--- id: wiki-2026-0508-seo title: SEO category: 10_Wiki/Topics status: verified canonical_id: self aliases: [Search Engine Optimization, Organic Search] duplicate_of: none source_trust_level: A confidence_score: 0.9 verification_status: applied tags: [seo, web, core-web-vitals, ai-overviews, technical-seo] raw_sources: [] last_reinforced: 2026-05-10 github_commit: pending tech_stack: language: HTML framework: Next.js 15 --- # SEO ## 매 한 줄 > **"매 SEO 는 search engine 의 'helpful content' signal 에 align — 매 2026 은 Google AI Overviews + Perplexity + ChatGPT search 의 multi-engine 시대"**. 매 origin 은 1990s keyword stuffing; 매 modern state 는 E-E-A-T, Core Web Vitals, structured data, 그리고 매 GEO (Generative Engine Optimization) — LLM citation 을 target. ## 매 핵심 ### 매 3 layer - **Technical SEO**: crawlability, indexability, performance (Core Web Vitals: LCP, INP, CLS). - **Content SEO**: E-E-A-T (Experience, Expertise, Authoritativeness, Trust), search intent match. - **Off-page**: backlinks, brand mentions, citation in LLM training data. ### 매 2026 의 큰 변화 - **AI Overviews (Google SGE)**: 매 SERP top 의 LLM-generated summary — 매 "position 0". - **GEO (Generative Engine Optimization)**: 매 ChatGPT/Perplexity/Claude citation 을 target. - **Core Web Vitals**: INP (Interaction to Next Paint) ≤ 200ms, LCP ≤ 2.5s, CLS ≤ 0.1. - **Helpful content update**: 매 thin/AI-spam content demote. ### 매 응용 1. Organic traffic acquisition. 2. LLM citation (brand mention in ChatGPT answers). 3. Local SEO (Google Business Profile). 4. E-commerce product discovery. ## 💻 패턴 ### 매 Next.js 15 metadata API (App Router) ```tsx // app/blog/[slug]/page.tsx import type { Metadata } from "next"; export async function generateMetadata({ params }): Promise { const post = await getPost(params.slug); return { title: `${post.title} | Acme Blog`, description: post.excerpt.slice(0, 160), alternates: { canonical: `https://acme.com/blog/${params.slug}` }, openGraph: { title: post.title, description: post.excerpt, images: [post.coverImage], type: "article", publishedTime: post.publishedAt, authors: [post.author.name], }, twitter: { card: "summary_large_image" }, }; } ``` ### 매 JSON-LD structured data (Article) ```tsx export default function BlogPost({ post }) { const jsonLd = { "@context": "https://schema.org", "@type": "Article", headline: post.title, image: [post.coverImage], datePublished: post.publishedAt, dateModified: post.updatedAt, author: { "@type": "Person", name: post.author.name, url: post.author.url }, publisher: { "@type": "Organization", name: "Acme", logo: { "@type": "ImageObject", url: "https://acme.com/logo.png" }, }, }; return ( <>