18 購買トレンドを分析する
中級
これはMarket Research, AI Summarization分野の自動化ワークフローで、15個のノードを含みます。主にGoogleSheets, McpClientTool, ManualTrigger, Agent, LmChatOpenAiなどのノードを使用。 Amazonの購入傾向をBright Data、OpenAI、Google Sheetsで分析する
前提条件
- •Google Sheets API認証情報
- •OpenAI API Key
使用ノード (15)
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": "FtPQQBuZOQRWsWkH",
"meta": {
"instanceId": "60046904b104f0f72b2629a9d88fe9f676be4035769f1f08dad1dd38a76b9480",
"templateCredsSetupCompleted": true
},
"name": "18 Analyze Purchase Trends",
"tags": [],
"nodes": [
{
"id": "1ab29609-739c-4f42-b398-d40e275d2531",
"name": "ワークフロー実行時",
"type": "n8n-nodes-base.manualTrigger",
"position": [
0,
0
],
"parameters": {},
"typeVersion": 1
},
{
"id": "a4117e05-67bc-42be-ba31-4b75be46ef9f",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
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],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "8sEyPDkC5p4w4Jha",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "99c92ba4-9af0-4808-8f5a-5729ab7c922b",
"name": "Google SheetsからAmazon URLを取得",
"type": "n8n-nodes-base.googleSheets",
"position": [
220,
0
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12ouaPrMp5HEKKctEhVmjmIBVSFu75P4NFFe20XKH9mM/edit#gid=0",
"cachedResultName": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "12ouaPrMp5HEKKctEhVmjmIBVSFu75P4NFFe20XKH9mM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12ouaPrMp5HEKKctEhVmjmIBVSFu75P4NFFe20XKH9mM/edit?usp=drivesdk",
"cachedResultName": "Product purchase trends"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "r2mDaisH6e9VkwHl",
"name": "Google Sheets account"
}
},
"typeVersion": 4.6
},
{
"id": "a9a77a78-e60c-4329-ba4a-697c806bbf5c",
"name": "Amazon商品分析 (AIエージェント)",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
500,
0
],
"parameters": {
"text": "=extract the unit sold, current price, stock availability, review count & rating, sales rank and based on it's purchasing performance give it rating out of 10.\nBelow is the url of the amazon product:\n{{ $json.url }}",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2
},
{
"id": "353646b6-e2cb-42fd-aa8d-9d3c1693ef25",
"name": "Tool: MCP Client (Bright Data)",
"type": "n8n-nodes-mcp.mcpClientTool",
"position": [
660,
260
],
"parameters": {
"toolName": "web_data_amazon_product",
"operation": "executeTool",
"toolParameters": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Tool_Parameters', ``, 'json') }}"
},
"credentials": {
"mcpClientApi": {
"id": "eqq94k789oJCd6jU",
"name": "MCP Client (STDIO) account"
}
},
"typeVersion": 1
},
{
"id": "8ef0d68c-c9f6-4fda-8421-318da2875715",
"name": "商品インサイトでシートを更新",
"type": "n8n-nodes-base.googleSheets",
"position": [
1040,
0
],
"parameters": {
"columns": {
"value": {
"Ranking": "={{ $json.output[0].performance_rating }}",
"Sales rank": "={{ $json.output[0].sales_rank }}",
"Units sold": "={{ $json.output[0].units_sold_last_month }}",
"row_number": "={{ $('Fetch Amazon URLs from Google Sheets').item.json.row_number }}",
"Current price": "={{ $json.output[0].current_price }}",
"Stock availability": "={{ $json.output[0].stock_status }}",
"Review count & rating": "={{ $json.output[0].review_count }} & {{ $json.output[0].rating }}"
},
"schema": [
{
"id": "url",
"type": "string",
"display": true,
"required": false,
"displayName": "url",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Units sold",
"type": "string",
"display": true,
"required": false,
"displayName": "Units sold",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Current price",
"type": "string",
"display": true,
"required": false,
"displayName": "Current price",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Stock availability",
"type": "string",
"display": true,
"required": false,
"displayName": "Stock availability",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Review count & rating",
"type": "string",
"display": true,
"required": false,
"displayName": "Review count & rating",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Sales rank",
"type": "string",
"display": true,
"required": false,
"displayName": "Sales rank",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Ranking",
"type": "string",
"display": true,
"required": false,
"displayName": "Ranking",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "row_number",
"type": "string",
"display": true,
"removed": false,
"readOnly": true,
"required": false,
"displayName": "row_number",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"row_number"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "update",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12ouaPrMp5HEKKctEhVmjmIBVSFu75P4NFFe20XKH9mM/edit#gid=0",
"cachedResultName": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "12ouaPrMp5HEKKctEhVmjmIBVSFu75P4NFFe20XKH9mM",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12ouaPrMp5HEKKctEhVmjmIBVSFu75P4NFFe20XKH9mM/edit?usp=drivesdk",
"cachedResultName": "Product purchase trends"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "r2mDaisH6e9VkwHl",
"name": "Google Sheets account"
}
},
"typeVersion": 4.6
},
{
"id": "f2b27f36-4860-4b98-8dac-1ca89192d7a4",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
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-620
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"parameters": {
"color": 5,
"width": 420,
"height": 820,
"content": "### 🔹 **SECTION 1: Trigger & Read Product URLs**\n\n**Nodes Combined:**\n\n* `Start Workflow (Manual Trigger)`\n* `Fetch Amazon URLs from Google Sheets`\n\n📌 **What Happens Here:**\nWhen you click **\"Execute workflow\"**, the automation kicks off. It reads a list of Amazon product URLs from a connected **Google Sheet** — each URL representing a product you want to analyze.\n\n🧠 **Why This Is Useful:**\nYou don't have to input product links manually every time. Just **paste your URLs in the Google Sheet**, and this step will automatically fetch them all. Perfect for monitoring dozens (or hundreds) of products.\n\n📋 **Fields Expected in Google Sheet:**\n\n* `URL` (Amazon product link)\n* *(Other columns will be auto-filled later)*\n\n🔧 **Icons Involved:**\n\n* ⚡ `Trigger`\n* 📄 `Google Sheets`\n\n---\n\n"
},
"typeVersion": 1
},
{
"id": "20d538a0-6bec-4e2f-9d53-55a10c7f2236",
"name": "付箋1",
"type": "n8n-nodes-base.stickyNote",
"position": [
460,
-1120
],
"parameters": {
"color": 3,
"width": 340,
"height": 1320,
"content": "### 🤖 **SECTION 2: AI Agent + Scraper + Parser**\n\n**Node: `Amazon Product Analyzer (AI Agent)` + Sub-nodes:**\n\n* `OpenAI Chat Model`\n* `MCP Client (Bright Data)`\n* `Structured Output Parser`\n\n📌 **What Happens Here:**\n\n1. 🔍 The **AI Agent** passes each product URL to:\n\n * 🛰️ The **MCP Client**, which uses **Bright Data's Mobile Carrier Proxy** to scrape data safely from Amazon (bypassing detection).\n * 📊 The **data collected** includes:\n\n * Units sold last month\n * Current price\n * Stock availability\n * Review count\n * Average rating\n * Sales rank\n\n2. 💬 Then, the **OpenAI Chat Model** intelligently evaluates this data and gives a **performance rating out of 10**, simulating a product analyst's decision-making.\n\n3. 📦 Finally, the **Structured Output Parser** transforms the AI’s natural language response into **clean JSON fields** that n8n can write back to your Google Sheet.\n\n🧠 **Why This Is Useful:**\nThis section automates **competitive product research**, letting you know which products are worth stocking, promoting, or avoiding — without manually checking every listing.\n\n🛠️ **Icons Involved:**\n\n* 🤖 AI Agent\n* 🧠 OpenAI Chat\n* 🌐 MCP Scraper (Bright Data)\n* 📤 JSON Parser\n\n---\n\n"
},
"typeVersion": 1
},
{
"id": "d6bd1b54-2b77-490f-acf8-001c94affccd",
"name": "付箋2",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
-720
],
"parameters": {
"color": 6,
"width": 260,
"height": 920,
"content": "### 📈 **SECTION 3: Update Google Sheet with Final Data**\n\n**Node: `Update Sheet with Product Insights`**\n\n📌 **What Happens Here:**\nOnce scraping and AI evaluation are done, the workflow **updates the original Google Sheet** with all the new fields:\n\n| Column | Description |\n| ----------------------- | -------------------------------------------------- |\n| `Units Sold` | Estimated number of units sold in the last 30 days |\n| `Current Price` | Latest listed price on Amazon |\n| `Stock Availability` | Whether product is in stock, and how many units |\n| `Review Count & Rating` | Total reviews and average rating |\n| `Sales Rank` | Rank in overall and subcategory |\n| `Performance Rating` | AI-generated score out of 10 based on all factors |\n\n"
},
"typeVersion": 1
},
{
"id": "c696695f-78b4-4baf-83b6-7939311bf1b0",
"name": "付箋5",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 7,
"width": 380,
"height": 240,
"content": "## I’ll receive a tiny commission if you join Bright Data through this link—thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25"
},
"typeVersion": 1
},
{
"id": "67d803eb-9a83-4fcd-8c73-e3f0f5bf6285",
"name": "付箋9",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 4,
"width": 1300,
"height": 320,
"content": "=======================================\n WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n - YouTube: https://www.youtube.com/@YaronBeen/videos\n - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
},
"typeVersion": 1
},
{
"id": "adf14924-8511-4c24-878b-0c766f869ec0",
"name": "付箋4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1820,
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],
"parameters": {
"color": 4,
"width": 1289,
"height": 2298,
"content": "## 🚀 Amazon Product Performance Analyzer Workflow\n\n**Automate product research + scoring using AI, scraping, and Google Sheets.**\n\n---\n\n### 🔹 **SECTION 1: Trigger & Read Product URLs**\n\n**Nodes Combined:**\n\n* `Start Workflow (Manual Trigger)`\n* `Fetch Amazon URLs from Google Sheets`\n\n📌 **What Happens Here:**\nWhen you click **\"Execute workflow\"**, the automation kicks off. It reads a list of Amazon product URLs from a connected **Google Sheet** — each URL representing a product you want to analyze.\n\n🧠 **Why This Is Useful:**\nYou don't have to input product links manually every time. Just **paste your URLs in the Google Sheet**, and this step will automatically fetch them all. Perfect for monitoring dozens (or hundreds) of products.\n\n📋 **Fields Expected in Google Sheet:**\n\n* `URL` (Amazon product link)\n* *(Other columns will be auto-filled later)*\n\n🔧 **Icons Involved:**\n\n* ⚡ `Trigger`\n* 📄 `Google Sheets`\n\n---\n\n### 🤖 **SECTION 2: AI Agent + Scraper + Parser**\n\n**Node: `Amazon Product Analyzer (AI Agent)` + Sub-nodes:**\n\n* `OpenAI Chat Model`\n* `MCP Client (Bright Data)`\n* `Structured Output Parser`\n\n📌 **What Happens Here:**\n\n1. 🔍 The **AI Agent** passes each product URL to:\n\n * 🛰️ The **MCP Client**, which uses **Bright Data's Mobile Carrier Proxy** to scrape data safely from Amazon (bypassing detection).\n * 📊 The **data collected** includes:\n\n * Units sold last month\n * Current price\n * Stock availability\n * Review count\n * Average rating\n * Sales rank\n\n2. 💬 Then, the **OpenAI Chat Model** intelligently evaluates this data and gives a **performance rating out of 10**, simulating a product analyst's decision-making.\n\n3. 📦 Finally, the **Structured Output Parser** transforms the AI’s natural language response into **clean JSON fields** that n8n can write back to your Google Sheet.\n\n🧠 **Why This Is Useful:**\nThis section automates **competitive product research**, letting you know which products are worth stocking, promoting, or avoiding — without manually checking every listing.\n\n🛠️ **Icons Involved:**\n\n* 🤖 AI Agent\n* 🧠 OpenAI Chat\n* 🌐 MCP Scraper (Bright Data)\n* 📤 JSON Parser\n\n---\n\n### 📈 **SECTION 3: Update Google Sheet with Final Data**\n\n**Node: `Update Sheet with Product Insights`**\n\n📌 **What Happens Here:**\nOnce scraping and AI evaluation are done, the workflow **updates the original Google Sheet** with all the new fields:\n\n| Column | Description |\n| ----------------------- | -------------------------------------------------- |\n| `Units Sold` | Estimated number of units sold in the last 30 days |\n| `Current Price` | Latest listed price on Amazon |\n| `Stock Availability` | Whether product is in stock, and how many units |\n| `Review Count & Rating` | Total reviews and average rating |\n| `Sales Rank` | Rank in overall and subcategory |\n| `Performance Rating` | AI-generated score out of 10 based on all factors |\n\n📈 **Why This Is Useful:**\nNow your spreadsheet becomes a **live product intelligence dashboard**, perfect for:\n\n* 👨💼 Product managers deciding what to sell\n* 📦 Suppliers checking demand\n* 📊 Marketers picking hot products to promote\n\n🛠️ **Icon Involved:**\n\n* 📝 Google Sheets (Update Node)\n\n---\n\n## 💡 Final Outcome:\n\nYour workflow is now a **smart Amazon trend analyzer**, delivering:\n\n* 🔁 Repeated product evaluation at scale\n* ⏱️ Instant product scoring without manual research\n* 📊 Clean, structured data ready for decision-making\n\n---\n\n"
},
"typeVersion": 1
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{
"id": "14b5ab60-1fac-4728-8ab3-b52f3ef476cd",
"name": "Auto-fixing Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
"position": [
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"parameters": {
"options": {}
},
"typeVersion": 1
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{
"id": "312c6667-4ee1-4a44-85a5-99e612928451",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
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"parameters": {
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"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
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"credentials": {
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"name": "OpenAi account"
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"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
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"parameters": {
"jsonSchemaExample": "[\n {\n \"product_name\": \"UGREEN Revodok 105 USB-C Hub\",\n \"units_sold_last_month\": 8000,\n \"current_price\": 9.98,\n \"original_price\": 15.99,\n \"stock_status\": \"In Stock\",\n \"max_quantity_available\": 30,\n \"review_count\": 18381,\n \"rating\": 4.6,\n \"sales_rank\": {\n \"overall_category\": \"#11 in Computers & Accessories\",\n \"subcategory\": \"#2 in Laptop Docking Stations\"\n },\n \"performance_rating\": 9\n },\n {\n \"product_name\": \"Amazon Product (Unnamed)\",\n \"units_sold_last_month\": 7000,\n \"current_price\": 25.78,\n \"stock_status\": \"In Stock\",\n \"review_count\": 847,\n \"rating\": 4.7,\n \"sales_rank\": {\n \"overall_category\": \"#7 in Tablet Chargers & Adapters\"\n },\n \"performance_rating\": 8.5\n },\n {\n \"product_name\": \"UGREEN Power Bank 25,000mAh 145W Laptop Portable Charger\",\n \"seller\": \"UGREEN GROUP LIMITED\",\n \"units_sold_last_month\": 2000,\n \"current_price\": 69.99,\n \"original_price\": 99.99,\n \"discount_percent\": 30,\n \"stock_status\": \"In Stock\",\n \"review_count\": 3657,\n \"rating\": 4.4,\n \"sales_rank\": {\n \"overall_category\": \"#1,198 in Cell Phones & Accessories\",\n \"subcategory\": \"#105 in Cell Phone Portable Power Banks\"\n },\n \"performance_rating\": 8\n }\n]\n"
},
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"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "9c19383b-cabd-4530-8c1b-19eec6c6fb4a",
"connections": {
"a4117e05-67bc-42be-ba31-4b75be46ef9f": {
"ai_languageModel": [
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{
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"type": "ai_languageModel",
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"312c6667-4ee1-4a44-85a5-99e612928451": {
"ai_languageModel": [
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"a238a9f8-74ac-4a40-96fb-20c60f9b9dd9": {
"ai_outputParser": [
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{
"node": "14b5ab60-1fac-4728-8ab3-b52f3ef476cd",
"type": "ai_outputParser",
"index": 0
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"14b5ab60-1fac-4728-8ab3-b52f3ef476cd": {
"ai_outputParser": [
[
{
"node": "a9a77a78-e60c-4329-ba4a-697c806bbf5c",
"type": "ai_outputParser",
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"353646b6-e2cb-42fd-aa8d-9d3c1693ef25": {
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"a9a77a78-e60c-4329-ba4a-697c806bbf5c": {
"main": [
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"type": "main",
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"99c92ba4-9af0-4808-8f5a-5729ab7c922b": {
"main": [
[
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"node": "a9a77a78-e60c-4329-ba4a-697c806bbf5c",
"type": "main",
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"1ab29609-739c-4f42-b398-d40e275d2531": {
"main": [
[
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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？
中級 - 市場調査, AI要約
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
中級
ノード数15
カテゴリー2
ノードタイプ8
作成者
Yaron Been
@yaron-nofluffBuilding AI Agents and Automations | Growth Marketer | Entrepreneur | Book Author & Podcast Host If you need any help with Automations, feel free to reach out via linkedin: https://www.linkedin.com/in/yaronbeen/ And check out my Youtube channel: https://www.youtube.com/@YaronBeen/videos
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