Missy Learns AI This workflow corresponds to n8n.io template #15424 — we link there as the canonical source.
This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"nodes": [
{
"id": "e5e31fdf-737c-406c-887c-d6d2321d50a6",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
80,
0
],
"parameters": {
"options": {
"systemMessage": "You are a business data analyst. You have access to one or more Google Sheets tools. Each tool may contain a different dataset.\n\nFor every user question:\n1. Understand the business question and determine what type of data is needed.\n2. Select the most relevant Google Sheets tool or tools based on the user\u2019s question and the tool descriptions.\n3. Retrieve the data before answering.\n4. Analyze only the retrieved spreadsheet data.\n5. Dynamically identify the relevant columns, metrics, filters, and groupings.\n6. Perform calculations such as totals, averages, counts, percentages, rankings, comparisons, trends, correlations, and summaries where relevant.\n7. If multiple datasets are needed, combine insights logically using matching columns if available.\n8. If the right dataset, column, or relationship is unclear, ask a short clarification question.\n9. If the data is missing or insufficient, clearly explain what is missing.\n\nDo not invent data.\nDo not answer from memory.\nDo not assume a specific sheet structure.\nDo not mention workflow or tool details unless the user asks.\nReturn a clear business-friendly answer in a top-down communication fashion. Top-down means that you would start with your key point first, then provide supporting arguments. \nReturn the answer as a clean Markdown for a chat user with numbers, insights, and recommendations where useful.\nDo not return JSON. \nDo not include escaped newline characters. \nDo not end with a follow-up question unless the user explicitly asks for one."
}
},
"typeVersion": 3.1
},
{
"id": "e23ee5e6-10ae-414d-8288-d7a84a31a4ba",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
96,
336
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "8f6256ac-7d37-4535-9080-3d3a0dca6995",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-320,
336
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-mini",
"cachedResultName": "gpt-4.1-mini"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "18a994f5-2e75-4e26-8b74-2ccd523f9a3f",
"name": "E-commerce Orders & Customer Analysis",
"type": "n8n-nodes-base.googleSheetsTool",
"position": [
448,
336
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "YOUR_ECOMMERCE_GOOGLE_SHEET_TAB_URL",
"cachedResultName": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "YOUR_ECOMMERCE_GOOGLE_SHEET_ID",
"cachedResultUrl": "YOUR_ECOMMERCE_GOOGLE_SHEET_URL",
"cachedResultName": "E-commerce Orders & Customer Analysis"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.7
},
{
"id": "ea2ea688-6780-491a-a758-941f076ff583",
"name": "Edit Fields",
"type": "n8n-nodes-base.set",
"position": [
608,
0
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "c5e911e3-5aa2-4f6f-8433-50fa663bdf55",
"name": "response",
"type": "string",
"value": "={{ $json.output.replace(/\\\\n/g, '\\n') }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "ba4a4417-b727-45f1-a301-18e75c8f902b",
"name": "Chat",
"type": "@n8n/n8n-nodes-langchain.chat",
"position": [
944,
0
],
"parameters": {
"message": "={{ $json.response }}",
"options": {}
},
"typeVersion": 1.3
},
{
"id": "49a52a96-be4f-48f6-b506-93d84920f2b1",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1248,
-192
],
"parameters": {
"color": 5,
"width": 720,
"height": 208,
"content": "## Workflow\n\n1. User asks a business question and starts a conversation related to the data\n2. AI Agent starts its work\n3. Refers to the right dataset in Google Sheet\n4. Analyse the data and builds insights\n5. Edit Fields formats the response\n6. Chat response node sends back an insightful response to your question"
},
"typeVersion": 1
},
{
"id": "46a09736-3d8d-4624-9825-f5afbe951cf3",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-80,
-160
],
"parameters": {
"width": 512,
"height": 320,
"content": "Understands the question\nSelects the right Google Sheets tool\nRetrieves the data\nAnalyzes the data\nReturns the result in the required format"
},
"typeVersion": 1
},
{
"id": "a492f95a-e09a-4fb8-8e87-852912fa3c20",
"name": "Start Conversation",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-320,
0
],
"parameters": {
"options": {
"responseMode": "responseNodes"
}
},
"typeVersion": 1.4
},
{
"id": "433cca8d-cc1d-4c0a-98dc-d8839d629ca0",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
352,
240
],
"parameters": {
"width": 592,
"height": 272,
"content": "Use this tool to retrieve order-level e-commerce sales data, including customer, gender, payment method, product category, quantity, price, region, order status, and rating."
},
"typeVersion": 1
},
{
"id": "97d9370a-1d2e-48f0-8b4e-a95156684d58",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
464,
-112
],
"parameters": {
"width": 368,
"height": 272,
"content": "Converts the AI Agent\u2019s output field into a clean response field for the chat.\nThis expression helps convert escaped newline text into actual line breaks."
},
"typeVersion": 1
},
{
"id": "c2e2fbcb-72ec-48a6-9010-f4aa42b26e03",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
864,
-48
],
"parameters": {
"color": 4,
"width": 288,
"height": 208,
"content": "Responding back to the user"
},
"typeVersion": 1
},
{
"id": "d26295d7-99ec-451d-9d59-7662884067f3",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
-448,
240
],
"parameters": {
"color": 3,
"width": 336,
"height": 272,
"content": "Setup OpenAI connection.\n\n### Keep your API key private"
},
"typeVersion": 1
},
{
"id": "7c64a60a-fe05-4b9d-9af0-c12bd22f09fc",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-432,
-32
],
"parameters": {
"color": 4,
"width": 320,
"height": 192,
"content": "Start your conversation"
},
"typeVersion": 1
},
{
"id": "dcab4735-5b77-4907-b81c-02e1f7c17758",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-48,
240
],
"parameters": {
"width": 368,
"height": 272,
"content": "Stores past conversations to maintain context during the chat."
},
"typeVersion": 1
},
{
"id": "0b7810f9-1a49-4a7a-a5fa-76ebd96c0e4a",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1248,
-576
],
"parameters": {
"width": 720,
"height": 368,
"content": "# Business Data Analyst Chatbot\n\nThis workflow creates a chat-based business analyst assistant in n8n. The assistant can answer business questions by retrieving data from one or more connected Google Sheets datasets, analyzing the data, and returning a clean stakeholder-friendly response in chat.\n\n## Overview\n\nThe workflow allows a user to ask natural-language business questions such as:\n\n- How are PayPal orders distributed between men and women?\n- Which product category has the highest sales?\n- Which region has the highest return rate?\n- What are the top-performing products?\n- How does customer rating vary by sales channel?\n\nThe AI Agent dynamically selects the relevant Google Sheets tool, retrieves the spreadsheet data, performs the analysis, and returns a business-friendly answer."
},
"typeVersion": 1
},
{
"id": "962ab14a-1645-4173-888a-725dfd2eeb7d",
"name": "Marketing Campaign Performance Analysis",
"type": "n8n-nodes-base.googleSheetsTool",
"position": [
736,
336
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "YOUR_MARKETING_GOOGLE_SHEET_TAB_URL",
"cachedResultName": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "YOUR_MARKETING_GOOGLE_SHEET_ID",
"cachedResultUrl": "YOUR_MARKETING_GOOGLE_SHEET_URL",
"cachedResultName": "Marketing Campaign Performance Analysis"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.7
}
],
"connections": {
"AI Agent": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields": {
"main": [
[
{
"node": "Chat",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Start Conversation": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"E-commerce Orders & Customer Analysis": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Marketing Campaign Performance Analysis": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googleSheetsOAuth2ApiopenAiApi
Pro
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About this workflow
This workflow is a chat-based Business Data Analyst Chatbot built in n8n.
Source: https://n8n.io/workflows/15424/ — original creator credit. Request a take-down →
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