Shopify 블로그 자동화: 키워드 목록 기반 SEO/AEO 최적화 문서
고급
이것은Content Creation, Multimodal AI분야의자동화 워크플로우로, 32개의 노드를 포함합니다.주로 If, Set, Code, Merge, HttpRequest 등의 노드를 사용하며. 사용GPT-4와Google 스프레드시트로 SEO/AEO 최적화된 Shopify 블로그 기사 생성
사전 요구사항
- •대상 API의 인증 정보가 필요할 수 있음
- •Google Sheets API 인증 정보
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
"id": "fpun8HUSy6VdVm9l",
"meta": {
"instanceId": "8e9162e70be518ca153a70a16d8785f5bfc6523821e135712fb7ef93fe97a5dd",
"templateCredsSetupCompleted": true
},
"name": "Shopify Blog on autopilot: SEO/AEO-optimized articles from a keyword List",
"tags": [],
"nodes": [
{
"id": "f5411ac3-3df5-4d11-8458-81fd89b11874",
"name": "수동 트리거",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-384,
48
],
"parameters": {},
"typeVersion": 1
},
{
"id": "62f498a7-861e-4264-ad79-30be7945957d",
"name": "일정 트리거",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-384,
-144
],
"parameters": {
"rule": {
"interval": [
{
"field": "cronExpression",
"expression": "0 9 * * 2,5"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "4c86423b-5357-4e8d-84cb-96e8491ace80",
"name": "Shopify: Create Article (REST)",
"type": "n8n-nodes-base.httpRequest",
"position": [
992,
592
],
"parameters": {
"url": "=https://{{$items('Set - Config')[0].json.shopDomain}}/admin/api/{{$items('Set - Config')[0].json.shopApiVersion}}/blogs/{{$items('Set - Config')[0].json.blogId}}/articles.json",
"method": "POST",
"options": {},
"jsonBody": "={{ JSON.stringify({\n article: {\n title: $('Code - Sanitize + pick non-conflicting slug').item.json.title,\n handle: $('Code - Sanitize + pick non-conflicting slug').item.json.slug,\n author: $items('Set - Config')[0].json.author || 'Equipo',\n tags: ($('Code - Sanitize + pick non-conflicting slug').item.json.tags || []).join(', '),\n summary_html: $('Code - Sanitize + pick non-conflicting slug').item.json.summary,\n body_html: $('Code - Sanitize + pick non-conflicting slug').item.json.content_html,\n published: $items('Set - Config')[0].json.autoPublish === 'true' || $items('Set - Config')[0].json.autoPublish === true,\n image: $json.data[0].b64_json\n ? {\n attachment: $json.data[0].b64_json,\n alt: $('Code - Sanitize + pick non-conflicting slug').item.json.image_alt\n }\n : null\n }\n}) }}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "2sKJ6R3gCnrct0e3",
"name": "Shopify Admin Token"
}
},
"typeVersion": 4.2
},
{
"id": "ff02026b-1083-47de-83cc-4809ecce14fb",
"name": "Build Article GID",
"type": "n8n-nodes-base.code",
"position": [
1200,
592
],
"parameters": {
"jsCode": "const id = $input.first().json.article.id;\nif (!id) throw new Error('No article.id returned');\nreturn [{ json: { ...$input, articleId: id, articleGid: `gid://shopify/Article/${id}` } }];"
},
"typeVersion": 2
},
{
"id": "eae2f1a4-9a71-422e-846d-ef9db7c7885b",
"name": "Shopify: metafields설정 (GraphQL)",
"type": "n8n-nodes-base.httpRequest",
"position": [
1392,
592
],
"parameters": {
"url": "=https://{{$items('Set - Config')[0].json.shopDomain}}/admin/api/{{$items('Set - Config')[0].json.shopApiVersion}}/graphql.json",
"method": "POST",
"options": {},
"jsonBody": "={\n \"query\": \"mutation metafieldsSet($metafields: [MetafieldsSetInput!]!) { metafieldsSet(metafields: $metafields) { metafields { id key value } userErrors { field message } } }\",\n \"variables\": {\n \"metafields\": [\n {\n \"ownerId\": \"{{$json.articleGid}}\",\n \"namespace\": \"global\",\n \"key\": \"title_tag\",\n \"type\": \"single_line_text_field\",\n \"value\": \"{{ $('Code - Sanitize + pick non-conflicting slug').item.json.seo_title }}\"\n },\n {\n \"ownerId\": \"{{$json.articleGid}}\",\n \"namespace\": \"global\",\n \"key\": \"description_tag\",\n \"type\": \"single_line_text_field\",\n \"value\": \"{{ $('Code - Sanitize + pick non-conflicting slug').item.json.seo_description }}\"\n }\n ]\n }\n}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "2sKJ6R3gCnrct0e3",
"name": "Shopify Admin Token"
}
},
"typeVersion": 4.2
},
{
"id": "7db3c0c6-06c7-4812-9b4e-b7f37218e0a3",
"name": "메모",
"type": "n8n-nodes-base.stickyNote",
"position": [
224,
-688
],
"parameters": {
"width": 720,
"height": 880,
"content": "## Google sheets structure\n* Create a Google Sheet with 3 tabs: Keywords, Links, Published\n* Keywords tab:\n** A: Keyword\n** B: Cluster (pillar/topic group)\n** C: Intent (informational / transactional / navigational)\n** D: volume_sum (sum of volume for this keyword from Semrush or other similar websites)\n** E: difficulty_avg (difficulty for this keyword from Semrush or other similar websites)\n** F: Priority (1–5)\n* Links tab (for internal linking within the articles): \n** A: URL (absolute URL)\n** C: Keywords (keywords that can be linked to the url)\n* Published tab (to keep track of published article): \n** A Datetime\n** B Keyword\n** C Cluster\n** D Title\n** E Slug\n** F URL\n** G Status (false if unpublished/true if published)"
},
"typeVersion": 1
},
{
"id": "4c0bdb78-5bdd-429a-aed8-5b1de72f8b6a",
"name": "메모1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-192,
-688
],
"parameters": {
"color": 3,
"width": 400,
"height": 880,
"content": "## CONFIG\n**Important** to edit the config with your information.\nVariables that **YOU MUST** edit:\n* shopDomain=your-store.myshopify.com\n* siteBaseUrl=https://your-domain (if you have one) or https://your-store.myshopify.com\n* blogHandle= the blog handle is just the slug after /blogs/\n* author: which author you want to use to publish the article.\n* sheetId=<YOUR_SHEET_ID>\n\nVariables that you can leave as they are:\n* shopApiVersion=2025-07\n* tz=Europe/Madrid\n* lang=en-EN\n* maxPerRun=1 (how many articles to write per run)\n* autoPublish=false (creating a draft -> change to true if you want to publish directly)"
},
"typeVersion": 1
},
{
"id": "6da08969-64a5-487d-969b-ed6567b08687",
"name": "Sheets - Read Keywords",
"type": "n8n-nodes-base.googleSheets",
"position": [
272,
-240
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Keywords"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.sheetId }}"
},
"authentication": "serviceAccount"
},
"credentials": {
"googleApi": {
"id": "IakWbbx0a4c1W8qa",
"name": "Google Service Account account"
}
},
"typeVersion": 4.7
},
{
"id": "ddf9b47b-16fa-40b6-8b64-f675bef27de8",
"name": "Sheets - Read Links",
"type": "n8n-nodes-base.googleSheets",
"position": [
272,
48
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Links"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set - Config').item.json.sheetId }}"
},
"authentication": "serviceAccount"
},
"credentials": {
"googleApi": {
"id": "IakWbbx0a4c1W8qa",
"name": "Google Service Account account"
}
},
"executeOnce": false,
"typeVersion": 4.7
},
{
"id": "4885986d-2d2f-4335-9ff2-1ae727b64206",
"name": "Sheets - Read Published",
"type": "n8n-nodes-base.googleSheets",
"position": [
272,
-96
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Published"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set - Config').item.json.sheetId }}"
},
"authentication": "serviceAccount"
},
"credentials": {
"googleApi": {
"id": "IakWbbx0a4c1W8qa",
"name": "Google Service Account account"
}
},
"executeOnce": false,
"typeVersion": 4.7
},
{
"id": "a5706020-9dc0-4b8c-804f-85167d6dff33",
"name": "코드 - Normalize Inputs",
"type": "n8n-nodes-base.code",
"position": [
752,
-96
],
"parameters": {
"jsCode": "/**\n * Buckets:\n * - Keywords (keywords/keyword, cluster, intent, priority, volume_sum?, difficulty_avg?)\n * - Published (Datetime, Keyword, Cluster, Title, Slug/Handle, URL, Status)\n *\n * Output:\n * {\n * keywords: [{ keyword, cluster, intent, priority, volume_sum?, difficulty_avg?, slug }],\n * published: {\n * slugs: string[],\n * clusters: string[],\n * slugToUrl: { [slug]: url },\n * pairs: string[] // \"keyword||cluster\" normalized\n * }\n * }\n */\n\nconst toAscii = (s='') =>\n String(s).normalize('NFD').replace(/[\\u0300-\\u036f]/g,'').replace(/ñ/gi,'n');\n\nconst toSlug = (s='') => toAscii(String(s).toLowerCase())\n .replace(/[^a-z0-9\\s-]/g,'')\n .trim().replace(/\\s+/g,'-').replace(/-+/g,'-')\n .slice(0,65).replace(/-+$/,'');\n\nconst isHttp = (s='') => /^https?:\\/\\//i.test(String(s||'').trim());\n\nconst lcKeys = (obj={}) => {\n const out = {};\n for (const [k,v] of Object.entries(obj)) out[String(k).toLowerCase()] = v;\n return out;\n};\n\n// normalized pair helpers\nconst norm = (s='') =>\n toAscii(String(s).toLowerCase().trim().replace(/\\s+/g,' '));\nconst pairKey = (k, c) =>\n `${norm(k)}||${norm(c || '(unclustered)')}`;\n\n// Collect all merged rows\nconst rows = $input.all().map(i => i.json).filter(Boolean);\n\n// Buckets\nconst kwRows = [];\nconst pubRows = [];\n\n// Classify rows; explicitly ignore Links rows\nfor (const r0 of rows) {\n const r = lcKeys(r0);\n if (!Object.values(r).some(v => String(v||'').trim())) continue;\n\n // IGNORE Links rows (Key + URL [+ Anchor])\n if (r.key && r.url && isHttp(r.url)) { continue; }\n\n // Published: has a slug (or handle) and either URL or Title or Keyword\n if ((r.slug || r.handle) && (r.url || r.title || r.keyword || r.keywords)) { pubRows.push(r); continue; }\n\n // Keywords: has 'keywords' or 'keyword' column\n if (r.keywords || r.keyword) { kwRows.push(r); continue; }\n\n // Fallbacks (conservative): ignore rows that only have URL\n if (isHttp(r.url)) { continue; }\n}\n\n// --- Normalize Keywords ---\nconst seen = new Set(); // de-dupe identical keyword->slug rows\nconst keywords = [];\nfor (const r of kwRows) {\n const keyword = String(r.keywords ?? r.keyword ?? '').trim();\n if (!keyword) continue;\n\n const clusterRaw = String(r.cluster ?? '').trim();\n const cluster = clusterRaw || '(unclustered)';\n const intent = String(r.intent ?? 'informational').trim();\n\n const pRaw = String(r.priority ?? r.prioridad ?? '3').trim();\n const pNum = parseInt(pRaw, 10);\n const priority = Math.min(5, Math.max(1, Number.isFinite(pNum) ? pNum : 3));\n\n const volNum = Number(r.volume_sum ?? r.volume);\n const kdNum = Number(r.difficulty_avg ?? r.difficulty ?? r.kd);\n const volume_sum = Number.isFinite(volNum) ? volNum : undefined;\n const difficulty_avg = Number.isFinite(kdNum) ? kdNum : undefined;\n\n const slug = toSlug(keyword);\n if (!slug || seen.has(slug)) continue;\n seen.add(slug);\n\n keywords.push({ keyword, cluster, intent, priority, volume_sum, difficulty_avg, slug });\n}\n\n// --- Normalize Published ---\nconst slugs = new Set();\nconst clusters = new Set();\nconst slugToUrl = {};\nconst pairs = new Set();\n\nfor (const r of pubRows) {\n const slug = String((r.slug ?? r.handle ?? '')).trim().toLowerCase();\n if (slug) {\n slugs.add(slug);\n if (isHttp(r.url)) slugToUrl[slug] = String(r.url).trim();\n }\n\n const clCell = String(r.cluster ?? '').trim();\n if (clCell) clusters.add(toSlug(clCell));\n\n // Build (keyword, cluster) pair if the Published sheet includes them\n const kwCell = String((r.keyword ?? r.keywords ?? '')).trim();\n if (kwCell) {\n pairs.add(pairKey(kwCell, clCell || '(unclustered)'));\n }\n}\n\n// Emit consolidated item (no Links)\nreturn [{\n json: {\n keywords,\n published: {\n slugs: Array.from(slugs),\n clusters: Array.from(clusters),\n slugToUrl,\n pairs: Array.from(pairs)\n }\n }\n}];"
},
"typeVersion": 2
},
{
"id": "3c1b2333-12c8-4c9f-a154-f13897e33f61",
"name": "병합",
"type": "n8n-nodes-base.merge",
"position": [
544,
-96
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "d62e4586-c8de-4dbc-80c7-96c37ab035d6",
"name": "코드 - Pick Candidate",
"type": "n8n-nodes-base.code",
"position": [
1120,
-96
],
"parameters": {
"jsCode": "const data = $input.first().json;\nconst cfg = ($items('Set - Config')[0] || { json: {} }).json;\n\n// settings\nconst maxPerRun = Math.max(1, parseInt(cfg.maxPerRun ?? '1', 10));\nconst onePerCluster = true;\nconst avoidPublishedClusters = false;\n\n// helpers\nconst num = (v,d=0)=>{ const n=Number(v); return Number.isFinite(n)?n:d; };\nconst toAscii = s=>String(s||'').normalize('NFD').replace(/[\\u0300-\\u036f]/g,'').replace(/ñ/gi,'n');\nconst norm = s=>toAscii(String(s).toLowerCase().trim().replace(/\\s+/g,' '));\nconst pairKey = (k,c)=>`${norm(k)}||${norm(c||'(unclustered)')}`;\nconst lc = s=>String(s||'').toLowerCase();\n\n// lookups (from Normalize)\nconst publishedPairs = new Set((data.published?.pairs || []).map(String));\nconst publishedClusters = new Set((data.published?.clusters || []).map(lc));\n\n// eligible (dedupe by keyword+cluster)\nconst seenPairs = new Set();\nlet candidates = [];\nfor (const k of (data.keywords || [])) {\n if (!k || !k.keyword) continue;\n const pKey = pairKey(k.keyword, k.cluster);\n if (publishedPairs.has(pKey)) continue;\n if (seenPairs.has(pKey)) continue;\n seenPairs.add(pKey);\n candidates.push(k);\n}\n\n// optional: avoid clusters that already have content\nif (avoidPublishedClusters) {\n candidates = candidates.filter(k => !publishedClusters.has(lc(k.cluster)));\n}\n\n// sort: priority (5 best) → volume desc → difficulty asc → keyword A→Z\ncandidates.sort((a,b)=>{\n const pa=num(a.priority,3), pb=num(b.priority,3);\n if (pa!==pb) return pb-pa;\n const va=num(a.volume_sum??a.volume,0), vb=num(b.volume_sum??b.volume,0);\n if (va!==vb) return vb-va;\n const da=num(a.difficulty_avg??a.difficulty??a.kd,999), db=num(b.difficulty_avg??b.difficulty??b.kd,999);\n if (da!==db) return da-db;\n return String(a.keyword||'').localeCompare(String(b.keyword||''));\n});\n\n// pick up to maxPerRun, one-per-cluster if enabled\nconst picks=[], seenClusters=new Set();\nfor (const k of candidates) {\n if (picks.length>=maxPerRun) break;\n const ck = lc(k.cluster||'(unclustered)');\n if (onePerCluster && seenClusters.has(ck)) continue;\n picks.push(k); seenClusters.add(ck);\n}\n\nif (!picks.length) return [{ json:{ skip:true, reason:'No eligible keywords after (keyword,cluster) dedupe.' }}];\nreturn picks.map(p=>({ json:p }));"
},
"typeVersion": 2
},
{
"id": "4144bece-9034-4d44-986a-d79c1acc9559",
"name": "Shopify - List Article Slugs",
"type": "n8n-nodes-base.httpRequest",
"position": [
1664,
-96
],
"parameters": {
"url": "=https://{{$items('Set - Config')[0].json.shopDomain}}/admin/api/{{$items('Set - Config')[0].json.shopApiVersion}}/graphql.json",
"method": "POST",
"options": {
"response": {
"response": {
"fullResponse": true,
"responseFormat": "json"
}
}
},
"jsonBody": "={{ JSON.stringify({\n query: \"query getArticles($id: ID!, $after: String){ node(id:$id){ ... on Blog { id handle articles(first:250, after:$after){ edges{ node{ id handle } } pageInfo{ hasNextPage endCursor } } } } }\",\n variables: Object.assign(\n { id: `gid://shopify/Blog/${$items('Set - Config')[0].json.blogId}` },\n $json.__cursor ? { after: $json.__cursor } : {}\n )\n}) }}\n",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpBearerAuth": {
"id": "lA5pPKE4T8YORtpH",
"name": "Bearer Auth account"
},
"httpHeaderAuth": {
"id": "2sKJ6R3gCnrct0e3",
"name": "Shopify Admin Token"
}
},
"typeVersion": 4.2
},
{
"id": "ad70b29e-ae77-4bb8-ab6b-0ce1bf23d18c",
"name": "설정 - Config",
"type": "n8n-nodes-base.set",
"position": [
-48,
-64
],
"parameters": {
"values": {
"number": [
{
"name": "maxPerRun",
"value": 1
}
],
"string": [
{
"name": "shopDomain"
},
{
"name": "siteBaseUrl"
},
{
"name": "blogId"
},
{
"name": "blogHandle"
},
{
"name": "tz",
"value": "Europe/Madrid"
},
{
"name": "lang",
"value": "en-EN"
},
{
"name": "shopApiVersion",
"value": "2025-07"
},
{
"name": "autoPublish",
"value": "false"
},
{
"name": "sheetId"
},
{
"name": "author"
}
]
},
"options": {}
},
"typeVersion": 2
},
{
"id": "4d99e350-ac86-4128-96d1-3e827a6a4b92",
"name": "If - More pages?",
"type": "n8n-nodes-base.if",
"position": [
2112,
-96
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "24406e83-c21f-4a0a-948b-c80e3581d54e",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.__hasNext === true }}",
"rightValue": "="
}
]
}
},
"typeVersion": 2.2
},
{
"id": "7dc7d93d-af2b-4c77-884a-7f4cb70f79cf",
"name": "메모2",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
-288
],
"parameters": {
"color": 5,
"width": 400,
"height": 480,
"content": "## Pick a candidate\nPick a keyword/cluster based on priority, volume and difficulty. It takes keywords with highest priority first."
},
"typeVersion": 1
},
{
"id": "15ab76cc-350d-4b6b-930b-c061b16ccb3a",
"name": "코드 - Init Slug Parser",
"type": "n8n-nodes-base.code",
"position": [
1440,
-96
],
"parameters": {
"jsCode": "return [{\n json: {\n existingSlugs: [],\n __cursor: null\n }\n}];"
},
"typeVersion": 2
},
{
"id": "bf9c87ee-9494-445a-9645-407de7a2b2e0",
"name": "코드 - Accumulate Slugs + Cursor",
"type": "n8n-nodes-base.code",
"position": [
1904,
-96
],
"parameters": {
"jsCode": "// 1) Get prior state from the SAME item (if present)\nconst list = Array.isArray($json.existingSlugs) ? $json.existingSlugs.slice() : [];\nconst seen = new Set(list.map(s => String(s).toLowerCase()));\n\n// 2) Read Shopify response from body.*\nconst edges = $json.body?.data?.node?.articles?.edges || [];\nconst pageInfo = $json.body?.data?.node?.articles?.pageInfo || {};\n\n// 3) Accumulate unique handles\nfor (const e of edges) {\n const h = String(e?.node?.handle || '').trim().toLowerCase();\n if (h && !seen.has(h)) {\n seen.add(h);\n list.push(h);\n }\n}\n\n// 4) Emit updated state for the loop\nreturn [{\n json: {\n existingSlugs: list,\n __cursor: pageInfo?.hasNextPage ? pageInfo?.endCursor : null,\n __hasNext: !!pageInfo?.hasNextPage,\n countAccumulated: list.length\n }\n}];"
},
"typeVersion": 2
},
{
"id": "c1d53448-4627-4954-9881-e623f9c41d3b",
"name": "메모3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1376,
-288
],
"parameters": {
"width": 960,
"height": 480,
"content": "## Pipeline to make a list of already used slugs from the shopify blog\nThis is a process to make a list of already used slugs so that in the next step, it doesn't create a slug already in use. "
},
"typeVersion": 1
},
{
"id": "945286fe-135f-46ac-aaca-bebc8429fe14",
"name": "코드 - Build Prompt",
"type": "n8n-nodes-base.code",
"position": [
16,
592
],
"parameters": {
"jsCode": "const all = $input.all();\n\n// 1) Existing slugs\nconst existingSlugs = (all.find(i => i.json.existingSlugs) || { json: { existingSlugs: [] } }).json.existingSlugs;\n\n// 2) Keyword data\nconst kwItem = all.find(i => i.json.keyword) || { json: {} };\nconst kw = kwItem.json.keyword || '';\nconst cluster = kwItem.json.cluster || '';\nconst intent = kwItem.json.intent || '';\n\n// 3) Candidate internal links\nconst links = (all.find(i => i.json.links) || { json: { links: [] } }).json.links || [];\n\n// --- PROMPT (system + user) ---\nconst system = `You are a team composed of a senior editor (English, en-EN), and an SEO/AEO expert.\nYou write for humans (E-E-A-T): clear and useful, without fluff or exaggeration.\nDo not use first person or testimonials. Use a neutral, respectful, and didactic tone.\nUse sentence case in ALL content: titles (title, seo_title, H1, H2, H3), paragraphs, and image alt text, with capitalization only at the beginning of the sentence and for proper nouns or acronyms (e.g., SEO, AEO, HTML).\nDo not use Title Case or ALL CAPS for common words.\nDo not use semicolons (;) or double dashes (--). Replace them with a period or comma as appropriate.`;\n\n// --- NEW BLOCK: internal link policy ---\nconst internalLinkPolicy = `\n### Internal linking (evaluation and use)\n- I give you a list of internal links with their associated keywords:\n${JSON.stringify(links, null, 2)}\n- Goal: **insert exactly 1 (one) internal link** in the article **only if** it is relevant.\n- Minimum relevance: there is a clear semantic match between the target keyword (\"${kw}\"), the cluster (\"${cluster}\"), the article content or its sections, and the keywords associated with the link.\n- Selection preferences:\n - Direct keyword match > partial match > thematic relation.\n- Insertion:\n - Place the link **inside an existing paragraph**, naturally (not at the beginning or end of the article).\n - Use a **descriptive and natural anchor** (not \"click here\").\n - Insert **only that link** with the tag <a href=\"...\">…</a>. Do not add more links or invent URLs.\n - Do not repeat the same URL more than once.\n- If **no link is clearly relevant**, **do not insert any**.\n`;\n\n// --- Your original user prompt + additions ---\nconst user = `\nWrite **ONE** SEO- and AEO-optimized article about the keyword: \"${kw}\".\nCluster: ${cluster}. Search intent: ${intent}. Language: English (en-EN).\nAvoid repeating slugs already used in the blog: [${existingSlugs.join(', ')}].\n\n${internalLinkPolicy}\n\nReturn ONLY JSON in this exact shape:\n{\n \"title\": string,\n \"slug\": string, // kebab-case ascii, ≤65, NOT included in [${existingSlugs.slice(0,50).join(', ')}]\n \"backup_slugs\": string[], // 2–4 valid and free alternatives\n \"seo_title\": string, // ≤70\n \"seo_description\": string, // ≤160\n \"tags\": string[], // 3–8\n \"content_html\": string, // ONLY: h2,h3,p,ul,ol,li,a,strong,em,blockquote,code,pre\n \"resumen\": string, // will appear on the blog home\n \"image_prompt\": string, // brief for hero image, without overlay text\n \"image_alt\": string, // ≤120 chars\n \"internal_link_used\": { // NEW — meta for control\n \"url\": string | null, // URL used or null if no relevant link\n \"anchor\": string | null, // anchor text used or null\n \"reason\": string | null // brief justification of relevance or null\n }\n}\n\n### Hard rules (comply with all):\n- Start with a **Direct Answer** block (35–60 words) that responds to the user’s intent without digressions.\n- **Structure**: H2/H3 by intent (informational: definition → usefulness → how to apply it → common mistakes → FAQs; comparative: criteria → alternatives → pros/cons → FAQs).\n- **SEO/AEO**: the keyword appears in the first 100 words and in an H2 (without over-optimizing); use synonyms and related entities naturally.\n- **Length**: ≥900 words unless the keyword is clearly short.\n- **Lists** scannable; short paragraphs (≤4 lines).\n- content_html must not contain <h1>\n- **Internal links**:\n - Keep your 3–6 **suggested internal anchors** (anchor text without URL, as already indicated).\n - **Additionally** apply the internal link policy above to insert **exactly 1** <a href=\"real URL\"> inside a paragraph, **only if** there is clear relevance. If not, insert none.\n- **Language**: avoid absolutes and unnecessary jargon; briefly define technical terms.\n- Sentence case in titles and text.\n- Do not use ';' or '--'.\n\n### Validations before returning JSON (do not show them):\n- Wordcount ≥900 approx. in body.\n- Character limits ok.\n- Valid, unique slug not similar to those given.\n- Keyword present in the first 100 words and an H2.\n- 3–6 suggested internal anchors inside paragraphs (without URL).\n- **If 'internal_link_used.url' is not null**:\n - 'content_html' contains **exactly one** occurrence of that URL as <a href=\"...\">…</a>.\n - There is no other different URL.\n- **If 'internal_link_used.url' is null**:\n - 'content_html' does not contain any <a href=\"http\".\n- Sentence case and no ';' or '--'.\n`;\n\nreturn [{\n json: {\n messages: [\n { role: 'system', content: system },\n { role: 'user', content: user }\n ],\n response_format: { type: 'json_object' }\n }\n}];\n"
},
"typeVersion": 2
},
{
"id": "980b1d19-816f-4556-a082-d734a65b0868",
"name": "OpenAI - Chat Completions",
"type": "n8n-nodes-base.httpRequest",
"position": [
240,
592
],
"parameters": {
"url": "https://api.openai.com/v1/chat/completions",
"method": "POST",
"options": {},
"jsonBody": "={{ JSON.stringify({\n model: \"gpt-4o-mini\",\n temperature: 0.5,\n response_format: $json.response_format,\n messages: $json.messages\n}) }}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "V3HO9ZNvIwrMeJ2f",
"name": "OpenAI n8n workflow"
}
},
"typeVersion": 4.2
},
{
"id": "7048dcfd-b13e-420e-805b-571213d55c66",
"name": "코드 - Sanitize + pick non-conflicting slug",
"type": "n8n-nodes-base.code",
"position": [
464,
592
],
"parameters": {
"jsCode": "const existing = new Set($('Merge - Wiring').first().json.existingSlugs.map(s => String(s).toLowerCase()));\nconst resp = $input.first().json;\nlet ai;\ntry { ai = JSON.parse(resp.choices?.[0]?.message?.content || \"{}\"); } catch { throw new Error(\"LLM JSON inválido\"); }\n\nconst keep = /(\\/?)(h1|h2|h3|p|ul|ol|li|a|strong|em|blockquote|code|pre)(\\s+[^>]*)?>/i;\nconst clean = (html=\"\") => html.replace(/<[^>]+>/g, t => keep.test(t) ? t : \"\");\n\nconst toAscii = s => s.normalize('NFD').replace(/[\\u0300-\\u036f]/g,'').replace(/ñ/gi,'n');\nconst toSlug = s => toAscii(String(s||'').toLowerCase())\n .replace(/[^a-z0-9\\s-]/g,'').trim().replace(/\\s+/g,'-').replace(/-+/g,'-').slice(0,65).replace(/-+$/,'');\nconst cut = (s,n)=>{s=String(s||'');return s.length<=n?s:s.slice(0,n-1).replace(/\\s+\\S*$/,'')+'…';};\n\nconst preferSlug = (s, backups=[]) => {\n let cand = toSlug(s);\n if (!existing.has(cand)) return cand;\n for (const b of backups) {\n const bs = toSlug(b);\n if (bs && !existing.has(bs)) return bs;\n }\n // suffix fallback\n let i = 2;\n while (i < 10) {\n const tryS = (cand + '-' + i).slice(0,65);\n if (!existing.has(tryS)) return tryS;\n i++;\n }\n return cand; // last resort\n};\n\nconst title = cut(ai.title || \"\", 90);\nconst slug = preferSlug(ai.slug || ai.title, Array.isArray(ai.backup_slugs) ? ai.backup_slugs : []);\nconst seo_title = cut(ai.seo_title || title, 70);\nconst seo_description = cut(ai.seo_description || \"\", 160);\nconst summary = ai.resumen;\nlet html = clean(ai.content_html || \"\");\n\n// Ensure single H1\nif (!/<h1>/i.test(html)) html = `<h1>${title}</h1>` + html;\n\n\nreturn [{\n json: {\n title, slug, seo_title, seo_description, summary, \n tags: Array.isArray(ai.tags) ? ai.tags.slice(0,8) : [],\n content_html: html,\n image_prompt: String(ai.image_prompt || ''),\n image_alt: cut(ai.image_alt || '', 120),\n existingSlugs: Array.from(existing),\n blogHandle: $('Set - Config').first().json.blogHandle\n }\n}];\n"
},
"typeVersion": 2
},
{
"id": "a072d4af-4421-4c72-8a65-f85c9d195c33",
"name": "HTTP Request - OpenAI Images (Hero)",
"type": "n8n-nodes-base.httpRequest",
"position": [
720,
592
],
"parameters": {
"url": "https://api.openai.com/v1/images/generations",
"method": "POST",
"options": {},
"jsonBody": "={{ JSON.stringify({\n model: \"gpt-image-1\",\n prompt: `${$json.image_prompt}`,\n size: \"1536x1024\",\n n: 1\n}) }}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "V3HO9ZNvIwrMeJ2f",
"name": "OpenAI n8n workflow"
}
},
"typeVersion": 4.2
},
{
"id": "932eb48e-a0e7-43cd-b45b-f5ab0e38889b",
"name": "병합 - Wiring",
"type": "n8n-nodes-base.merge",
"position": [
1728,
208
],
"parameters": {
"numberInputs": 3
},
"typeVersion": 3.2
},
{
"id": "726c102b-8cc4-48d0-9adc-b65a6d42911b",
"name": "메모4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-32,
432
],
"parameters": {
"color": 4,
"width": 944,
"height": 432,
"content": "## Prepare the article with OpenAI to get the content and the hero image"
},
"typeVersion": 1
},
{
"id": "2fc47ec6-f572-47c2-a5db-eaaa6e176612",
"name": "메모5",
"type": "n8n-nodes-base.stickyNote",
"position": [
944,
432
],
"parameters": {
"color": 6,
"width": 592,
"height": 432,
"content": "## Create shopify article and update metafields for SEO"
},
"typeVersion": 1
},
{
"id": "55d9c6f3-9577-420e-abd5-ca5bb6939897",
"name": "메모6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1584,
416
],
"parameters": {
"color": 3,
"width": 608,
"height": 448,
"content": "## Update to Google Sheets\n* Update the \"Published\" tab to keep track of keywords that were already used.\n* Update the \"Links\" tab, so that in the next articles, this link can be used for internal linking."
},
"typeVersion": 1
},
{
"id": "dcc2314f-d7dd-4789-9318-6d70a2a67346",
"name": "Append row to \"Published\" tab",
"type": "n8n-nodes-base.googleSheets",
"position": [
1776,
528
],
"parameters": {
"columns": {
"value": {
"URL": "=/{{ $('Code - Sanitize + pick non-conflicting slug').item.json.slug }}",
"Slug": "={{ $('Code - Sanitize + pick non-conflicting slug').item.json.slug }}",
"Title": "={{ $('Code - Sanitize + pick non-conflicting slug').item.json.title }}",
"Status": "={{$items('Set - Config')[0].json.autoPublish}}",
"Cluster": "={{ $('Code - Pick Candidate').first().json.cluster }}",
"Keyword": "={{ $('Code - Pick Candidate').first().json.keyword }}",
"Datetime": "={{ $('Build Article GID').item.json.context.response.body.article.created_at }}"
},
"schema": [
{
"id": "Datetime",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Datetime",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Keyword",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Keyword",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Cluster",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Cluster",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Title",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Slug",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Slug",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "URL",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "URL",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Status",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Status",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Published"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "={{$items('Set - Config')[0].json.sheetId}}"
},
"authentication": "serviceAccount"
},
"credentials": {
"googleApi": {
"id": "IakWbbx0a4c1W8qa",
"name": "Google Service Account account"
}
},
"typeVersion": 4.7
},
{
"id": "fb03a884-40fb-4622-8bed-a110616af897",
"name": "코드 - List of links for article",
"type": "n8n-nodes-base.code",
"position": [
1120,
208
],
"parameters": {
"jsCode": "return [\n {\n json: {\n links: items.map(item => ({\n url: item.json.URL,\n keywords: item.json.Keywords.split(\",\").map(k => k.trim())\n }))\n }\n }\n];"
},
"typeVersion": 2
},
{
"id": "90f2c446-cad7-4249-b115-43db941fefb7",
"name": "Append row to \"Links\" tab",
"type": "n8n-nodes-base.googleSheets",
"position": [
1776,
704
],
"parameters": {
"columns": {
"value": {
"URL": "=/{{ $('Build Article GID').item.json.context.response.body.article.handle }}",
"Keywords": "={{ $('Code - Pick Candidate').first().json.keyword }}"
},
"schema": [
{
"id": "URL",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "URL",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Keywords",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Keywords",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "name",
"value": "Links"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set - Config').first().json.sheetId }}"
},
"authentication": "serviceAccount"
},
"credentials": {
"googleApi": {
"id": "IakWbbx0a4c1W8qa",
"name": "Google Service Account account"
}
},
"typeVersion": 4.7
},
{
"id": "5b24d0c3-6850-4020-9650-02525a971fce",
"name": "메모7",
"type": "n8n-nodes-base.stickyNote",
"position": [
-448,
-256
],
"parameters": {
"height": 272,
"content": "There is a cron to run the process each Tuesday and Friday at 9AM."
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"callerPolicy": "workflowsFromSameOwner",
"errorWorkflow": "ib0LqomNsNIqEoi6",
"executionOrder": "v1"
},
"versionId": "3928abaa-6112-4e63-a760-569ebcc3a448",
"connections": {
"Merge": {
"main": [
[
{
"node": "Code - Normalize Inputs",
"type": "main",
"index": 0
}
]
]
},
"Set - Config": {
"main": [
[
{
"node": "6da08969-64a5-487d-969b-ed6567b08687",
"type": "main",
"index": 0
},
{
"node": "ddf9b47b-16fa-40b6-8b64-f675bef27de8",
"type": "main",
"index": 0
},
{
"node": "4885986d-2d2f-4335-9ff2-1ae727b64206",
"type": "main",
"index": 0
}
]
]
},
"Manual Trigger": {
"main": [
[
{
"node": "Set - Config",
"type": "main",
"index": 0
}
]
]
},
"Merge - Wiring": {
"main": [
[
{
"node": "Code - Build Prompt",
"type": "main",
"index": 0
}
]
]
},
"4d99e350-ac86-4128-96d1-3e827a6a4b92": {
"main": [
[
{
"node": "4144bece-9034-4d44-986a-d79c1acc9559",
"type": "main",
"index": 0
}
],
[
{
"node": "Merge - Wiring",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Set - Config",
"type": "main",
"index": 0
}
]
]
},
"ff02026b-1083-47de-83cc-4809ecce14fb": {
"main": [
[
{
"node": "Shopify: metafieldsSet (GraphQL)",
"type": "main",
"index": 0
}
]
]
},
"Code - Build Prompt": {
"main": [
[
{
"node": "980b1d19-816f-4556-a082-d734a65b0868",
"type": "main",
"index": 0
}
]
]
},
"ddf9b47b-16fa-40b6-8b64-f675bef27de8": {
"main": [
[
{
"node": "Code - List of links for article",
"type": "main",
"index": 0
}
]
]
},
"Code - Pick Candidate": {
"main": [
[
{
"node": "Code - Init Slug Parser",
"type": "main",
"index": 0
},
{
"node": "Merge - Wiring",
"type": "main",
"index": 1
}
]
]
},
"6da08969-64a5-487d-969b-ed6567b08687": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 0
}
]
]
},
"Code - Init Slug Parser": {
"main": [
[
{
"node": "4144bece-9034-4d44-986a-d79c1acc9559",
"type": "main",
"index": 0
}
]
]
},
"Code - Normalize Inputs": {
"main": [
[
{
"node": "Code - Pick Candidate",
"type": "main",
"index": 0
}
]
]
},
"4885986d-2d2f-4335-9ff2-1ae727b64206": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"90f2c446-cad7-4249-b115-43db941fefb7": {
"main": [
[]
]
},
"980b1d19-816f-4556-a082-d734a65b0868": {
"main": [
[
{
"node": "Code - Sanitize + pick non-conflicting slug",
"type": "main",
"index": 0
}
]
]
},
"4144bece-9034-4d44-986a-d79c1acc9559": {
"main": [
[
{
"node": "Code - Accumulate Slugs + Cursor",
"type": "main",
"index": 0
}
]
]
},
"4c86423b-5357-4e8d-84cb-96e8491ace80": {
"main": [
[
{
"node": "ff02026b-1083-47de-83cc-4809ecce14fb",
"type": "main",
"index": 0
}
]
]
},
"Code - Accumulate Slugs + Cursor": {
"main": [
[
{
"node": "4d99e350-ac86-4128-96d1-3e827a6a4b92",
"type": "main",
"index": 0
}
]
]
},
"Code - List of links for article": {
"main": [
[
{
"node": "Merge - Wiring",
"type": "main",
"index": 2
}
]
]
},
"Shopify: metafieldsSet (GraphQL)": {
"main": [
[
{
"node": "90f2c446-cad7-4249-b115-43db941fefb7",
"type": "main",
"index": 0
},
{
"node": "dcc2314f-d7dd-4789-9318-6d70a2a67346",
"type": "main",
"index": 0
}
]
]
},
"a072d4af-4421-4c72-8a65-f85c9d195c33": {
"main": [
[
{
"node": "4c86423b-5357-4e8d-84cb-96e8491ace80",
"type": "main",
"index": 0
}
]
]
},
"Code - Sanitize + pick non-conflicting slug": {
"main": [
[
{
"node": "a072d4af-4421-4c72-8a65-f85c9d195c33",
"type": "main",
"index": 0
}
]
]
}
}
}자주 묻는 질문
이 워크플로우를 어떻게 사용하나요?
위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.
이 워크플로우는 어떤 시나리오에 적합한가요?
고급 - 콘텐츠 제작, 멀티모달 AI
유료인가요?
이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.
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