Bright Data と Gemini AI を使用して SEO 最適化されたタイトルとメタディスクリプションを生成
上級
これはMarket Research, Multimodal AI分野の自動化ワークフローで、16個のノードを含みます。主にSet, HttpRequest, GoogleSheets, ManualTrigger, SplitInBatchesなどのノードを使用。 Bright DataとGemini AIを使ってSEO最適化されたタイトルとメタディスクリプションを生成する
前提条件
- •ターゲットAPIの認証情報が必要な場合あり
- •Google Sheets API認証情報
- •Google Gemini API Key
使用ノード (16)
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"meta": {
"instanceId": "db80165df40cb07c0377167c050b3f9ab0b0fb04f0e8cae0dc53f5a8527103ca",
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "63865e5c-9e83-49ad-8d51-02391ee9e36c",
"name": "ワークフロー実行時",
"type": "n8n-nodes-base.manualTrigger",
"position": [
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],
"parameters": {},
"typeVersion": 1
},
{
"id": "e935f831-25e0-4325-b0a4-72dd632c6c46",
"name": "Google検索結果の取得JSON",
"type": "n8n-nodes-base.httpRequest",
"onError": "continueErrorOutput",
"position": [
-816,
480
],
"parameters": {
"url": "https://api.brightdata.com/request",
"method": "POST",
"options": {
"batching": {
"batch": {}
},
"redirect": {
"redirect": {}
}
},
"sendBody": true,
"sendQuery": true,
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "zone",
"value": "serp_api1"
},
{
"name": "url",
"value": "=https://www.google.com/search?q={{ $json.search_term .replaceAll(\" \", \"+\")}}&start=0&brd_json=1"
},
{
"name": "country",
"value": "={{ $json['country code'] }}"
},
{
"name": "format",
"value": "raw"
}
]
},
"genericAuthType": "httpHeaderAuth",
"queryParameters": {
"parameters": [
{
"name": "async",
"value": "true"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "Accept",
"value": "application/json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "gfLRVcGG09VEZv5B",
"name": "Brightdata Header"
}
},
"typeVersion": 4.2,
"alwaysOutputData": true
},
{
"id": "ee4881f0-9148-493e-825e-ce2dde83fbae",
"name": "キーワード取得",
"type": "n8n-nodes-base.googleSheets",
"position": [
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],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QU9rwawCZLiYW8nlYYRMj-9OvAUNZoe2gP49KbozQqw/edit#gid=0",
"cachedResultName": "Keywords to Track"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1QU9rwawCZLiYW8nlYYRMj-9OvAUNZoe2gP49KbozQqw",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QU9rwawCZLiYW8nlYYRMj-9OvAUNZoe2gP49KbozQqw/edit?usp=drivesdk",
"cachedResultName": "Position Tracking for Keyword + Dashboard "
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "ZAI2a6Qt80kX5a9s",
"name": "Google Sheets account✅ "
}
},
"typeVersion": 4.6
},
{
"id": "69fff95a-24de-4331-89a8-14d4ea25c066",
"name": "アイテムのループ処理",
"type": "n8n-nodes-base.splitInBatches",
"position": [
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],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "9b6c4df9-90af-431a-9d85-54ea38c49155",
"name": "Google Geminiチャットモデル",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
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],
"parameters": {
"options": {}
},
"credentials": {
"googlePalmApi": {
"id": "Xp5T9q3YYxBIw2nd",
"name": "Google Gemini(PaLM) Api account✅"
}
},
"typeVersion": 1
},
{
"id": "4f164104-6881-4636-b238-d75c7d52f866",
"name": "新規タイトルとメタディスクリプション生成",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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],
"parameters": {
"text": "=You are an advanced SEO strategist and content optimization engine.\n\nYour task is to:\n1. Analyze the list of top-ranking page titles and meta descriptions for a given keyword.\n2. Infer common SEO patterns, content structure, and user search intent.\n3. Use these insights to generate a highly optimized new **Title** and **Meta Description** that:\n - Aligns with the dominant SERP format\n - Matches search intent\n - Stands out enough to drive clicks (CTR-optimized)\n - Includes the target keyword naturally\n - Sounds trustworthy, relevant, and modern\n\n---\n\n### Input Keyword:\n{{ $('set keyword').item.json.search_term }}\n### Top SERP Results (Titles + Descriptions):\n{{ $json.titlesDescriptions }}\n\n### \"People Also Ask\" Questions:\n{{ $json.paaQuestions }}\n\n---\n\n### Output Format:\n{\n \"intent\": \"[Label the dominant search intent. Examples: Listicle, How-to, Informational, Commercial, Review, Product Page, Case Study, etc.]\",\n \"dominant_patterns\": {\n \"title_structure\": \"[Respond only with the generalized pattern using placeholders. No full sentences. No explanations.]\",\n \"meta_structure\": \"[Respond only with the generalized meta pattern using placeholders. No full sentences. No explanations.]\"\n},\n \"optimized_title\": \"[SEO-optimized title for the keyword]\",\n \"optimized_meta\": \"[Well-written meta description under 160 characters]\",\n \"cta\": \"[Optional call-to-action if helpful]\"\n}\n",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2
},
{
"id": "d150f732-b580-430b-9a2d-d225b73839f9",
"name": "構造化出力パーサー1",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
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],
"parameters": {
"jsonSchemaExample": "{\n \"intent\": \"[Label the dominant search intent. Examples: Listicle, How-to, Informational, Commercial, Review, Product Page, Case Study, etc.]\",\n \"dominant_patterns\": {\n \"title_structure\": \"[Respond only with the generalized pattern using placeholders. No full sentences. No explanations.]\",\n \"meta_structure\": \"[Respond only with the generalized meta pattern using placeholders. No full sentences. No explanations.]\"\n},\n \"optimized_title\": \"[SEO-optimized title for the keyword]\",\n \"optimized_meta\": \"[Well-written meta description under 160 characters]\",\n \"cta\": \"[Optional call-to-action if helpful]\"\n}"
},
"typeVersion": 1.3
},
{
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"name": "メタ構造",
"type": "n8n-nodes-base.set",
"position": [
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],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "660979bb-be4d-4551-b15a-1963b9c1b4d1",
"name": "Keyword",
"type": "string",
"value": "={{ $('Loop Over Items').item.json.search_term }}"
},
{
"id": "334b8afd-d8ae-4b75-8f03-3f9315870268",
"name": "intent",
"type": "string",
"value": "={{ $json.output.intent }}"
},
{
"id": "b2f9402c-7f22-4081-b5ac-494c6a3f9869",
"name": "dominant_patterns - meta_structure",
"type": "string",
"value": "={{ $json.output.dominant_patterns.meta_structure }}"
},
{
"id": "018ce0e2-5af2-40df-adc5-2ab1d8977d05",
"name": "dominant_patterns - title_structure",
"type": "string",
"value": "={{ $json.output.dominant_patterns.title_structure }}"
},
{
"id": "6890732d-c773-4254-bb3d-2acdcab32ef2",
"name": "optimized_title",
"type": "string",
"value": "={{ $json.output.optimized_title }}"
},
{
"id": "99ef63dc-c8e3-48e5-8d29-9c7019b019b2",
"name": "optimized_meta",
"type": "string",
"value": "={{ $json.output.optimized_meta }}"
},
{
"id": "d4768bd4-23c0-4bf1-8e88-51c21e314cf9",
"name": "cta",
"type": "string",
"value": "={{ $json.output.cta }}"
}
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}
},
"typeVersion": 3.4
},
{
"id": "b1271960-96c0-48a4-9bd6-07325b0ea5e1",
"name": "新規メタと構造の作成",
"type": "n8n-nodes-base.googleSheets",
"position": [
112,
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],
"parameters": {
"columns": {
"value": {},
"schema": [
{
"id": "Keyword",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Keyword",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "country code",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "country code",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "domain",
"type": "string",
"display": true,
"required": false,
"displayName": "domain",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "page",
"type": "string",
"display": true,
"required": false,
"displayName": "page",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Position",
"type": "string",
"display": true,
"required": false,
"displayName": "Position",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "intent",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "intent",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "dominant_patterns - meta_structure",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "dominant_patterns - meta_structure",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "dominant_patterns - title_structure",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "dominant_patterns - title_structure",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "optimized_title",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "optimized_title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "optimized_meta",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "optimized_meta",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "CTA",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "CTA",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "cta",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "cta",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "autoMapInputData",
"matchingColumns": [
"Keyword"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QU9rwawCZLiYW8nlYYRMj-9OvAUNZoe2gP49KbozQqw/edit#gid=0",
"cachedResultName": "Keywords to Track"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1QU9rwawCZLiYW8nlYYRMj-9OvAUNZoe2gP49KbozQqw",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QU9rwawCZLiYW8nlYYRMj-9OvAUNZoe2gP49KbozQqw/edit?usp=drivesdk",
"cachedResultName": "Position Tracking for Keyword + Dashboard "
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "ZAI2a6Qt80kX5a9s",
"name": "Google Sheets account✅ "
}
},
"typeVersion": 4.6
},
{
"id": "70796069-27d9-4076-8936-e5ec75ab42e8",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
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384
],
"parameters": {
"width": 980,
"height": 504,
"content": "## Analyze title and meta description formats for top 10 pages"
},
"typeVersion": 1
},
{
"id": "ad89de82-a005-4851-8c40-102b83f3c912",
"name": "付箋4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1584,
384
],
"parameters": {
"width": 200,
"height": 320,
"content": "- Make a copy of this [G sheet](https://docs.google.com/spreadsheets/d/1QU9rwawCZLiYW8nlYYRMj-9OvAUNZoe2gP49KbozQqw/edit?usp=sharing)\n\n- Add your desired keywords"
},
"typeVersion": 1
},
{
"id": "571a1981-a9f3-4b66-8c9f-3d4779425df6",
"name": "付箋5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1344,
288
],
"parameters": {
"color": 5,
"width": 200,
"height": 340,
"content": "- We loop over each item one at a time"
},
"typeVersion": 1
},
{
"id": "5b39d950-56e9-4069-81f0-8a061a56795d",
"name": "キーワード設定",
"type": "n8n-nodes-base.set",
"position": [
-1008,
480
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "cee3c6fe-dc44-43b2-9243-a1f1a62f9fa1",
"name": "search_term",
"type": "string",
"value": "={{ $json.Keyword }}"
},
{
"id": "3c58a493-6d15-4b90-bc5a-154d6f6d6474",
"name": "country code",
"type": "string",
"value": "={{ $json['country code'] }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "72f54c66-32df-45a4-8b1d-84a02cc7c4b8",
"name": "付箋6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1024,
400
],
"parameters": {
"color": 4,
"width": 340,
"height": 320,
"content": "- Map keyword and country code \n- Update the Zone name to match your zone on Bright Data\n- Run the scraper"
},
"typeVersion": 1
},
{
"id": "49eb27cd-0ced-498d-a85e-92c0928847a4",
"name": "キーワードのマッピング",
"type": "n8n-nodes-base.set",
"position": [
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],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "4a5b9b7c-184e-4269-bee1-36684b1c99fc",
"name": "titlesDescriptions",
"type": "array",
"value": "={{ $json.organic.map(item => ({ title: item.title, description: item.description })) }}"
},
{
"id": "27ae3f27-d185-4ef0-8aaa-7e65c87fa6f2",
"name": "paaQuestions",
"type": "array",
"value": "={{ $json.people_also_ask.map(item => item.question )}}"
},
{
"id": "cd6102fa-8c47-44ca-b302-53b52dcaeb4f",
"name": "search_term",
"type": "string",
"value": "={{ $('set keyword').item.json.search_term }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "ae34e2d9-17ec-4013-a1cc-1ed7b1adfcae",
"name": "操作なし（何もしない）1",
"type": "n8n-nodes-base.noOp",
"position": [
-784,
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],
"parameters": {},
"typeVersion": 1
}
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"pinData": {},
"connections": {
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"9b6c4df9-90af-431a-9d85-54ea38c49155": {
"ai_languageModel": [
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"type": "ai_languageModel",
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}
]
]
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"type": "ai_outputParser",
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"e935f831-25e0-4325-b0a4-72dd632c6c46": {
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}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
上級 - 市場調査, マルチモーダルAI
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
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ワークフロー情報
難易度
上級
ノード数16
カテゴリー2
ノードタイプ10
作成者
Zacharia Kimotho
@imperolqAutomation expert with years of experience helping businesses improve their efficiency and productivity with smart automations that are affordable, scalable, and flexible.
外部リンク
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