{ "id": "LIOY5U6r4W8pmkrH", "meta": { "templateCredsSetupCompleted": true }, "name": "33 Analyze Territory Performance", "tags": [], "nodes": [ { "id": "0568c8de-17a3-4a9b-a3d7-cf9a9e937888", "name": "Weekly Territory Check", "type": "n8n-nodes-base.scheduleTrigger", "position": [ 0, 0 ], "parameters": { "rule": { "interval": [ { "field": "weeks", "triggerAtDay": [ 1 ], "triggerAtHour": 9 } ] } }, "typeVersion": 1.2 }, { "id": "065eaed2-28b0-4866-8173-5ec742a40e47", "name": "Prepare Request Params", "type": "n8n-nodes-base.set", "position": [ 200, 0 ], "parameters": { "options": {}, "assignments": { "assignments": [ { "id": "01dce1c2-299c-4def-a8d0-0194cae94ea2", "name": "url", "type": "string", "value": "example.com" } ] } }, "typeVersion": 3.4 }, { "id": "71435f74-f8bf-485e-b16e-0a9092dfdec7", "name": "Run Bright Data Scraper", "type": "@n8n/n8n-nodes-langchain.agent", "position": [ 440, 0 ], "parameters": { "text": "=From the following URL, extract fields the below fields.\n\nStore ID\nName\nAddress\nRegion\n\nURL: {{ $json.url }}", "options": {}, "promptType": "define", "hasOutputParser": true }, "typeVersion": 2 }, { "id": "26363bd7-51e1-4a01-a489-e16f4b877b52", "name": "Send Notification Email", "type": "n8n-nodes-base.gmail", "position": [ 1040, -240 ], "parameters": { "sendTo": "user@example.com", "message": "=Hello Team!\n\nThe Regional sales data has updated in the google sheets. So go and check it out fast.\n\nRegards,\nYour Name", "options": {}, "subject": "Regional Sales data has updated", "emailType": "text" }, "credentials": { "gmailOAuth2": { "name": "" } }, "typeVersion": 2.1 }, { "id": "bf4afd69-2309-4aed-89d5-34c704812bc9", "name": "Split Stores to Items", "type": "n8n-nodes-base.code", "position": [ 1040, 0 ], "parameters": { "jsCode": "// n8n Function Node\n// Purpose: Takes wrapped `output` array, returns each store as its own item\n\nconst results = [];\n\n// Grab the output array from first item\nconst stores = items[0].json.output;\n\n// Loop through each store\nfor (const store of stores) {\n results.push({ json: store });\n}\n\nreturn results;\n" }, "typeVersion": 2 }, { "id": "6c9ea046-2bc1-40e5-a95e-66a7afbc3bad", "name": "Update Regional Data Sheet", "type": "n8n-nodes-base.googleSheets", "position": [ 1260, 0 ], "parameters": { "columns": { "value": { "Region": "={{ $json.region }}", "Address": "={{ $json.address }}", "Store ID": "={{ $json.store_id }}", "Store name": "={{ $json.store_name }}", "Last updated": "={{ $json.last_updated }}", "Estimated sales": "={{ $json.estimated_sales }}" }, "schema": [ { "id": "Store ID", "type": "string", "display": true, "removed": false, "required": false, "displayName": "Store ID", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Store name", "type": "string", "display": true, "removed": false, "required": false, "displayName": "Store name", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Address", "type": "string", "display": true, "removed": false, "required": false, "displayName": "Address", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Region", "type": "string", "display": true, "removed": false, "required": false, "displayName": "Region", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Estimated sales", "type": "string", "display": true, "removed": false, "required": false, "displayName": "Estimated sales", "defaultMatch": false, "canBeUsedToMatch": true }, { "id": "Last updated", "type": "string", "display": true, "removed": false, "required": false, "displayName": "Last updated", "defaultMatch": false, "canBeUsedToMatch": true } ], "mappingMode": "defineBelow", "matchingColumns": [], "attemptToConvertTypes": false, "convertFieldsToString": false }, "options": {}, "operation": "append", "sheetName": { "__rl": true, "mode": "list", "value": "gid=0", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/12hjlzSEhesN4r05t4Bq9w4ttEBzwXEmddDSJZ30N0tA/edit#gid=0", "cachedResultName": "Sheet1" }, "documentId": { "__rl": true, "mode": "list", "value": "12hjlzSEhesN4r05t4Bq9w4ttEBzwXEmddDSJZ30N0tA", "cachedResultUrl": "https://docs.google.com/spreadsheets/d/12hjlzSEhesN4r05t4Bq9w4ttEBzwXEmddDSJZ30N0tA/edit?usp=drivesdk", "cachedResultName": "Store data" } }, "credentials": { "googleSheetsOAuth2Api": { "name": "" } }, "typeVersion": 4.6 }, { "id": "f4d0b4ea-5842-4730-8cf5-e6627ab54329", "name": "Bright Data MCP Tool", "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": { "name": "" } }, "typeVersion": 1 }, { "id": "d3e22591-7bc7-494d-b917-934a4ffe419a", "name": "LLM Prompt Handler", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 400, 280 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "name": "" } }, "typeVersion": 1.2 }, { "id": "f100c167-e28b-480a-87d5-6c143812a96a", "name": "Sticky Note", "type": "n8n-nodes-base.stickyNote", "position": [ -40, -640 ], "parameters": { "color": 6, "width": 380, "height": 820, "content": "## \u2705 **\ud83d\udd39 Section 1: Trigger & Prepare**\n\n**Nodes:**\n1\ufe0f\u20e3 `Weekly Territory Check` *(Schedule Trigger)*\n2\ufe0f\u20e3 `Prepare Request Params` *(Edit Fields)*\n\n**\ud83d\udca1 What it does:**\n\n* \u23f0 **Weekly Trigger**: The automation starts **automatically** on a set schedule \u2014 e.g., every Monday at 6 AM \u2014 so you don\u2019t need to remember to run it.\n* \ud83d\udcdd **Prepare Request**: This step **sets up the input** \u2014 like choosing which regions to scrape, date filters, or any special parameters you want the scraper to use.\n\n**\u2728 Why it\u2019s powerful for you:**\n\n* You never forget to update your data.\n* Anyone can **adjust input** (e.g., change region) **without touching the rest of the workflow**.\n* Perfect for **zero-code team edits**.\n\n---\n\n" }, "typeVersion": 1 }, { "id": "8548ff7c-748e-464c-87b4-39b1bd973bde", "name": "Sticky Note1", "type": "n8n-nodes-base.stickyNote", "position": [ 420, -1000 ], "parameters": { "color": 3, "width": 300, "height": 1180, "content": "## \u2705 **\ud83d\udd39 Section 2: Smart Data Collection & Parsing**\n\n**Nodes:**\n3\ufe0f\u20e3 `Run Bright Data Scraper` *(AI Agent)*\n\u2014 uses \u23ec\n\n* `Bright Data MCP Tool` *(MCP Client)*\n* `LLM Prompt Handler` *(OpenAI Chat Model)*\n* `Fix/Format Scraper Output` *(Auto-fixing Output Parser)*\n* `Validation Assistant` *(OpenAI Chat Model1)*\n* `Final Output Formatter` *(Structured Output Parser)*\n\n**\ud83d\udca1 What it does:**\n\n* \ud83e\udd16 The **AI Agent** talks to the **Bright Data MCP Tool** to **scrape live data** from your target sites.\n* \ud83e\udde0 The **LLM Prompt Handler** helps the AI figure out what pages to crawl, what data to look for, and how to handle tricky websites.\n* \ud83e\uddf9 The **Auto-fixer & Parsers** make sure your scraped data is always **clean JSON**, so you never get errors in the next steps.\n\n**\u2728 Why it\u2019s powerful for you:**\n\n* This section handles all the **dirty work** of web scraping & fixing messy data.\n* You **don\u2019t write code or worry about site changes** \u2014 the agent + model fix issues automatically.\n* If a page changes, the AI adjusts how it scrapes, so you\u2019re not stuck fixing broken scrapers every week.\n\n---\n" }, "typeVersion": 1 }, { "id": "17a66823-bde6-4205-b1e4-3c6cd1969f2b", "name": "Sticky Note2", "type": "n8n-nodes-base.stickyNote", "position": [ 1000, -780 ], "parameters": { "color": 5, "width": 400, "height": 960, "content": "## \u2705 **\ud83d\udd39 Section 3: Process, Save & Notify**\n\n**Nodes:**\n4\ufe0f\u20e3 `Split Stores to Items` *(Code)*\n5\ufe0f\u20e3 `Update Regional Data Sheet` *(Google Sheets)*\n6\ufe0f\u20e3 `Send Notification Email` *(Gmail)*\n\n**\ud83d\udca1 What it does:**\n\n* \u2699\ufe0f The `Split Stores to Items` node **unwraps** the single big output from the scraper \u2192 breaks it into **one item per store** so you can work with them individually.\n* \ud83d\udcca The `Update Regional Data Sheet` node **writes each store\u2019s info** into Google Sheets \u2014 creating a clean, always-up-to-date record of all your stores & their sales.\n* \ud83d\udce7 The `Send Notification Email` node **alerts you automatically** if anything needs attention \u2014 for example, \u201cHey, Region North has 20% higher load than Region South. Reassign recommended!\u201d\n\n" }, "typeVersion": 1 }, { "id": "666629f1-e070-49f3-a31b-1c6375c75734", "name": "Sticky Note5", "type": "n8n-nodes-base.stickyNote", "position": [ 1480, -780 ], "parameters": { "color": 7, "width": 380, "height": 240, "content": "## I\u2019ll receive a tiny commission if you join Bright Data through this link\u2014thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25" }, "typeVersion": 1 }, { "id": "f4e125ba-f6df-465d-8ce0-b0a6c996f3e0", "name": "Sticky Note9", "type": "n8n-nodes-base.stickyNote", "position": [ -1680, -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": "ec9115e3-3507-44e6-b57c-37e5fe7ed046", "name": "Sticky Note4", "type": "n8n-nodes-base.stickyNote", "position": [ -1680, -300 ], "parameters": { "color": 4, "width": 1289, "height": 2398, "content": "## \ud83c\udfaf **Your Workflow: Territory Performance Analyzer & Reassigner**\n\n**\u2728 Purpose:**\nEvery week, this automation **scrapes fresh regional sales data**, splits it cleanly, saves it to a tracking sheet, and sends a smart email update if anything needs your attention \u2014 **all without you doing a thing!**\n\n---\n\n## \u2705 **\ud83d\udd39 Section 1: Trigger & Prepare**\n\n**Nodes:**\n1\ufe0f\u20e3 `Weekly Territory Check` *(Schedule Trigger)*\n2\ufe0f\u20e3 `Prepare Request Params` *(Edit Fields)*\n\n**\ud83d\udca1 What it does:**\n\n* \u23f0 **Weekly Trigger**: The automation starts **automatically** on a set schedule \u2014 e.g., every Monday at 6 AM \u2014 so you don\u2019t need to remember to run it.\n* \ud83d\udcdd **Prepare Request**: This step **sets up the input** \u2014 like choosing which regions to scrape, date filters, or any special parameters you want the scraper to use.\n\n**\u2728 Why it\u2019s powerful for you:**\n\n* You never forget to update your data.\n* Anyone can **adjust input** (e.g., change region) **without touching the rest of the workflow**.\n* Perfect for **zero-code team edits**.\n\n---\n\n## \u2705 **\ud83d\udd39 Section 2: Smart Data Collection & Parsing**\n\n**Nodes:**\n3\ufe0f\u20e3 `Run Bright Data Scraper` *(AI Agent)*\n\u2014 uses \u23ec\n\n* `Bright Data MCP Tool` *(MCP Client)*\n* `LLM Prompt Handler` *(OpenAI Chat Model)*\n* `Fix/Format Scraper Output` *(Auto-fixing Output Parser)*\n* `Validation Assistant` *(OpenAI Chat Model1)*\n* `Final Output Formatter` *(Structured Output Parser)*\n\n**\ud83d\udca1 What it does:**\n\n* \ud83e\udd16 The **AI Agent** talks to the **Bright Data MCP Tool** to **scrape live data** from your target sites.\n* \ud83e\udde0 The **LLM Prompt Handler** helps the AI figure out what pages to crawl, what data to look for, and how to handle tricky websites.\n* \ud83e\uddf9 The **Auto-fixer & Parsers** make sure your scraped data is always **clean JSON**, so you never get errors in the next steps.\n\n**\u2728 Why it\u2019s powerful for you:**\n\n* This section handles all the **dirty work** of web scraping & fixing messy data.\n* You **don\u2019t write code or worry about site changes** \u2014 the agent + model fix issues automatically.\n* If a page changes, the AI adjusts how it scrapes, so you\u2019re not stuck fixing broken scrapers every week.\n\n---\n\n## \u2705 **\ud83d\udd39 Section 3: Process, Save & Notify**\n\n**Nodes:**\n4\ufe0f\u20e3 `Split Stores to Items` *(Code)*\n5\ufe0f\u20e3 `Update Regional Data Sheet` *(Google Sheets)*\n6\ufe0f\u20e3 `Send Notification Email` *(Gmail)*\n\n**\ud83d\udca1 What it does:**\n\n* \u2699\ufe0f The `Split Stores to Items` node **unwraps** the single big output from the scraper \u2192 breaks it into **one item per store** so you can work with them individually.\n* \ud83d\udcca The `Update Regional Data Sheet` node **writes each store\u2019s info** into Google Sheets \u2014 creating a clean, always-up-to-date record of all your stores & their sales.\n* \ud83d\udce7 The `Send Notification Email` node **alerts you automatically** if anything needs attention \u2014 for example, \u201cHey, Region North has 20% higher load than Region South. Reassign recommended!\u201d\n\n**\u2728 Why it\u2019s powerful for you:**\n\n* You get **fresh, structured data** to review any time.\n* No manual copy/paste \u2192 your team sees **live performance trends**.\n* Automated emails keep your sales leads or managers in the loop without extra work.\n\n---\n\n## \ud83c\udf89 **\ud83d\udd11 How a Beginner Can Use This**\n\n\u2705 **No coding:** Everything runs with prebuilt nodes.\n\u2705 **Flexible:** Change your schedule, filters, or regions without breaking the flow.\n\u2705 **Scalable:** Easily add more stores, new regions, or extra tools \u2014 e.g., auto-publish to Airtable or a dashboard.\n\u2705 **Fully Automated:** Wake up Monday \u2192 check your sheet \u2192 know exactly where to adjust territories.\n\n---\n\n## \u2705 **\ud83c\udf1f Visual Summary with Icons**\n\n| Section | Steps | Icon |\n| ---------------------- | -------------------------------------------------- | -------- |\n| **1\ufe0f\u20e3 Trigger & Prep** | \ud83d\udd52 Weekly schedule \u2192 \ud83d\udcdd set scrape parameters | \u23f0 \u270f\ufe0f |\n| **2\ufe0f\u20e3 Collect & Fix** | \ud83e\udd16 AI scrapes \u2192 \ud83e\udde0 LLM helps \u2192 \ud83e\uddf9 Fix bad data | \ud83e\udd16 \ud83e\udde0 \ud83e\uddf9 |\n| **3\ufe0f\u20e3 Process & Act** | \ud83d\udd17 Split items \u2192 \ud83d\udcca Save to Sheets \u2192 \ud83d\udce7 Send email | \u2699\ufe0f \ud83d\udcca \ud83d\udce7 |\n\n---\n\n## \ud83d\uddc2\ufe0f **Result:**\n\n**Zero-hassle, fully automated territory management**, designed for **non-coders**, **sales ops**, or any small business owner.\n\n---\n\n" }, "typeVersion": 1 }, { "id": "8d32a7e9-423f-4c22-8356-d59302e9afd5", "name": "Auto-fixing Output Parser", "type": "@n8n/n8n-nodes-langchain.outputParserAutofixing", "position": [ 720, 280 ], "parameters": { "options": {} }, "typeVersion": 1 }, { "id": "02d03b02-4186-4c9a-aa7c-dd9a0eddf39c", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [ 700, 500 ], "parameters": { "model": { "__rl": true, "mode": "list", "value": "gpt-4o-mini" }, "options": {} }, "credentials": { "openAiApi": { "name": "" } }, "typeVersion": 1.2 }, { "id": "85bbb951-75ca-48ba-bd56-9763b0d8bd58", "name": "Structured Output Parser1", "type": "@n8n/n8n-nodes-langchain.outputParserStructured", "position": [ 860, 500 ], "parameters": { "jsonSchemaExample": "[\n {\n \"store_id\": \"ST-101\",\n \"store_name\": \"SuperMart Downtown\",\n \"address\": \"123 Main St, Springfield\",\n \"region\": \"North Region\",\n \"estimated_sales\": 125000,\n \"last_updated\": \"2025-07-09\"\n },\n {\n \"store_id\": \"ST-102\",\n \"store_name\": \"SuperMart East Side\",\n \"address\": \"456 Maple Ave, Springfield\",\n \"region\": \"North Region\",\n \"estimated_sales\": 98000,\n \"last_updated\": \"2025-07-09\"\n },\n {\n \"store_id\": \"ST-103\",\n \"store_name\": \"SuperMart Riverside\",\n \"address\": \"789 River Rd, Rivertown\",\n \"region\": \"South Region\",\n \"estimated_sales\": 73000,\n \"last_updated\": \"2025-07-09\"\n },\n {\n \"store_id\": \"ST-104\",\n \"store_name\": \"SuperMart Uptown\",\n \"address\": \"321 Oak St, Rivertown\",\n \"region\": \"South Region\",\n \"estimated_sales\": 67000,\n \"last_updated\": \"2025-07-09\"\n },\n {\n \"store_id\": \"ST-105\",\n \"store_name\": \"SuperMart West End\",\n \"address\": \"555 Elm St, Lake City\",\n \"region\": \"West Region\",\n \"estimated_sales\": 115000,\n \"last_updated\": \"2025-07-09\"\n }\n]\n" }, "typeVersion": 1.2 } ], "active": false, "settings": { "executionOrder": "v1" }, "versionId": "e5410ef0-2611-442f-894a-4ebf7ab5ba3d", "connections": { "OpenAI Chat Model": { "ai_languageModel": [ [ { "node": "Auto-fixing Output Parser", "type": "ai_languageModel", "index": 0 } ] ] }, "LLM Prompt Handler": { "ai_languageModel": [ [ { "node": "Run Bright Data Scraper", "type": "ai_languageModel", "index": 0 } ] ] }, "Bright Data MCP Tool": { "ai_tool": [ [ { "node": "Run Bright Data Scraper", "type": "ai_tool", "index": 0 } ] ] }, "Split Stores to Items": { "main": [ [ { "node": "Update Regional Data Sheet", "type": "main", "index": 0 } ] ] }, "Prepare Request Params": { "main": [ [ { "node": "Run Bright Data Scraper", "type": "main", "index": 0 } ] ] }, "Weekly Territory Check": { "main": [ [ { "node": "Prepare Request Params", "type": "main", "index": 0 } ] ] }, "Run Bright Data Scraper": { "main": [ [ { "node": "Split Stores to Items", "type": "main", "index": 0 }, { "node": "Send Notification Email", "type": "main", "index": 0 } ] ] }, "Auto-fixing Output Parser": { "ai_outputParser": [ [ { "node": "Run Bright Data Scraper", "type": "ai_outputParser", "index": 0 } ] ] }, "Structured Output Parser1": { "ai_outputParser": [ [ { "node": "Auto-fixing Output Parser", "type": "ai_outputParser", "index": 0 } ] ] } } }