic:29
- AI research evidence record google:1.1.6
- AI research evidence record openai:becited_services
- AI research evidence record perplexity:c4
- AI research evidence record openai:becited_terms
- AI research evidence record perplexity:c1
- AI research evidence record openai:becited_sample
- AI research evidence record anthropic:29
- AI research evidence record kimi:search_2026-09-18_no_results
- AI research evidence record deepseek:c1
- 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
- 28
- Ranking mentions
- 3 of 7
- Platform share
- 43%
- Final consensus rank
- #1
Research trail and source mix
Configured platforms
openai, anthropic, deepseek, grok, perplexity, kimi, google
Source mix
5 independent · 23 company-owned
Evidence support
25 direct · 2 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 9981bf7d2eea4ad7501fe877710c088ecda79232d593e632c5f9610faa159195