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LLM SEO & Generative Engine Optimization
LLM SEOGenerative Engine OptimizationAI Citation Strategy

LLM SEO & 生成式引擎最佳化

在 AI 答案中被引用，而不是被埋沒

73%
AI Citation Rate
Avg. client improvement
6
LLM Platforms
ChatGPT, Perplexity, Gemini, Claude, Copilot, SearchGPT
40+
Entity Signals
Per optimization cycle
30 days
First Results
Typical citation visibility
What Is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is about structuring your website's content, technical markup, and entity authority so large language models — ChatGPT, Perplexity, Gemini, Claude — cite your brand when they generate answers. Traditional SEO chases blue links. GEO targets the AI synthesis layer, where LLMs decide which sources to select, attribute, and quote.

專案失敗的原因

Your competitors are getting cited by ChatGPT Your brand isn't showing up at all. That's an entire traffic channel you're losing as users move away from Google and toward AI-generated answers.
Traditional SEO rankings don't carry over to LLM citations A page-one ranking doesn't mean much when users never click through to search results in the first place.
Your content doesn't have the structured entity signals LLMs need to work with Without clear signals, AI models can't attribute expertise to your brand — so they cite whoever made it easier.
There's no way to measure AI citation performance right now You're guessing while competitors quietly build visibility in generative results.
Your schema markup is outdated or nonexistent LLMs can't parse your authority, your authorship, or what your site is actually about.
Your content was written for humans and Google — not for LLM retrieval AI models skip your pages because they don't find the concise, quotable, fact-dense passages they're looking for.

合規

Entity Authority Building

We build and reinforce your brand's knowledge graph presence across Wikidata, Google Knowledge Panels, and structured entity references. LLMs trust brands with strong, consistent entity signals — so that's what we give them.

Structured Data Architecture

We handle deep JSON-LD implementation: Organization, Person, FAQPage, HowTo, and custom schemas where needed. Every piece of content becomes machine-readable and attribution-ready.

AI Citation Monitoring

We track citations across ChatGPT, Perplexity, Gemini, Claude, and Copilot using our own proprietary process. Monthly reports cover citation frequency, context, and how you stack up against competitors.

Quotable Content Engineering

We restructure existing content and build new pages around concise, fact-dense passages — the kind LLMs prefer to quote. Every paragraph gets optimized for extractive summarization.

Topical Authority Mapping

We audit your content graph and close the gaps so LLMs recognize your site as an authority on your core topics. The cluster architecture is built with retrieval-augmented generation in mind.

Source Credibility Signals

Author pages, credential markup, citation networks, trust signals — these are the things LLMs actually look at when deciding which sources to reference. We make your expertise machine-verifiable.

我們構建的內容

LLM Citation Audit

We query six major AI platforms using your target topics and map exactly where your brand appears, how often, and how that compares to competitors.

Answer Engine Content Strategy

Content briefs and page structures built specifically for LLM retrieval: quotable blocks, definitive statements, entity-rich context throughout.

Knowledge Graph Optimization

Wikidata entries, Google Knowledge Panel claims, cross-platform entity consistency — all of it works together to strengthen your brand's machine-readable identity.

Schema Markup Overhaul

JSON-LD across your entire site, covering 15+ schema types relevant to AI content extraction.

Competitor Citation Analysis

Monthly benchmarking of which competitors get cited, for which queries, and what content patterns are driving their visibility.

RAG-Optimized Technical SEO

Crawlability, content chunking, semantic HTML, internal linking — all optimized for retrieval-augmented generation pipelines.

我們的流程

01

AI Citation Audit

We run your brand through 200+ queries across ChatGPT, Perplexity, Gemini, Claude, and Copilot. You get a baseline citation report showing exactly where you stand and where competitors are pulling ahead.
Week 1
02

Entity & Schema Architecture

We map your brand's entity graph, fix inconsistencies, claim knowledge panels, and build a structured data layer from the ground up. This is the foundation LLMs need to recognize your authority.
Weeks 2-3
03

Content Engineering

We restructure existing pages and create new content with quotable passages, definitive answers, and fact-dense formats. Every page gets an AI-extraction optimization pass before we're done with it.
Weeks 3-5
04

Technical Implementation

JSON-LD deployment, semantic HTML cleanup, internal link architecture, crawl optimization. We ship the technical changes that make your content machine-parseable at scale.
Weeks 5-7
05

Monitor & Iterate

Ongoing citation tracking across all major AI platforms. Monthly reports show citation frequency, new query coverage, and the content adjustments we're making based on what's actually working.
Ongoing
Next.jsSchema.orgJSON-LDVercelGoogle Search ConsoleAhrefsCustom Entity Graphs

常見問題

什麼是生成式引擎最佳化 (GEO)？

GEO 是最佳化您網站的實踐，使 ChatGPT、Perplexity 和 Gemini 等 AI 系統在其生成的答案中引用您的品牌。它將結構化資料、實體權威性和內容工程結合在一起，使您的頁面在 LLM 合成回應時成為首選來源。這是一個獨立於傳統 SEO 的學科——相關但並不相同。

LLM SEO 與傳統 SEO 有何不同？

傳統 SEO 是關於在 Google 藍色連結中排名。LLM SEO 是關於在多個平台的 AI 生成答案中被引用。信號不同——LLM 更關心實體權威性、可引用內容、結構化標記和來源可信度，而非反向連結量或關鍵字密度。兩者都重要，但需要不同的策略。

您能保證我的品牌會被 ChatGPT 引用嗎？

沒有代理商能保證特定的 AI 引用。LLM 輸出本質上是概率性的。我們能保證的是實施所有已知的信號來增加引用可能性：結構化資料、實體圖表、可引用內容、來源權威性。我們大多數客戶在 30 到 60 天內看到可測量的引用改進。

您如何追蹤 AI 引用？

我們使用您的目標主題和競爭對手比較，系統性地查詢 ChatGPT、Perplexity、Gemini、Claude、Copilot 和 SearchGPT。我們每月記錄引用頻率、背景和確切措辭。您會獲得一個儀表板，顯示趨勢、新引用、失去的引用，以及競爭對手的動向。

如果我做 GEO，我還需要傳統 SEO 嗎？

是的——這值得理解。許多 AI 系統將網頁搜尋結果作為其檢索管道的一部分，所以強大的傳統 SEO 直接促進 LLM 可見性。GEO 不會取代 SEO；它層疊在其上。我們的技術實施設計用於同時使兩個管道受益。

生成式引擎最佳化需要多長時間才能看到結果？

大多數客戶在 30 天內看到初始引用改進，特別是在 Perplexity 和 Gemini 中，它們更頻繁地更新檢索索引。ChatGPT 引用可能需要更長時間，取決於訓練資料週期。在 3 到 6 個月的持續監控和迭代中，結果會複利。

LLM SEO & GEO from $8,000
Fixed-fee engagement. Monthly retainer available for ongoing citation monitoring.
See all packages →
Next.js DevelopmentCore Web Vitals OptimizationCore Web Vitals Complete Guide 2026

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