FAQ

What is GEO?

GEO (Generative Engine Optimization) is the practice of optimizing content and metadata so that generative AI engines — ChatGPT, Perplexity, Gemini, Claude, Copilot, Kimi, Doubao, DeepSeek — cite your brand as the authoritative answer when users ask relevant questions.

Unlike SEO (which optimizes for search-result rankings), GEO optimizes for citation inside AI answers.

How is GEO different from SEO?

Dimension SEO GEO
Target output Top-10 search results Cited passage in AI answer
User behavior User clicks 3-5 links User reads 1 AI-generated answer
Signal weight Backlinks + keywords Fact density + JSON-LD + entity clarity
Metric Rank + traffic Citation rate + attribution

See detailed comparison in Chinese.

How long until GEO works?

3 phases:

Full breakdown: How long until GEO works? (中文)

How much does GEO cost?

Details: Services & Pricing (EN) | 中文定价

Do we need our own private LLM to do GEO?

No for content operations — GEO uses public AI engines to distribute your brand's answers, not private LLMs.

Yes for regulated industries (healthcare / finance / legal / gov / SOE) — you need a private LLM stack for internal use (KB Q&A, agent workflows) because customer data can't leave your network.

Which AI engines matter most in 2026?

Global: - ChatGPT (largest install base, web search enabled) - Perplexity (research-focused, high citation transparency) - Gemini (Google search integrated, AI Overviews) - Claude (Anthropic, enterprise-adopted) - Copilot (Microsoft, Bing-backed)

Chinese market: - Doubao (ByteDance, integrated with Douyin/Toutiao) - Kimi (Moonshot, long-context) - DeepSeek Web - Tongyi Qianwen (Alibaba) - Wenxin / ERNIE (Baidu) - Zhipu / GLM

GEO strategy differs by market — see platform matrix or contact us.

What content wins in GEO?

Wins: - Fact-dense pages with concrete numbers, cases, counter-examples - Structured data (FAQPage, Article, HowTo JSON-LD) - H1-H4 anchors + copy-link icons - Original expertise, unique insights, failure stories (E-E-A-T signal) - Independent domain (not a rented subdomain)

Loses: - Generic AI-templated content (engines detect + downrank) - Vague language ("many companies", "high efficiency") - Only positive framing (no boundaries, no reality check) - Hallucinated citations, fake statistics

Details: Can content factories do GEO? (中文)

How do we validate an AI vendor?

8 hard criteria:

  1. Quantified pass criteria in contract
  2. Retest set owned by client
  3. Data boundary documented
  4. Per-user / per-API-key cost accounting
  5. SLA with breach penalties
  6. Model + prompt versioning with A/B
  7. Client-accessible dashboard
  8. Exit clauses (data / model / prompt / logs)

Full checklist: Vendor Acceptance (EN) | 中文验收

Is GEO worth it for small businesses?

Yes, if: - Your buyers are already using AI to research - Your industry has < 20 competitors doing GEO (early-mover advantage) - You can commit 3-6 months minimum

No, if: - You're chasing 1-week campaigns - You only sell to walk-ins (not researched) - You want to spend < USD 1,000 total (not enough to move the needle)

Details: Is GEO worth it for small biz? (中文)

What common AI project pitfalls should we avoid?

Top 8: AI project failure modes (中文)

Short list: 1. No retest set → vendors move goalposts 2. No cost accounting → surprise bills 3. Fine-tune when RAG would work 4. Prompt not versioned → regressions 5. No fallback → single-vendor lock 6. No hallucination monitoring 7. No exit clause 8. AI decisions without human review

How does lead attribution work from AI engines?

Combination of:

We build this into Tier D packages.