# Free AI visibility audit for global brands > Free AI visibility audit for global brands. See whether DeepSeek, Qwen and Doubao can find, explain and recommend your site. China-specific. No login. Published: 2026-05-05 Updated: 2026-05-07 (form-first hero + private-beta disclosure) Site: https://www.eastbound.ai/ai-visibility-audit/ Audit runner: https://www.eastbound.ai/dashboard.html Markdown source: https://www.eastbound.ai/ai-visibility-audit/index.md ## Run the audit (private beta) The audit form on https://www.eastbound.ai/ai-visibility-audit/ captures three fields: website URL, brand name, work email. The full audit pipeline is currently in **private beta** — we capture your details and email a sampled report within 48 hours, handled by an Eastbound researcher rather than an automated pipeline. To skip the wait and walk through results live, book a 30-min consultation: https://www.eastbound.ai/book-consultation/. No login, no credit card. ## What an AI visibility audit actually checks Generative search has two stages, not one. **Citation selection** decides whether a page enters the engine's source pool. **Citation absorption** decides whether the page actually shapes the answer language versus sitting unused. The user-visible mention is a third stage downstream of both. A real audit measures all three layers, separately. Most "AI visibility checker" tools collapse them into a single score. We don't, because the fix for each is different — and a single score hides which layer is the actual blocker. The audit also reports both onsite readiness and offsite visibility. For brand visibility in Mainland China, offsite signal is often the dominant factor — third-party citations are observed roughly 6.5× more often than self-citations in published GEO research. ## The six layers we score The audit grades against the citation pyramid. Each layer is a prerequisite for the next: 1. **Search-engine indexed.** Bing for ChatGPT search; Google for AI Overview / Gemini. 2. **AI-crawler reachable.** Granular robots.txt across five buckets — search/retrieval, user-triggered, training, opt-out tokens, undeclared. 3. **AI-parseable.** Clean HTML, semantic URLs, llms.txt, Markdown alternates. 4. **Selection-worthy.** Relevance, specificity, length, authority signals. Pages with real numbers and named entities are cited 50%+ more. 5. **Absorption-worthy.** Quotable phrasing, evidence density, structured comparisons. Length sweet spot 1,000–3,000 words. 6. **Third-party validated.** Cited from Reddit, Zhihu, Baidu Baike, Hacker News, vertical media. Highest-leverage signal — slowest to build. JSON-LD schema is a Bing/Copilot signal in our experimental sample, not a universal one. We flag it as Bing-only rather than counting it as broader AI-readiness evidence. ## What makes this audit different — China specificity Across a 540-call panel (30 prompts × 3 LLMs × 3 reps × 2 turns) we ran in May 2026, the three Chinese-trained engines we tested cited Mainland-CN sources at materially different rates: | Engine | Mainland-CN source share | Notable secondary sources | |-----------|--------------------------|------------------------------------------------| | DeepSeek | 72.3% | Wikipedia 21%, YouTube 20%, Reddit secondary | | Qwen | 85.0% | Institutional / professional bodies overrepresented | | Doubao | 88.6% | Commerce / lifestyle aggregators (SMZDM, Xiaohongshu) overrepresented | Top-15 source overlap (Jaccard) between the three engines was 0.20–0.30. They operate on substantially different source substrates. An audit built for ChatGPT or Gemini systematically under-reports what Mainland Chinese consumers see. On a re-run of the identical panel one week later, source mention rates correlated at Pearson r 0.97–0.99 (ICC 0.97–0.99). Top-5 source membership was perfectly stable (κ = 1.00). Doubao top-15 κ = 0.46 — long-tail source ranking is less stable for Doubao specifically. See: https://www.eastbound.ai/blog/three-chinese-ais.html ## What you get back - **A — Executive snapshot.** Aggregate score 0–100 plus single most-impactful blocker. - **B — Onsite readiness.** Per-bucket robots.txt, llms.txt, Markdown alternates, semantic URLs, structured-data sanity (with Bing-only caveat). - **D — Per-LLM × category × niche surfacing.** Whether each engine surfaces your brand at L1 and L2; absorption-depth column. - **E — Audience hot topics.** Live mainland-CN consumer questions in your category. - **F — Top fixes.** 3–7 prioritised actions, labelled as measured / hypothesis / intervention test. ## What this audit does NOT do - Guarantee a ranking position in any number of days. - Claim JSON-LD makes AI find you (Bing/Copilot only in our sample). - Recommend "add an FAQ section" — pure FAQ-format pages underperform. - Recommend "increase content length" generically — only if each chunk adds new info. - Measure sales / conversion / attributable revenue. Brand visibility, not traffic. - Inspect any engine's training data. We can only measure what engines self-attribute. Every recommendation is labelled measured evidence, prior-knowledge hypothesis, or planned intervention test. We do not guarantee. ## Who this audit is built for - **Western luxury, fashion and beauty brands** evaluating China expansion (Zhihu / Xiaohongshu / SMZDM / Bilibili surface heavily; ultra-luxury collapses to The Purse Forum / Vogue Business / auction archives). - **Travel, hospitality and destination marketing** tracking inbound Mainland-CN demand and recommendation behaviour across DeepSeek / Qwen / Doubao. - **B2B technology and SaaS**, especially developer-facing — DeepSeek's developer-corpus weight is more pronounced than Qwen / Doubao for technical questions. ## Related Eastbound resources - DeepSeek-only rank tracker: https://www.eastbound.ai/deepseek-rank-tracker/ - Why your brand looks different on every Chinese AI: https://www.eastbound.ai/blog/three-chinese-ais.html - The 5 websites Chinese AI reads before recommending a luxury brand: https://www.eastbound.ai/blog/luxury-ai-sources.html - Eastbound methodology: https://www.eastbound.ai/methodology/