{ "workflow": { "id": 5966, "name": "Analyze & target high-value customers with GPT-4 and Bright Data MCP", "views": 428, "recentViews": 0, "totalViews": 428, "createdAt": "2025-07-13T19:02:15.762Z", "description": "*This workflow contains community nodes that are only compatible with the self-hosted version of n8n.*\n\nThis workflow automatically analyzes customer lifetime value (CLV) metrics to optimize customer acquisition and retention strategies. It saves you time by eliminating the need to manually calculate CLV and provides data-driven insights for maximizing customer profitability and improving business growth.\n\n## Overview\n\nThis workflow automatically scrapes customer data, purchase history, and engagement metrics to calculate and analyze customer lifetime value patterns. It uses Bright Data to access customer analytics platforms and AI to intelligently segment customers, predict CLV, and identify high-value customer characteristics.\n\n## Tools Used\n\n- **n8n**: The automation platform that orchestrates the workflow\n- **Bright Data**: For scraping customer analytics and CRM platforms without being blocked\n- **OpenAI**: AI agent for intelligent CLV analysis and customer segmentation\n- **Google Sheets**: For storing CLV calculations and customer analysis data\n\n## How to Install\n\n1. **Import the Workflow**: Download the .json file and import it into your n8n instance\n2. **Configure Bright Data**: Add your Bright Data credentials to the MCP Client node\n3. **Set Up OpenAI**: Configure your OpenAI API credentials\n4. **Configure Google Sheets**: Connect your Google Sheets account and set up your CLV analysis spreadsheet\n5. **Customize**: Define customer data sources and CLV calculation parameters\n\n## Use Cases\n\n- **Customer Success**: Focus retention efforts on high-value customers\n- **Marketing Strategy**: Optimize customer acquisition costs based on projected CLV\n- **Sales Teams**: Prioritize prospects with higher lifetime value potential\n- **Business Strategy**: Make data-driven decisions about customer investments\n\n## Connect with Me\n\n- **Website**: https://www.nofluff.online\n- **YouTube**: https://www.youtube.com/@YaronBeen/videos\n- **LinkedIn**: https://www.linkedin.com/in/yaronbeen/\n- **Get Bright Data**: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission)\n\n#n8n #automation #customerlifetimevalue #clv #customeranalytics #brightdata #webscraping #customerdata #n8nworkflow #workflow #nocode #customersegmentation #valueanalysis #customerinsights #revenueoptimization #customervalue #clvanalysis #customermetrics #customerprofitability #businessintelligence #customerretention #valueprediction #customeroptimization #revenueanalysis #customerstrategy #lifetimevalue #customerroi #valuedriven #customerworth #profitability", "workflow": { "id": "wIBHF1QNYzvZZHta", "meta": { "instanceId": "60046904b104f0f72b2629a9d88fe9f676be4035769f1f08dad1dd38a76b9480", "templateCredsSetupCompleted": true }, "name": "23 Analyze Customer Lifetime Value", "tags": [], "nodes": [ { "id": "a73dd3f9-4d76-46ba-b4bc-9c7035109825", "name": "Run Offer Campaign Monthly", "type": "n8n-nodes-base.scheduleTrigger", "position": [ 0, 0 ], "parameters": { "rule": { "interval": [ { "field": "months", "triggerAtHour": 9 } ] } }, "typeVersion": 1.2 }, { "id": "8b11a03a-71da-4d82-8891-084adcddfd77", "name": "Set customer history url", "type": "n8n-nodes-base.set", "position": [ 200, 0 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "b366b00a-ad35-46ab-9722-6478ded6ec91", "name": "customer data url", "type": "string", "value": "example.com" } ] } }, "typeVersion": 3.4 }, { "id": "b1f84ba5-90f9-4483-968e-67df657a1936", "name": "Scrape Customer Profiles & Orders (Agent)", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 480, 0 ], "parameters": { "text": "=scrape the customer history url below and extract the key information:\n{{ $json['customer data url'] }}", "options": {}, "promptType": "define", "hasOutputParser": true }, "typeVersion": 2 }, { "id": "5aced094-ac88-4033-8a9b-dfc7b1457a6d", "name": "Bright Data MCP Scraper", "type": "n8n-nodes-mcp.mcpClientTool", "position": [ 640, 280 ], "parameters": { "toolName": "scrape_as_markdown", "operation": "executeTool", "toolParameters": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Tool_Parameters', ``, 'json') }}" }, "credentials": { "mcpClientApi": { "id": "credential-id", "name": "mcpClientApi Credential" } }, "typeVersion": 1 }, { "id": "ef9b75c8-1ec6-43ca-9969-909146214422", "name": "AI Assistant", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 440, 280 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1.2 }, { "id": "2d7909b4-333c-46cc-9909-5df7fe9bdeb6", "name": "Format Customer Info", "type": "n8n-nodes-base.code", "position": [ 900, 0 ], "parameters": { "jsCode": "// Get the array inside the 'output' key\nconst customers = items[0].json.output;\n\n// Map each customer to a separate item\nreturn customers.map(customer => {\n return { json: customer };\n});\n" }, "typeVersion": 2 }, { "id": "8d562c3e-2e0c-4ba8-8dbe-a89a23ba913b", "name": "Get Customer Order History", "type": "n8n-nodes-base.code", "position": [ 1100, 0 ], "parameters": { "jsCode": "// Loop through all incoming customers\nconst output = [];\n\nfor (const item of items) {\n const customerName = item.json.customer_name;\n const customerEmail = item.json.customer_email; // Added email extraction\n const orders = item.json.orders;\n\n for (const order of orders) {\n output.push({\n json: {\n customer_name: customerName,\n customer_email: customerEmail, // Added email in output\n amount: order.amount,\n date: order.date\n }\n });\n }\n}\n\nreturn output;\n" }, "typeVersion": 2 }, { "id": "02a09456-b359-4989-99b5-c830e9d6ca2a", "name": "Is Customer High-Value?", "type": "n8n-nodes-base.if", "position": [ 1360, 0 ], "parameters": { "options": {}, "conditions": { "options": { "version": 2, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "6725053f-eae9-422c-942d-c82279482697", "operator": { "type": "number", "operation": "gte" }, "leftValue": "={{ $json.amount }}", "rightValue": 200 } ] } }, "typeVersion": 2.2 }, { "id": "9a0b0647-1341-4159-b639-5b3581548d74", "name": "Send Special Offer Email", "type": "n8n-nodes-base.gmail", "position": [ 1580, -100 ], "webhookId": "f2c94a4c-06f0-43a0-81db-8c728ef0de2f", "parameters": { "sendTo": "={{ $json.customer_email }}", "message": "write any offer", "options": {}, "subject": "Offer for being out ideal customer" }, "credentials": { "gmailOAuth2": { "id": "credential-id", "name": "gmailOAuth2 Credential" } }, "typeVersion": 2.1 }, { "id": "3d73fb01-ab20-4be2-97c7-c21d5c95b45f", "name": "Ignore Low-Value Customers", "type": "n8n-nodes-base.noOp", "position": [ 1580, 100 ], "parameters": {}, "typeVersion": 1 }, { "id": "7f81c4d2-d406-4d58-956e-78bca5a8f861", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ -40, -1020 ], "parameters": { "color": 2, "width": 400, "height": 1200, "content": "## ๐Ÿ” **Section 1: Schedule & Input Setup**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿ•’ `Run Offer Campaign Daily`**\n* **โœ๏ธ `Set Admin Dashboard URL`**\n\n### ๐Ÿ“– What Happens Here:\n\nThis section **initiates the workflow on a regular schedule** (daily, weekly, etc.). It also **sets the URL** of the **admin dashboard** where your customer data is stored.\n\n๐Ÿ’ก **Beginner Tip:**\nThis is your starting point. You don't need to manually run the workflow every time โ€” just schedule it, and it will run automatically using the trigger.\n\nโœ… **Why itโ€™s useful:**\nYou can run this process daily or weekly to find customers who deserve promotional offers, all on autopilot!\n\n---\n\n" }, "typeVersion": 1 }, { "id": "de0d7ee1-b627-4f17-b03e-4076b09166a9", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 440, -900 ], "parameters": { "color": 3, "width": 340, "height": 1080, "content": "## ๐Ÿค– **Section 2: Scraping Customer Data with Agent**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿค– `Scrape Customer Profiles & Orders (Agent)`**\n\n * โš™๏ธ **`AI Assistant (OpenAI Chat Model)`**\n * ๐ŸŒ **`Bright Data MCP Scraper`**\n * ๐Ÿงพ **`Format Agent Output (Structured Output Parser)`**\n\n### ๐Ÿ“– What Happens Here:\n\nThe **AI Agent** (powered by OpenAI and Bright Data MCP) accesses your dashboard and scrapes:\n\n* ๐Ÿ“‡ **Customer profiles**\n* ๐Ÿ›’ **Their purchase/order history**\n\nThe **Structured Output Parser** then **cleans up and organizes** this data into a format that other nodes can use.\n\n๐Ÿ’ก **Beginner Tip:**\nThis is like a smart assistant that goes to your admin dashboard, collects important info, and makes sure itโ€™s readable for the next steps.\n\nโœ… **Why itโ€™s useful:**\nEven if the data is messy or complex on the dashboard, this section makes sure itโ€™s clean and ready to use in your automation.\n\n---\n\n" }, "typeVersion": 1 }, { "id": "9f5db009-9461-4937-8c88-d55bf47bfe2c", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 860, -760 ], "parameters": { "color": 5, "width": 360, "height": 940, "content": "## ๐Ÿงฉ **Section 3: Data Formatting & Order Extraction**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿ”ง `Format Customer Info`**\n* **๐Ÿ“ฆ `Get Customer Order History`**\n\n### ๐Ÿ“– What Happens Here:\n\nThese function nodes further **organize and process the scraped data**:\n\n* The first node extracts key customer details like name, email, and ID.\n* The second node focuses on their **order data** โ€” how many items they bought, total amount spent, etc.\n\n๐Ÿ’ก **Beginner Tip:**\nThink of this as organizing data into two folders: ๐Ÿงโ€โ™‚๏ธ โ€œCustomer Infoโ€ and ๐Ÿ“Š โ€œPurchase Dataโ€.\n\nโœ… **Why itโ€™s useful:**\nClean separation of data means better targeting. You'll know exactly **who** bought **what**, and **how much** they spent โ€” perfect for personalized offers!\n\n---\n\n" }, "typeVersion": 1 }, { "id": "a46e5710-fb85-46d6-addd-211994597386", "name": "Sticky Note3", "type": "n8n-nodes-base.stickyNote", "position": [ 1320, -740 ], "parameters": { "color": 6, "width": 380, "height": 1000, "content": "## ๐ŸŽฏ **Section 4: Offer Decision & Action**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿ’ฐ `Is Customer High-Value?`**\n* **๐Ÿ“ง `Send Special Offer Email`**\n* **โžก๏ธ `Ignore Low-Value Customers`**\n\n### ๐Ÿ“– What Happens Here:\n\nThis section **decides what action to take**:\n\n* The \"High Value Check\" compares a customerโ€™s total spending against a fixed threshold.\n* If their spending is **high enough**, they get a personalized **offer email** via Gmail.\n* If not, theyโ€™re simply **skipped** โ€” no email is sent.\n\n๐Ÿ’ก **Beginner Tip:**\nYou donโ€™t want to send offers to everyone. This smart filter ensures **only loyal/high-value customers** get incentives.\n\n" }, "typeVersion": 1 }, { "id": "e32fb60f-390a-4f16-9b81-6b82fda08328", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ 1820, -740 ], "parameters": { "color": 7, "width": 380, "height": 240, "content": "## Iโ€™ll receive a tiny commission if you join Bright Data through this linkโ€”thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25" }, "typeVersion": 1 }, { "id": "a31f7eec-c104-4631-86f3-523e68aab57b", "name": "Sticky Note9", "type": "n8n-nodes-base.stickyNote", "position": [ -1780, -1040 ], "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": "0f4db4d3-102f-4c2c-a456-42bd14e95a76", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ -1780, -700 ], "parameters": { "color": 4, "width": 1289, "height": 2758, "content": "# ๐ŸŽฏ **Automated High-Value Customer Targeting & Offer Campaign**\n\n### *Smartly scrape, segment, and send personalized offers โ€” all without lifting a finger.*\n\n---\n\n## ๐Ÿ” **Section 1: Schedule & Input Setup**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿ•’ `Run Offer Campaign Daily`**\n* **โœ๏ธ `Set Admin Dashboard URL`**\n\n### ๐Ÿ“– What Happens Here:\n\nThis section **initiates the workflow on a regular schedule** (daily, weekly, etc.). It also **sets the URL** of the **admin dashboard** where your customer data is stored.\n\n๐Ÿ’ก **Beginner Tip:**\nThis is your starting point. You don't need to manually run the workflow every time โ€” just schedule it, and it will run automatically using the trigger.\n\nโœ… **Why itโ€™s useful:**\nYou can run this process daily or weekly to find customers who deserve promotional offers, all on autopilot!\n\n---\n\n## ๐Ÿค– **Section 2: Scraping Customer Data with Agent**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿค– `Scrape Customer Profiles & Orders (Agent)`**\n\n * โš™๏ธ **`AI Assistant (OpenAI Chat Model)`**\n * ๐ŸŒ **`Bright Data MCP Scraper`**\n * ๐Ÿงพ **`Format Agent Output (Structured Output Parser)`**\n\n### ๐Ÿ“– What Happens Here:\n\nThe **AI Agent** (powered by OpenAI and Bright Data MCP) accesses your dashboard and scrapes:\n\n* ๐Ÿ“‡ **Customer profiles**\n* ๐Ÿ›’ **Their purchase/order history**\n\nThe **Structured Output Parser** then **cleans up and organizes** this data into a format that other nodes can use.\n\n๐Ÿ’ก **Beginner Tip:**\nThis is like a smart assistant that goes to your admin dashboard, collects important info, and makes sure itโ€™s readable for the next steps.\n\nโœ… **Why itโ€™s useful:**\nEven if the data is messy or complex on the dashboard, this section makes sure itโ€™s clean and ready to use in your automation.\n\n---\n\n## ๐Ÿงฉ **Section 3: Data Formatting & Order Extraction**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿ”ง `Format Customer Info`**\n* **๐Ÿ“ฆ `Get Customer Order History`**\n\n### ๐Ÿ“– What Happens Here:\n\nThese function nodes further **organize and process the scraped data**:\n\n* The first node extracts key customer details like name, email, and ID.\n* The second node focuses on their **order data** โ€” how many items they bought, total amount spent, etc.\n\n๐Ÿ’ก **Beginner Tip:**\nThink of this as organizing data into two folders: ๐Ÿงโ€โ™‚๏ธ โ€œCustomer Infoโ€ and ๐Ÿ“Š โ€œPurchase Dataโ€.\n\nโœ… **Why itโ€™s useful:**\nClean separation of data means better targeting. You'll know exactly **who** bought **what**, and **how much** they spent โ€” perfect for personalized offers!\n\n---\n\n## ๐ŸŽฏ **Section 4: Offer Decision & Action**\n\n### ๐Ÿงฑ Nodes:\n\n* **๐Ÿ’ฐ `Is Customer High-Value?`**\n* **๐Ÿ“ง `Send Special Offer Email`**\n* **โžก๏ธ `Ignore Low-Value Customers`**\n\n### ๐Ÿ“– What Happens Here:\n\nThis section **decides what action to take**:\n\n* The \"High Value Check\" compares a customerโ€™s total spending against a fixed threshold.\n* If their spending is **high enough**, they get a personalized **offer email** via Gmail.\n* If not, theyโ€™re simply **skipped** โ€” no email is sent.\n\n๐Ÿ’ก **Beginner Tip:**\nYou donโ€™t want to send offers to everyone. This smart filter ensures **only loyal/high-value customers** get incentives.\n\nโœ… **Why itโ€™s useful:**\nIt automates your **customer segmentation** and **email marketing**, saving you time while targeting the right people to boost sales.\n\n---\n\n## ๐ŸŽ‰ Final Thoughts\n\nThis workflow is a **powerful marketing automation tool**. Here's what it empowers you to do:\n\n* โฐ Run promotions on autopilot\n* ๐Ÿง  Use AI and proxies to collect data\n* ๐Ÿงน Organize complex customer records\n* ๐ŸŽฏ Only target the most valuable users\n* ๐Ÿ“ˆ Increase conversion rates with personalized emails\n\n---\n\n" }, "typeVersion": 1 }, { "id": "e7eec1fb-1a84-44be-8b8c-ab6fa4acbc1c", "name": "Auto-fixing Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserAutofixing", "position": [ 780, 280 ], "parameters": { "options": {} }, "typeVersion": 1 }, { "id": "3e4a7bfa-5ba6-4abb-8dac-72eeee8263a4", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 760, 500 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1.2 }, { "id": "6ba75ee7-46ea-4388-b5c2-b5ab2d4aecc1", "name": "Structured Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ 920, 500 ], "parameters": { "jsonSchemaExample": "[\n {\n \"customer_name\": \"John Doe\",\n \"orders\": [\n {\n \"amount\": 120,\n \"date\": \"2024-05-10\"\n },\n {\n \"amount\": 80,\n \"date\": \"2024-06-15\"\n }\n ]\n },\n {\n \"customer_name\": \"Jane Smith\",\n \"orders\": [\n {\n \"amount\": 200,\n \"date\": \"2024-04-05\"\n },\n {\n \"amount\": 150,\n \"date\": \"2024-05-01\"\n },\n {\n \"amount\": 180,\n \"date\": \"2024-06-10\"\n }\n ]\n },\n {\n \"customer_name\": \"Michael Johnson\",\n \"orders\": [\n {\n \"amount\": 600,\n \"date\": \"2024-07-01\"\n }\n ]\n }\n]\n" }, "typeVersion": 1.2 } ], "active": false, "pinData": { "Scrape Customer Profiles & Orders (Agent)": [ { "json": { "output": [ { "orders": [ { "date": "2024-05-10", "amount": 120 }, { "date": "2024-06-15", "amount": 80 } ], "customer_name": "John Doe", "customer_email": "johndoe@gmail.com" }, { "orders": [ { "date": "2024-04-05", "amount": 200 }, { "date": "2024-05-01", "amount": 150 }, { "date": "2024-06-10", "amount": 180 } ], "customer_name": "Jane Smith", "customer_email": "johnsmith@gmail.com" }, { "orders": [ { "date": "2024-07-01", "amount": 600 } ], "customer_name": "Michael Johnson", "customer_email": "michael@gmail.com" } ] } } ] }, "settings": { "executionOrder": "v1" }, "versionId": "f2ffb3ba-6efc-493d-93c6-6a2e99e8c2d8", "connections": { "AI Assistant": { "ai_languageModel": [ [ { "node": "Scrape Customer Profiles & Orders (Agent)", "type": "ai_languageModel", "index": 0 } ] ] }, "OpenAI Chat Model": { "ai_languageModel": [ [ { "node": "Auto-fixing Output Parser", "type": "ai_languageModel", "index": 0 } ] ] }, "Format Customer Info": { "main": [ [ { "node": "Get Customer Order History", "type": "main", "index": 0 } ] ] }, "Bright Data MCP Scraper": { "ai_tool": [ [ { "node": "Scrape Customer Profiles & Orders (Agent)", "type": "ai_tool", "index": 0 } ] ] }, "Is Customer High-Value?": { "main": [ [ { "node": "Send Special Offer Email", "type": "main", "index": 0 } ], [ { "node": "Ignore Low-Value Customers", "type": "main", "index": 0 } ] ] }, "Set customer history url": { "main": [ [ { "node": "Scrape Customer Profiles & Orders (Agent)", "type": "main", "index": 0 } ] ] }, "Structured Output Parser": { "ai_outputParser": [ [ { "node": "Auto-fixing Output Parser", "type": "ai_outputParser", "index": 0 } ] ] }, "Auto-fixing Output Parser": { "ai_outputParser": [ [ { "node": "Scrape Customer Profiles & Orders (Agent)", "type": "ai_outputParser", "index": 0 } ] ] }, "Get Customer Order History": { "main": [ [ { "node": "Is Customer High-Value?", "type": "main", "index": 0 } ] ] }, "Run Offer Campaign Monthly": { "main": [ [ { "node": "Set customer history url", "type": "main", "index": 0 } ] ] }, "Scrape Customer Profiles & Orders (Agent)": { "main": [ [ { "node": "Format Customer Info", "type": "main", "index": 0 } ] ] } } }, "lastUpdatedBy": 62, "workflowInfo": { "nodeCount": 20, "nodeTypes": { "n8n-nodes-base.if": { "count": 1 }, "n8n-nodes-base.set": { "count": 1 }, "n8n-nodes-base.code": { "count": 2 }, "n8n-nodes-base.noOp": { "count": 1 }, "n8n-nodes-base.gmail": { "count": 1 }, "n8n-nodes-base.stickyNote": { "count": 7 }, "n8n-nodes-mcp.mcpClientTool": { "count": 1 }, "@n8n/n8n-nodes-langchain.agent": { "count": 1 }, "n8n-nodes-base.scheduleTrigger": { "count": 1 }, "@n8n/n8n-nodes-langchain.lmChatOpenAi": { "count": 2 }, "@n8n/n8n-nodes-langchain.outputParserAutofixing": { "count": 1 }, "@n8n/n8n-nodes-langchain.outputParserStructured": { "count": 1 } } }, "status": "published", "user": { "name": "Yaron Been", "username": "yaron-nofluff", "bio": "Building AI Agents and Automations | Growth Marketer | Entrepreneur | Book Author & Podcast Host\n\nIf you need any help with Automations, feel free to reach out via linkedin:\nhttps://www.linkedin.com/in/yaronbeen/\n\nAnd check out my Youtube channel:\nhttps://www.youtube.com/@YaronBeen/videos", "verified": true, "links": [ "https://www.nofluff.online/automation-services/" ], "avatar": "https://gravatar.com/avatar/a4e4dcaa1f76ff5266bbf80e8df86d22efda890474c68f7796e72fd82e3f2375?r=pg&d=retro&size=200" }, "nodes": [ { "id": 20, "icon": "fa:map-signs", "name": "n8n-nodes-base.if", "codex": { "data": { "alias": [ "Router", "Filter", "Condition", "Logic", "Boolean", "Branch" ], "details": "The IF node can be used to implement binary conditional logic in your workflow. You can set up one-to-many conditions to evaluate each item of data being inputted into the node. That data will either evaluate to TRUE or FALSE and route out of the node accordingly.\n\nThis node has multiple types of conditions: Bool, String, Number, and Date & Time.", "resources": { "generic": [ { "url": "https://n8n.io/blog/learn-to-automate-your-factorys-incident-reporting-a-step-by-step-guide/", "icon": "๐Ÿญ", "label": "Learn to Automate Your Factory's Incident Reporting: A Step by Step Guide" }, { "url": "https://n8n.io/blog/2021-the-year-to-automate-the-new-you-with-n8n/", "icon": "โ˜€๏ธ", "label": "2021: The Year to Automate the New You with n8n" }, { "url": "https://n8n.io/blog/why-business-process-automation-with-n8n-can-change-your-daily-life/", "icon": "๐Ÿงฌ", "label": "Why business process automation with n8n can change your daily life" }, { "url": "https://n8n.io/blog/create-a-toxic-language-detector-for-telegram/", "icon": "๐Ÿคฌ", "label": "Create a toxic language detector for Telegram in 4 step" }, { "url": 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