{"citations":{"source_mix":{"company_owned":22,"independent":4,"unclear":1},"sources_referenced_by_questions":0,"support_mix":{"direct":17,"partial":9},"total_sources":27,"unique_domain_count":17},"claims":[{"claim_id":"claim-001","confidence":"verified","observed_at":"2026-09-17","platform_support":["anthropic","deepseek","google","grok","kimi","openai","perplexity"],"predicate":"platforms_analyzed","qualifier":"valid included platform responses","subject":"Best AI Citation Architecture Audits","unit":"platforms","value":7},{"claim_id":"claim-002","confidence":"verified","observed_at":"2026-09-17","platform_support":["grok","kimi"],"predicate":"final_consensus_rank","qualifier":"AI Citation Architecture Audits","subject":"BeCited","unit":"rank","value":6},{"claim_id":"claim-003","confidence":"verified","observed_at":"2026-09-17","platform_support":["grok","kimi"],"predicate":"platform_mentions","qualifier":"out of 7","subject":"BeCited","unit":"platforms","value":2},{"claim_id":"claim-004","confidence":"verified","observed_at":"2026-09-17","platform_support":["grok","google"],"predicate":"fit_rating_count","qualifier":"strong","subject":"BeCited","unit":"platforms","value":2},{"claim_id":"claim-005","confidence":"verified","observed_at":"2026-09-17","platform_support":["openai","anthropic","perplexity"],"predicate":"fit_rating_count","qualifier":"good","subject":"BeCited","unit":"platforms","value":3},{"claim_id":"claim-006","confidence":"verified","observed_at":"2026-09-17","platform_support":["deepseek"],"predicate":"fit_rating_count","qualifier":"weak","subject":"BeCited","unit":"platforms","value":1},{"claim_id":"claim-007","confidence":"verified","observed_at":"2026-09-17","platform_support":["kimi"],"predicate":"fit_rating_count","qualifier":"uncertain","subject":"BeCited","unit":"platforms","value":1}],"content_scope":"aggregated facts, computed metrics, and retrieval summaries","entities":[{"average_rank":5,"best_rank":4,"entity_id":"entity-001","entity_type":"company","final_rank":6,"name":"BeCited","platform_mentions":2,"platform_share":0.2857142857142857}],"identity":{"dataset_url":"https://aimarketingconsensusindex.com/datasets/ai-citation-authority-building/architecture-audits/becited.json","page_url":"https://aimarketingconsensusindex.com/ai-citation-authority-building/architecture-audits/becited","report_type":"fit_review","study_id":"AIMCI-STUDY-774D26E96F44","title":"BeCited for AI Citation Architecture Audits: AI Consensus Fit Review"},"limitations":["Use the run researchdate as the study date. Platform-reported dates are provenance metadata and do not independently prove freshness.","All included platforms evaluated fit, but platformmentions counts only platforms that named the entity during ranking discovery.","Do not resolve conflicting product names, pricing, or capabilities by guessing; describe the conflict and tell buyers what to verify.","The supplied URLs were collected from platform responses and were not independently validated by the writer stage.","Company-owned citations materially outnumber independent citations; do not describe company claims as independently verified.","Citations are platform-reported evidence, not independently verified facts. No-search model claims require explicit verification before being described as current facts."],"methodology":{"fit_rating_contract":["strong","good","mixed","weak","uncertain"],"included_valid_platform_count":7,"maximum_finalists":10,"minimum_mentions":2,"name":"AI Marketing Consensus Index cross-platform AI consensus analysis","platforms_included":["anthropic","deepseek","google","grok","kimi","openai","perplexity"],"platforms_queried":["openai","anthropic","deepseek","grok","perplexity","kimi","google"],"stages":["ranking_discovery","fit_assessment","normalization","editorial_synthesis"],"version":"alias-table-1"},"provenance":{"generated_at":"2026-09-17 12:19:19.784176+00","research_date":"2026-09-17","source_snapshot_sha256":"d1f8c7cd6c4b93b7c9ea68ba677461fe20db9157564a9d28ed6087d5cc0e6130","verification_scope":"public_verification"},"ranking":{"candidates_evaluated":52,"qualified_finalists":6,"ranking_unit":"Audit company, audit service, or advisory provider"},"schema_version":4,"summary":"BeCited is a good fit for a focused, human-reviewed AI citation architecture audit across four major conversational engines at a transparent $2,000 one-time price. Two of seven platforms named BeCited during the ranking stage (grok and kimi), a 28.6% share of included platform responses, with an average listed rank of 5.0 and a best listed rank of 4. The strongest reason to consider it is the Full Audit's direct alignment with the buyer criteria: source mapping, competitor comparison, gap analysis, and a prioritized 90-day plan. The main limitation is narrow scope — four engines, no…","target_buyer":"Companies seeking AI Citation Architecture Audits across AI search, generative-answer, and recommendation platforms","topic":{"base_category":"AI citation and authority building","category_criteria":["Map first-party and third-party sources","identify which domains influence AI answers","compare competitor citation networks","detect missing authority sources","evaluate source concentration","and receive a prioritized plan for improving its citation environment"],"geography":"United States","slug":"best-ai-citation-architecture-audits","title":"Best AI Citation Architecture Audits","use_case":"AI Citation Architecture Audits"}}