Google SERPトラッカー+トレンドと推奨事項（Bright DataとGoogle Geminiを使用）
上級
これはAI, Marketing分野の自動化ワークフローで、23個のノードを含みます。主にSet, Code, HttpRequest, ConvertToFile, ManualTriggerなどのノードを使用、AI技術を活用したスマート自動化を実現。 Bright DataとGoogle Geminiを利用したGoogle検索結果ページの追跡、トレンド分析、レコメンデーション
前提条件
- •ターゲットAPIの認証情報が必要な場合あり
- •Google Gemini API Key
使用ノード (23)
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
{
"id": "77EZJT0bcpkDEigw",
"meta": {
"instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
"templateCredsSetupCompleted": true
},
"name": "Google SERP Tracker + Trends and Recommendations with Bright Data & Google Gemini",
"tags": [
{
"id": "Kujft2FOjmOVQAmJ",
"name": "Engineering",
"createdAt": "2025-04-09T01:31:00.558Z",
"updatedAt": "2025-04-09T01:31:00.558Z"
},
{
"id": "ZOwtAMLepQaGW76t",
"name": "Building Blocks",
"createdAt": "2025-04-13T15:23:40.462Z",
"updatedAt": "2025-04-13T15:23:40.462Z"
},
{
"id": "ddPkw7Hg5dZhQu2w",
"name": "AI",
"createdAt": "2025-04-13T05:38:08.053Z",
"updatedAt": "2025-04-13T05:38:08.053Z"
}
],
"nodes": [
{
"id": "89c87a2f-ee34-47e4-8efd-a4a95d02b052",
"name": "「Test workflow」クリック時",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-380,
-160
],
"parameters": {},
"typeVersion": 1
},
{
"id": "44ede7e3-f552-4a70-a538-9d124a4df315",
"name": "入力フィールド設定",
"type": "n8n-nodes-base.set",
"position": [
-120,
-160
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "0ac91db2-9848-40d4-b942-cd7288597ded",
"name": "url",
"type": "string",
"value": "https://www.google.com/search"
},
{
"id": "7142f0df-3c68-4ce0-8e9b-25101db31312",
"name": "webhook_notification_url",
"type": "string",
"value": "https://webhook.site/c9118da2-1c54-460f-a83a-e5131b7098db"
},
{
"id": "f5b7e10d-bcd8-439c-8e84-ba4af11f2cd2",
"name": "search",
"type": "string",
"value": "best crm for the year 2025"
},
{
"id": "3a0bcec2-ec6d-457f-87a5-b73f4d826b2a",
"name": "zone",
"type": "string",
"value": "web_unlocker1"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "adb4eb44-ae8b-4a5e-bab8-afbf5b91e2a2",
"name": "Bright Dataウェブリクエスト実行",
"type": "n8n-nodes-base.httpRequest",
"position": [
120,
-160
],
"parameters": {
"url": "https://api.brightdata.com/request",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "zone",
"value": "={{ $json.zone }}"
},
{
"name": "url",
"value": "={{ $json.url }}?q={{ encodeURI($json.search) }}"
},
{
"name": "format",
"value": "raw"
}
]
},
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "97f0a53c-81cb-4593-afde-d770547b88d0",
"name": "付箋4",
"type": "n8n-nodes-base.stickyNote",
"position": [
60,
-440
],
"parameters": {
"color": 5,
"width": 440,
"height": 240,
"content": "## LLM Usages\n\nGoogle Gemini LLM is being utilized for the structured data extraction handling."
},
"typeVersion": 1
},
{
"id": "ca10a555-a4ef-4a2b-8ad1-9abf0e02e2d8",
"name": "付箋5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-380,
-800
],
"parameters": {
"color": 7,
"width": 400,
"height": 340,
"content": "## Logo\n\n\n\n"
},
"typeVersion": 1
},
{
"id": "1ccd35b4-d56a-4c42-88a1-59453a344700",
"name": "付箋1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-380,
-440
],
"parameters": {
"width": 400,
"height": 240,
"content": "## Note\n\nDeals with the Google SERP Tracker by utilizing the Bright Data and Google Gemini LLM for transforming the profile into a structured JSON response.\n\n**Please make sure to set the input fields node with the filtering criteria, Bright Data zone name, Webhook notification URL**\n\nTest Webhook using - https://webhook.site/\n"
},
"typeVersion": 1
},
{
"id": "f9b7f382-4a5a-4ddf-a62c-ee83af913a21",
"name": "Google 検索データ抽出器",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
340,
-160
],
"parameters": {
"text": "=Extract the following:\n\nRank (position in list)\n\nTitle\n\nURL\n\nSnippet/description\n\nType (organic/ads/map)\n\n{{ $json.data }}\n\nMake sure to return the data in JSON",
"batching": {},
"promptType": "define",
"hasOutputParser": true
},
"retryOnFail": true,
"typeVersion": 1.7
},
{
"id": "f10a9a84-3e4c-4ac0-957e-7fc7308c9fda",
"name": "コード",
"type": "n8n-nodes-base.code",
"position": [
700,
-160
],
"parameters": {
"jsCode": "return $input.first().json.output.results"
},
"typeVersion": 2
},
{
"id": "d3621752-4837-4e6f-82af-953e98901b24",
"name": "アイテムループ処理",
"type": "n8n-nodes-base.splitInBatches",
"position": [
920,
-160
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "2f607774-34cf-4b0e-9384-f7214e0896e5",
"name": "トレンドデータ抽出器",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1180,
-140
],
"parameters": {
"text": "=Extract the trends based on the title and spippet:\n\nTitle : {{ $json.title }}\nSnippet : {{ $json.snippet }}\n\nMake sure to return the data in JSON",
"batching": {},
"promptType": "define",
"hasOutputParser": true
},
"retryOnFail": true,
"typeVersion": 1.7
},
{
"id": "551b645b-99d7-4824-ad69-290ea8105689",
"name": "Google 検索用 Gemini チャットモデル",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
340,
20
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "9bd32bc8-9452-4e6a-ac54-e3a1317d196e",
"name": "Google 検索用構造化出力パーサー",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
520,
20
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"$schema\": \"http://json-schema.org/schema#\",\n \"title\": \"Search Results Schema\",\n \"type\": \"object\",\n \"properties\": {\n \"results\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"required\": [\"rank\", \"title\", \"type\"],\n \"properties\": {\n \"rank\": {\n \"type\": \"integer\",\n \"minimum\": 1\n },\n \"title\": {\n \"type\": \"string\"\n },\n \"url\": {\n \"type\": \"string\",\n \"format\": \"uri\"\n },\n \"snippet\": {\n \"type\": \"string\"\n },\n \"type\": {\n \"type\": \"string\",\n \"enum\": [\"organic\", \"paid\", \"featured\"]\n }\n },\n \"additionalProperties\": false\n }\n }\n },\n \"required\": [\"results\"],\n \"additionalProperties\": false\n}\n"
},
"typeVersion": 1.2
},
{
"id": "06d01c21-4054-4879-a060-70c1a1bac559",
"name": "トレンドデータ用 Google Gemini チャットモデル",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1180,
40
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "7c89ac87-28b1-47f3-9f04-b2c05b1a483a",
"name": "レコメンデーションデータ抽出器",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1180,
-560
],
"parameters": {
"text": "=Provide recommendations based on the title and spippet:\n\nTitle : {{ $json.title }}\nSnippet : {{ $json.snippet }}\n\nMake sure to return the data in JSON",
"batching": {},
"promptType": "define",
"hasOutputParser": true
},
"retryOnFail": true,
"typeVersion": 1.7
},
{
"id": "f1f9cfac-28d0-40a9-9287-b11689570b53",
"name": "レコメンデーション用 Google Gemini チャットモデル",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1180,
-380
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
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"id": "YeO7dHZnuGBVQKVZ",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "c008d472-0982-4970-a017-73784c6916e7",
"name": "レコメンデーション用構造化出力パーサー",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1360,
-380
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"$schema\": \"https://json-schema.org/draft/2020-12/schema\",\n \"title\": \"CRM Recommendations Schema\",\n \"type\": \"object\",\n \"properties\": {\n \"recommendations\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"type\": {\n \"type\": \"string\",\n \"enum\": [\"Software\", \"Action\", \"Consideration\", \"Research\", \"Focus\"],\n \"description\": \"The category or nature of the recommendation\"\n },\n \"name\": {\n \"type\": \"string\",\n \"description\": \"The name\"\n },\n \"description\": {\n \"type\": \"string\",\n \"description\": \"Explanation or reason behind the recommendation\"\n },\n \"reason\": {\n \"type\": \"string\",\n \"description\": \"A detailed reason for recommendation (mainly used for Software type)\"\n }\n }\n }\n }\n },\n \"required\": [\"recommendations\"]\n}\n"
},
"typeVersion": 1.2
},
{
"id": "113b9477-cb62-47b9-8f43-f49247c7053d",
"name": "トレンドデータ用構造化出力パーサー",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1360,
40
],
"parameters": {
"schemaType": "manual",
"inputSchema": "{\n \"$schema\": \"https://json-schema.org/schema\",\n \"title\": \"Trends Schema\",\n \"type\": \"object\",\n \"properties\": {\n \"trends\": {\n \"type\": \"array\",\n \"items\": {\n \"type\": \"object\",\n \"properties\": {\n \"trend\": {\n \"type\": \"string\",\n \"description\": \"The name or label of the CRM trend\"\n },\n \"description\": {\n \"type\": \"string\",\n \"description\": \"A short explanation of the trend\"\n }\n },\n \"required\": [\"trend\", \"description\"],\n \"additionalProperties\": false\n }\n }\n },\n \"required\": [\"trends\"],\n \"additionalProperties\": false\n}\n"
},
"typeVersion": 1.2
},
{
"id": "6b6bb9f4-2836-469d-b81b-90cddf5d0d6c",
"name": "レコメンデーション用コード",
"type": "n8n-nodes-base.code",
"position": [
1580,
-560
],
"parameters": {
"jsCode": "return $input.first().json.output.recommendations"
},
"typeVersion": 2
},
{
"id": "cb71a4e9-55ff-4194-8e5c-be96f3971a4e",
"name": "トレンド用コード",
"type": "n8n-nodes-base.code",
"position": [
1600,
-140
],
"parameters": {
"jsCode": "return $input.first().json.output.trends"
},
"typeVersion": 2
},
{
"id": "bfdac6af-7fa9-42d9-8931-029291202a35",
"name": "トレンド用ファイル変換",
"type": "n8n-nodes-base.convertToFile",
"position": [
1840,
-140
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "28d26067-622b-4115-ab25-79bf8802acdd",
"name": "レコメンデーション用ファイル変換",
"type": "n8n-nodes-base.convertToFile",
"position": [
1820,
-560
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "0fb2daca-d998-432e-901a-001f750822db",
"name": "トレンド csv ファイルをディスクに書き込み",
"type": "n8n-nodes-base.readWriteFile",
"position": [
2080,
-140
],
"parameters": {
"options": {},
"fileName": "=d:\\Google_SERP_Trends_Response_{{ new Date().toISOString().replace(/[:.]/g, '-')}}.csv",
"operation": "write"
},
"typeVersion": 1
},
{
"id": "b0164de9-50a4-4aba-a680-a392eaba5765",
"name": "レコメンデーション csv ファイルをディスクに書き込み",
"type": "n8n-nodes-base.readWriteFile",
"position": [
2060,
-560
],
"parameters": {
"options": {},
"fileName": "=d:\\Google_SERP_Recommendations_Response_{{ new Date().toISOString().replace(/[:.]/g, '-')}}.csv",
"operation": "write"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "7842a7f6-ab16-42c6-a209-1f313ed15376",
"connections": {
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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 - 人工知能, マーケティング
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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26 ノードRanjan Dailata
人工知能
Bright Data を使用して Google Gemini で Etsy データをスクレイピングし自動化
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Split Out
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Split Out
19 ノードRanjan Dailata
プロダクト
DNB企業検索と抽出：Bright DataとOpenAI 4o miniを使用
Bright Data そして OpenAI 4o mini に基づく DNB 社検索と抽出
Set
Function
Mcp Client
+
Set
Function
Mcp Client
18 ノードRanjan Dailata
プロダクト
ワークフロー情報
難易度
上級
ノード数23
カテゴリー2
ノードタイプ11
作成者
Ranjan Dailata
@ranjancseA Professional based out of India specialized in handling AI-powered automations. Contact me at ranjancse@gmail.com
外部リンク
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