{ "workflow": { "id": 5965, "name": "Monitor customer churn indicators with Bright Data MCP and OpenAI", "views": 342, "recentViews": 0, "totalViews": 342, "createdAt": "2025-07-13T19:02:08.245Z", "description": "*This workflow contains community nodes that are only compatible with the self-hosted version of n8n.*\n\nThis workflow automatically monitors customer churn indicators and early warning signals to help reduce customer attrition and improve retention rates. It saves you time by eliminating the need to manually track customer behavior and provides proactive insights for preventing customer churn.\n\n## Overview\n\nThis workflow automatically scrapes customer data sources, support tickets, usage analytics, and engagement metrics to identify patterns that indicate potential customer churn. It uses Bright Data to access customer data and AI to intelligently analyze behavior patterns and predict churn risk.\n\n## Tools Used\n\n- **n8n**: The automation platform that orchestrates the workflow\n- **Bright Data**: For scraping customer data and analytics platforms without being blocked\n- **OpenAI**: AI agent for intelligent churn prediction and pattern analysis\n- **Google Sheets**: For storing churn indicators and customer retention 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 churn monitoring spreadsheet\n5. **Customize**: Define customer data sources and churn indicator parameters\n\n## Use Cases\n\n- **Customer Success**: Proactively identify at-risk customers for retention efforts\n- **Account Management**: Prioritize customer outreach based on churn probability\n- **Product Teams**: Identify product issues that contribute to customer churn\n- **Revenue Operations**: Reduce churn rates and improve customer lifetime value\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 #churnprediction #customerretention #brightdata #webscraping #customeranalytics #n8nworkflow #workflow #nocode #churnindicators #customersuccess #retentionanalysis #customerchurn #customerinsights #churnprevention #retentionmarketing #customerdata #churnmonitoring #customerlifecycle #retentionmetrics #churnanalysis #customerbehavior #retentionoptimization #churnreduction #customerengagement #retentionstrategy #churnmanagement #customerhealth #retentiontracking", "workflow": { "id": "JC8NHUFMRr3Ss4U1", "meta": { "instanceId": "60046904b104f0f72b2629a9d88fe9f676be4035769f1f08dad1dd38a76b9480", "templateCredsSetupCompleted": true }, "name": "22 Monitor Churn Indicators", "tags": [], "nodes": [ { "id": "25d6648a-74f7-46eb-afb9-d2e305373165", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 380, 280 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1.2 }, { "id": "42614abe-c0a6-4149-b0cc-96dbe6cade08", "name": "Daily Check Trigger", "type": "n8n-nodes-base.scheduleTrigger", "position": [ -60, 0 ], "parameters": { "rule": { "interval": [ { "triggerAtHour": 9 } ] } }, "typeVersion": 1.2 }, { "id": "f2f3dcdf-00d8-46ac-951a-4c1a7c964068", "name": "Set Admin Dashboard URL", "type": "n8n-nodes-base.set", "position": [ 140, 0 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "c07e5c58-b422-4384-85a5-a8049080f8f9", "name": "database", "type": "string", "value": "https://docs.google.com/spreadsheets/YOUR_AWS_SECRET_KEY_HERE?gid=1026450716#gid=1026450716" } ] } }, "typeVersion": 3.4 }, { "id": "2f224d5a-e0c7-4651-80de-b298e4cf5f5a", "name": "Scrape User Data (AI Agent)", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 440, 0 ], "parameters": { "text": "=scrape the database URL below and extract the data.\nURL: {{ $json.database }}", "options": {}, "promptType": "define", "hasOutputParser": true }, "typeVersion": 2 }, { "id": "c9eab14a-dd60-4a99-aa61-5a42fb9f7a72", "name": "Bright Data MCP Client", "type": "n8n-nodes-mcp.mcpClientTool", "position": [ 580, 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": "ea714fc5-b2cc-44dd-821e-2beaa818937e", "name": "Format User Login Data", "type": "n8n-nodes-base.code", "position": [ 780, 0 ], "parameters": { "jsCode": "// 1️⃣ Get the input array from the agent response\nconst users = items[0].json.output;\n\n// 2️⃣ Map each user to an individual n8n item\nconst output = users.map(user => {\n return {\n json: {\n name: user.name,\n email: user.email,\n last_login: user.last_login,\n plan: user.plan\n }\n };\n});\n\n// 3️⃣ Return the output array with each user as separate item\nreturn output;\n" }, "typeVersion": 2 }, { "id": "598f0e1b-e8d7-47c6-ba60-d390151359f1", "name": "Convert Date to Days Since Login", "type": "@n8n/n8n-nodes-langchain.openAi", "position": [ 960, 0 ], "parameters": { "modelId": { "__rl": true, "mode": "list", "value": "gpt-4o-mini", "cachedResultName": "GPT-4O-MINI" }, "options": {}, "messages": { "values": [ { "content": "=I will provide you with a last login date in YYYY-MM-DD format.\n\nPlease calculate the number of days between that date and today, and respond only with:\n\n\n\nFor example, if the last login date is 2024-06-01, and today is 2024-07-01, then reply:\n\n30\n\nHere is the last login date: {{ $json.last_login }}\n" } ] } }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1.8 }, { "id": "6ace5da5-be7e-4b65-9b03-87460b040dd5", "name": "Convert Days to Integer", "type": "n8n-nodes-base.set", "position": [ 1280, 0 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "45b3fe33-21b3-4ece-ac05-e9bd693ae035", "name": "message.content", "type": "number", "value": "={{ $json.message.content }}" } ] } }, "typeVersion": 3.4 }, { "id": "7cd275d8-32e8-4b66-8b3b-4b9fbaff6f7c", "name": "Check Inactive Threshold (>=30 days)", "type": "n8n-nodes-base.if", "position": [ 1680, 0 ], "parameters": { "options": {}, "conditions": { "options": { "version": 2, "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "a52ad37c-cc43-44a0-8018-9f7ef657a974", "operator": { "type": "number", "operation": "gte" }, "leftValue": "={{ $json.message.content }}", "rightValue": 30 } ] } }, "typeVersion": 2.2 }, { "id": "d960ebcd-7571-4bad-9940-a89cd5b96b94", "name": "Send Re-engagement Email", "type": "n8n-nodes-base.gmail", "position": [ 1920, -140 ], "webhookId": "d1e41033-adf9-41d0-a47a-97448c74347b", "parameters": { "sendTo": "={{ $('Format User Login Data').item.json.email }}", "message": "=We are missing you.\n\nYou haven't visited our application from a while. So we just wanted to reach out in case there is some problems.\n\nWe would like you to come back.\n\nKind regards,\nTeam [company name]", "options": {}, "subject": "We are missing you, we have an offer for you", "emailType": "text" }, "credentials": { "gmailOAuth2": { "id": "credential-id", "name": "gmailOAuth2 Credential" } }, "typeVersion": 2.1 }, { "id": "88a609e0-e60b-47d5-9da8-28302a4e3a4d", "name": "Do Nothing (User Active)", "type": "n8n-nodes-base.noOp", "position": [ 1920, 140 ], "parameters": {}, "typeVersion": 1 }, { "id": "66cc00e8-e9c9-454f-b600-ecc771e57ca3", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ -80, -680 ], "parameters": { "color": 6, "width": 360, "height": 860, "content": "## 🧩 **Section 1: Trigger & Dashboard Input**\n\n**🔁 Schedule Trigger** → **📝 Edit Fields**\n\n### 🔹 What Happens Here:\n\n* **⏰ Schedule Trigger** runs the workflow automatically (e.g., daily).\n* **📝 Edit Fields** manually sets the URL of the admin dashboard containing user data.\n\n### 💡 Beginner Tip:\n\nThis section starts everything. You define *where* the user data lives by setting the dashboard URL. You don’t need coding—just copy-paste the dashboard URL.\n\n### 🔧 Icons Summary:\n\n* ⏰ **Schedule Trigger** = Starts the automation\n* ✏️ **Edit Fields** = Inputs the dashboard URL\n\n---\n\n" }, "typeVersion": 1 }, { "id": "9d74403a-fd7d-41c1-b866-91ff1fdc0fa2", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 400, -720 ], "parameters": { "color": 3, "width": 1040, "height": 900, "content": "## 🤖 **Section 2: AI-Powered Scraping & Date Transformation**\n\n**🧠 AI Agent + MCP Client** → **{} Code** → **OpenAI Message Model** → **📝 Edit Fields1**\n\n### 🔹 What Happens Here:\n\n* **🤖 AI Agent** uses Bright Data MCP to scrape user data from the URL (like last login info).\n* **🧩 MCP Client + Structured Output Parser** help the agent fetch and structure the scraped data.\n* **{} Code Node** formats this data and isolates the `last_login_date` (e.g., \"2024-06-01\").\n* **🧠 OpenAI Message Model** is used smartly to convert `\"2024-06-01\"` into `\"30\"` (number of days since last login).\n* **📝 Edit Fields1** converts the data type from string to integer.\n\n### 💡 Beginner Tip:\n\nYou're combining **web scraping with AI** here. Even if you don’t know code, the AI agent and OpenAI node are doing the heavy lifting—transforming raw dates into meaningful values.\n\n### 🔧 Icons Summary:\n\n* 🤖 **AI Agent** = Fetches the data\n* 🛜 **MCP Client** = Connects to Bright Data’s mobile proxy\n* 🧩 **Structured Parser** = Makes scraped data usable\n* {} **Code Node** = Cleans and prepares the data\n* 🧠 **OpenAI** = Converts date to “days ago”\n* ✏️ **Edit Fields1** = Converts to a number\n\n---\n\n" }, "typeVersion": 1 }, { "id": "ba433321-f29a-4f05-beb0-7a2943c7e362", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 1640, -540 ], "parameters": { "color": 5, "width": 400, "height": 860, "content": "## ✉️ **Section 3: Smart Notification Logic**\n\n**⚖️ IF Node** → **📧 Gmail** OR **➡️ No Operation**\n\n### 🔹 What Happens Here:\n\n* **⚖️ IF Node** checks if the number of days since last login is **greater than or equal to 30**.\n* If **True** ➡️ send an email using **📧 Gmail Node**.\n* If **False** ➡️ just **do nothing** with **➡️ No Operation Node**.\n\n" }, "typeVersion": 1 }, { "id": "4422fbed-c696-4511-80ef-4a6eca6c9f64", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ 2180, -540 ], "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": "07a48184-3a1b-4756-8d79-b552df19a45d", "name": "Sticky Note9", "type": "n8n-nodes-base.stickyNote", "position": [ -1740, -640 ], "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": "07f592f8-0aac-4817-9c6f-5c62325b794b", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ -1740, -300 ], "parameters": { "color": 4, "width": 1289, "height": 2278, "content": "# ✅ **Workflow Title: Inactive User Detection & Re-engagement Email Automation**\n\n---\n\n## 🧩 **Section 1: Trigger & Dashboard Input**\n\n**🔁 Schedule Trigger** → **📝 Edit Fields**\n\n### 🔹 What Happens Here:\n\n* **⏰ Schedule Trigger** runs the workflow automatically (e.g., daily).\n* **📝 Edit Fields** manually sets the URL of the admin dashboard containing user data.\n\n### 💡 Beginner Tip:\n\nThis section starts everything. You define *where* the user data lives by setting the dashboard URL. You don’t need coding—just copy-paste the dashboard URL.\n\n### 🔧 Icons Summary:\n\n* ⏰ **Schedule Trigger** = Starts the automation\n* ✏️ **Edit Fields** = Inputs the dashboard URL\n\n---\n\n## 🤖 **Section 2: AI-Powered Scraping & Date Transformation**\n\n**🧠 AI Agent + MCP Client** → **{} Code** → **OpenAI Message Model** → **📝 Edit Fields1**\n\n### 🔹 What Happens Here:\n\n* **🤖 AI Agent** uses Bright Data MCP to scrape user data from the URL (like last login info).\n* **🧩 MCP Client + Structured Output Parser** help the agent fetch and structure the scraped data.\n* **{} Code Node** formats this data and isolates the `last_login_date` (e.g., \"2024-06-01\").\n* **🧠 OpenAI Message Model** is used smartly to convert `\"2024-06-01\"` into `\"30\"` (number of days since last login).\n* **📝 Edit Fields1** converts the data type from string to integer.\n\n### 💡 Beginner Tip:\n\nYou're combining **web scraping with AI** here. Even if you don’t know code, the AI agent and OpenAI node are doing the heavy lifting—transforming raw dates into meaningful values.\n\n### 🔧 Icons Summary:\n\n* 🤖 **AI Agent** = Fetches the data\n* 🛜 **MCP Client** = Connects to Bright Data’s mobile proxy\n* 🧩 **Structured Parser** = Makes scraped data usable\n* {} **Code Node** = Cleans and prepares the data\n* 🧠 **OpenAI** = Converts date to “days ago”\n* ✏️ **Edit Fields1** = Converts to a number\n\n---\n\n## ✉️ **Section 3: Smart Notification Logic**\n\n**⚖️ IF Node** → **📧 Gmail** OR **➡️ No Operation**\n\n### 🔹 What Happens Here:\n\n* **⚖️ IF Node** checks if the number of days since last login is **greater than or equal to 30**.\n* If **True** ➡️ send an email using **📧 Gmail Node**.\n* If **False** ➡️ just **do nothing** with **➡️ No Operation Node**.\n\n### 💡 Beginner Tip:\n\nThis section automates your decision-making! You’re now reaching out only to **inactive users**—this is powerful for **re-engagement**.\n\n### 🔧 Icons Summary:\n\n* ⚖️ **If Node** = Makes the decision\n* 📧 **Gmail** = Sends the message\n* ➡️ **No Operation** = Ignores the user if they recently logged in\n\n---\n\n## 🌟 **Real-World Use Case**\n\nThis workflow is **perfect for SaaS applications**. It helps:\n\n* Detect users who haven't logged in recently\n* Alert or re-engage them with tailored emails\n* Maintain active user base and reduce churn\n\n---\n\n## 🧠 How Can a Beginner Take Advantage?\n\n1. **No coding? No problem.** Just update the URL in the Edit Fields node.\n2. Customize the **email message** inside the Gmail node.\n3. Schedule this to run **daily/weekly** to automatically track user inactivity.\n4. Connect this to a **CRM** or **Google Sheets** to log alerts.\n\n---\n\n" }, "typeVersion": 1 }, { "id": "b943feef-921c-4958-a656-b64ef489822b", "name": "Auto-fixing Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserAutofixing", "position": [ 740, 280 ], "parameters": { "options": {} }, "typeVersion": 1 }, { "id": "7026ca7f-f4d3-4d15-920a-ce84a3da578d", "name": "OpenAI Chat Model1", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 720, 500 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "id": "credential-id", "name": "openAiApi Credential" } }, "typeVersion": 1.2 }, { "id": "c4772d37-4e51-48e2-b8aa-2b47f1b25503", "name": "Structured Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ 880, 500 ], "parameters": { "jsonSchemaExample": "[\n {\n \"name\": \"User 1\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-06-01\",\n \"plan\": \"Pro\"\n },\n {\n \"name\": \"User 2\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-05-20\",\n \"plan\": \"Free\"\n },\n {\n \"name\": \"User 3\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-04-15\",\n \"plan\": \"Enterprise\"\n },\n {\n \"name\": \"User 4\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-07-01\",\n \"plan\": \"Pro\"\n },\n {\n \"name\": \"User 5\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-03-25\",\n \"plan\": \"Free\"\n },\n {\n \"name\": \"User 6\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-05-10\",\n \"plan\": \"Enterprise\"\n },\n {\n \"name\": \"User 7\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-06-20\",\n \"plan\": \"Pro\"\n },\n {\n \"name\": \"User 8\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-04-05\",\n \"plan\": \"Free\"\n },\n {\n \"name\": \"User 9\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-05-30\",\n \"plan\": \"Enterprise\"\n },\n {\n \"name\": \"User 10\",\n \"email\": \"user@example.com\",\n \"last_login\": \"2024-03-15\",\n \"plan\": \"Pro\"\n }\n]\n" }, "typeVersion": 1.2 } ], "active": false, "pinData": { "Scrape User Data (AI Agent)": [ { "json": { "output": [ { "name": "User 1", "plan": "Pro", "email": "user1@example.com", "last_login": "2024-06-01" }, { "name": "User 2", "plan": "Free", "email": "user2@example.com", "last_login": "2024-05-20" }, { "name": "User 3", "plan": "Enterprise", "email": "user3@example.com", "last_login": "2024-04-15" }, { "name": "User 4", "plan": "Pro", "email": "user4@example.com", "last_login": "2024-07-01" }, { "name": "User 5", "plan": "Free", "email": "user5@example.com", "last_login": "2024-03-25" }, { "name": "User 6", "plan": "Enterprise", "email": "user6@example.com", "last_login": "2024-05-10" }, { "name": "User 7", "plan": "Pro", "email": "user7@example.com", "last_login": "2024-06-20" }, { "name": "User 8", "plan": "Free", "email": "user8@example.com", "last_login": "2024-04-05" }, { "name": "User 9", "plan": "Enterprise", "email": "user9@example.com", "last_login": "2024-05-30" }, { "name": "User 10", "plan": "Pro", "email": "user10@example.com", "last_login": "2024-03-15" } ] } } ] }, "settings": { "executionOrder": "v1" }, "versionId": "3590dd60-19d3-4b24-98e0-c6e495a0b9c0", "connections": { "OpenAI Chat Model": { "ai_languageModel": [ [ { "node": "Scrape User Data (AI Agent)", "type": "ai_languageModel", "index": 0 } ] ] }, "OpenAI Chat Model1": { "ai_languageModel": [ [ { "node": "Auto-fixing Output Parser", "type": "ai_languageModel", "index": 0 } ] ] }, "Daily Check Trigger": { "main": [ [ { "node": "Set Admin Dashboard URL", "type": "main", "index": 0 } ] ] }, "Bright Data MCP Client": { "ai_tool": [ [ { "node": "Scrape User Data (AI Agent)", "type": "ai_tool", "index": 0 } ] ] }, "Format User Login Data": { "main": [ [ { "node": "Convert Date to Days Since Login", "type": "main", "index": 0 } ] ] }, "Convert Days to Integer": { "main": [ [ { "node": "Check Inactive Threshold (>=30 days)", "type": "main", "index": 0 } ] ] }, "Set Admin Dashboard URL": { "main": [ [ { "node": "Scrape User Data (AI 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 User Data (AI Agent)", "type": "ai_outputParser", "index": 0 } ] ] }, "Scrape User Data (AI Agent)": { "main": [ [ { "node": "Format User Login Data", "type": "main", "index": 0 } ] ] }, "Convert Date to Days Since Login": { "main": [ [ { "node": "Convert Days to Integer", "type": "main", "index": 0 } ] ] }, "Check Inactive Threshold (>=30 days)": { "main": [ [ { "node": "Send Re-engagement Email", "type": "main", "index": 0 } ], [ { "node": "Do Nothing (User Active)", "type": "main", "index": 0 } ] ] } } }, "lastUpdatedBy": 62, "workflowInfo": { "nodeCount": 20, "nodeTypes": { "n8n-nodes-base.if": { "count": 1 }, "n8n-nodes-base.set": { "count": 2 }, "n8n-nodes-base.code": { "count": 1 }, "n8n-nodes-base.noOp": { "count": 1 }, "n8n-nodes-base.gmail": { "count": 1 }, "n8n-nodes-base.stickyNote": { "count": 6 }, "n8n-nodes-mcp.mcpClientTool": { "count": 1 }, "@n8n/n8n-nodes-langchain.agent": { "count": 1 }, "n8n-nodes-base.scheduleTrigger": { "count": 1 }, "@n8n/n8n-nodes-langchain.openAi": { "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": "🏭", "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": "☀️", "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": "🧬", "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": "🤬", "label": "Create a toxic language detector for Telegram in 4 step" }, { "url": "https://n8n.io/blog/no-code-ecommerce-workflow-automations/", 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