Simulate Business Decisions with Google Sheets, Gpt-4.1 and Slack

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 →

{
  "id": "Gcb0cNU03uh8EumM",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "name": "Simulate business decisions from Google Sheets with AI",
  "tags": [],
  "nodes": [
    {
      "id": "0c7c269d-42aa-458b-a43a-fd82490a2c3c",
      "name": "Sticky Note - Overview",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        0,
        0
      ],
      "parameters": {
        "width": 960,
        "height": 900,
        "content": "## AI Business Decision Simulator\n\nSimulate business decisions with AI before executing real workflows. Run \"what-if\" scenarios on pricing, campaigns, or hiring decisions using historical data.\n\n### Who's it for\n\u2022 Business analysts evaluating pricing strategies\n\u2022 Marketing teams planning campaigns before launch\n\u2022 HR/Ops teams assessing hiring decisions\n\u2022 Founders stress-testing business moves\n\n### How it works / What it does\n1. Accepts a what-if scenario via webhook or manual trigger\n2. Loads historical data from Google Sheets\n3. AI analyzes the scenario against past trends\n4. Simulates 3 possible outcomes (optimistic, realistic, pessimistic)\n5. Generates a decision recommendation report\n6. Logs the simulation result back to Google Sheets\n\n### How to set up\n1. Import this workflow\n2. Configure credentials (Google Sheets, OpenAI/Anthropic)\n3. Populate your historical data Google Sheet\n4. Activate the workflow\n\n### Requirements\n\u2022 Google Sheets (historical data + simulation log)\n\u2022 OpenAI / Anthropic / Grok API\n\u2022 n8n instance\n\n### How to customize\n\u2022 Adjust AI prompt for your industry/domain\n\u2022 Change scenario types in the filter node\n\u2022 Modify outcome columns in the Sheet logger\n\u2022 Add Slack/email notification after simulation"
      },
      "typeVersion": 1
    },
    {
      "id": "4c179fc5-b49c-4bfb-80de-2525005c110c",
      "name": "Sticky Note - Trigger",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1088,
        272
      ],
      "parameters": {
        "color": 4,
        "width": 780,
        "height": 480,
        "content": "## 1. Trigger & Scenario Intake"
      },
      "typeVersion": 1
    },
    {
      "id": "1543cb96-1966-4d5c-9949-b29fca94a6af",
      "name": "Sticky Note - Data",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1936,
        176
      ],
      "parameters": {
        "color": 3,
        "width": 916,
        "height": 620,
        "content": "## 2. Historical Data Fetch & Validation"
      },
      "typeVersion": 1
    },
    {
      "id": "35653b6c-8c8f-403e-bf97-d6fe314aa46d",
      "name": "Sticky Note - AI",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2960,
        224
      ],
      "parameters": {
        "color": 4,
        "width": 1124,
        "height": 600,
        "content": "## 3. AI Simulation & Output"
      },
      "typeVersion": 1
    },
    {
      "id": "9211debb-46f9-4cfc-92c7-cc83ea55fc64",
      "name": "Webhook - Scenario Input",
      "type": "n8n-nodes-base.webhook",
      "position": [
        1248,
        384
      ],
      "parameters": {
        "path": "simulate-business-decision",
        "options": {},
        "httpMethod": "POST",
        "responseMode": "responseNode"
      },
      "typeVersion": 1.1
    },
    {
      "id": "f5e4e82e-c743-4cdf-af15-c95f18f95bd5",
      "name": "Schedule - Weekly Simulation",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        1248,
        592
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "cronExpression",
              "expression": "0 9 * * 1"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "088b7232-87a8-4326-a005-30c568802b43",
      "name": "Prepare Scenario Context",
      "type": "n8n-nodes-base.set",
      "position": [
        1488,
        480
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "name": "scenarioType",
              "type": "string",
              "value": "={{ $json.scenarioType || $json.body?.scenarioType || 'pricing' }}"
            },
            {
              "name": "scenarioDescription",
              "type": "string",
              "value": "={{ $json.scenarioDescription || $json.body?.scenarioDescription || 'Increase product price by 15%' }}"
            },
            {
              "name": "targetMetric",
              "type": "string",
              "value": "={{ $json.targetMetric || $json.body?.targetMetric || 'revenue' }}"
            },
            {
              "name": "timeHorizon",
              "type": "string",
              "value": "={{ $json.timeHorizon || $json.body?.timeHorizon || '3 months' }}"
            },
            {
              "name": "simulationId",
              "type": "string",
              "value": "={{ 'SIM-' + Date.now().toString() }}"
            },
            {
              "name": "requestedAt",
              "type": "string",
              "value": "={{ new Date().toISOString() }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "d1fdd7e7-2ce4-492d-ab31-7356dfaf1633",
      "name": "Filter - Valid Scenario Types",
      "type": "n8n-nodes-base.filter",
      "position": [
        1728,
        480
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "conditions": [
            {
              "operator": {
                "type": "string",
                "operation": "regex"
              },
              "leftValue": "={{ $json.scenarioType }}",
              "rightValue": "^(pricing|campaign|hiring|expansion|discount|budget)$"
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "5fd08c46-b963-4af7-b06d-a78df9816a7f",
      "name": "Fetch Historical Data",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1968,
        384
      ],
      "parameters": {
        "url": "https://sheets.googleapis.com/v4/spreadsheets/YOUR_HISTORICAL_SHEET_ID/values/HistoricalData!A1:Z200?key=YOUR_TOKEN_HERE",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "94543f2e-dc7d-46a8-9712-57ebdbba8f12",
      "name": "Python - Parse & Summarize History",
      "type": "n8n-nodes-base.code",
      "position": [
        2208,
        480
      ],
      "parameters": {
        "mode": "runOnceForEachItem",
        "language": "python"
      },
      "typeVersion": 2
    },
    {
      "id": "4ca97fd1-23ca-4055-a11a-76a618628323",
      "name": "JS - Build Prompt Context",
      "type": "n8n-nodes-base.code",
      "position": [
        2512,
        480
      ],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "const item = $input.item.json;\n\n// Summarize scenario context for AI prompt\nconst historySummary = item.historySummary || 'No historical data available.';\n\nreturn {\n  json: {\n    ...item,\n    promptContext: {\n      scenarioType: item.scenarioType,\n      scenarioDescription: item.scenarioDescription,\n      targetMetric: item.targetMetric,\n      timeHorizon: item.timeHorizon,\n      historySummary\n    }\n  }\n};"
      },
      "typeVersion": 2
    },
    {
      "id": "96870305-1a8b-438c-895d-ab6c7cdfa00d",
      "name": "Wait - Rate Limit Buffer",
      "type": "n8n-nodes-base.wait",
      "position": [
        2688,
        480
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "f60c151c-cf5f-45b2-80d3-9dd3fbc78875",
      "name": "AI - Simulate Outcomes",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        3040,
        480
      ],
      "parameters": {
        "text": "=You are a senior business strategy consultant and data analyst. Simulate the following business decision using the historical performance data provided.\n\n---\n\n### Scenario Details\n- **Type**: {{ $json.scenarioType }}\n- **Decision**: {{ $json.scenarioDescription }}\n- **Target Metric**: {{ $json.targetMetric }}\n- **Time Horizon**: {{ $json.timeHorizon }}\n\n### Historical Data Summary\n{{ $json.historySummary || 'No historical data provided. Use general business benchmarks.' }}\n\n---\n\n### Instructions\nGenerate a structured what-if simulation with exactly 3 outcome scenarios:\n\n1. **Optimistic Outcome** \u2013 Best-case based on historical uptrends\n2. **Realistic Outcome** \u2013 Most probable based on average trends\n3. **Pessimistic Outcome** \u2013 Worst-case based on historical downturns\n\nFor each outcome, provide:\n- Projected change in {{ $json.targetMetric }} (%)\n- Key drivers / assumptions\n- Top 2 risks\n- Confidence score (0\u2013100%)\n\nEnd with a **Recommendation** (2\u20133 sentences) on whether to proceed, delay, or modify the decision.\n\nKeep the total response under 400 words. Use clear headers.",
        "options": {},
        "promptType": "define"
      },
      "typeVersion": 1.6
    },
    {
      "id": "4d7910ab-cef1-4439-bbbe-8f3cd4751028",
      "name": "JS - Format Simulation Report",
      "type": "n8n-nodes-base.code",
      "position": [
        3328,
        480
      ],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "const item = $input.item.json;\nconst aiOutput = item.output || item.text || item.response || 'Simulation could not be generated.';\n\n// Extract recommendation snippet (last paragraph heuristic)\nconst lines = aiOutput.split('\\n').filter(l => l.trim());\nconst recommendationLine = lines.find(l => l.toLowerCase().includes('recommendation')) || lines[lines.length - 1];\n\nreturn {\n  json: {\n    ...item,\n    simulationReport: aiOutput,\n    recommendationSummary: recommendationLine.replace(/[#*]/g, '').trim(),\n    status: 'Simulated',\n    completedAt: new Date().toISOString().split('T')[0]\n  }\n};"
      },
      "typeVersion": 2
    },
    {
      "id": "20bae7bb-7b16-49ab-b42e-73a17fc24488",
      "name": "Log Simulation to Google Sheet",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        3568,
        384
      ],
      "parameters": {
        "url": "https://sheets.googleapis.com/v4/spreadsheets/YOUR_LOG_SHEET_ID/values/SimulationLog!A1:append?valueInputOption=USER_ENTERED",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"values\": [[\n    \"{{ $json.simulationId }}\",\n    \"{{ $json.completedAt }}\",\n    \"{{ $json.scenarioType }}\",\n    \"{{ $json.scenarioDescription }}\",\n    \"{{ $json.targetMetric }}\",\n    \"{{ $json.timeHorizon }}\",\n    \"{{ $json.status }}\",\n    \"{{ $json.recommendationSummary }}\"\n  ]]\n}",
        "sendBody": true,
        "specifyBody": "json"
      },
      "typeVersion": 4.2
    },
    {
      "id": "b3006ad2-4685-490b-8d84-8ab65a619337",
      "name": "Notify via Slack",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        3568,
        592
      ],
      "parameters": {
        "url": "https://hooks.slack.com/services/YOUR_SLACK_WEBHOOK_URL",
        "method": "POST",
        "options": {},
        "jsonBody": "={\n  \"text\": \"*\ud83d\udcca Business Simulation Complete*\\n*ID:* {{ $json.simulationId }}\\n*Scenario:* {{ $json.scenarioDescription }}\\n*Recommendation:* {{ $json.recommendationSummary }}\\n*View full report in Google Sheets.*\"\n}",
        "sendBody": true,
        "specifyBody": "json"
      },
      "typeVersion": 4.2
    },
    {
      "id": "8b811db0-ae90-4515-a177-c085ff077121",
      "name": "Respond to Webhook",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [
        3808,
        480
      ],
      "parameters": {
        "options": {},
        "respondWith": "json",
        "responseBody": "={{ JSON.stringify({ simulationId: $json.simulationId, status: $json.status, report: $json.simulationReport, recommendation: $json.recommendationSummary }) }}"
      },
      "typeVersion": 1.1
    },
    {
      "id": "a25ae029-a46d-406a-a2b0-590b3c523c5e",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        3072,
        704
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {},
        "builtInTools": {}
      },
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1.3
    },
    {
      "id": "134a5439-78e9-42b3-b041-40b15fbc2761",
      "name": "Wait For Data",
      "type": "n8n-nodes-base.wait",
      "position": [
        2352,
        480
      ],
      "parameters": {
        "unit": "minutes",
        "amount": 1
      },
      "typeVersion": 1.1
    }
  ],
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "7a7240e4-25e5-4cad-b35e-b0ebc9068ff4",
  "connections": {
    "Wait For Data": {
      "main": [
        [
          {
            "node": "JS - Build Prompt Context",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI - Simulate Outcomes",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Fetch Historical Data": {
      "main": [
        [
          {
            "node": "Python - Parse & Summarize History",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "AI - Simulate Outcomes": {
      "main": [
        [
          {
            "node": "JS - Format Simulation Report",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Prepare Scenario Context": {
      "main": [
        [
          {
            "node": "Filter - Valid Scenario Types",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Wait - Rate Limit Buffer": {
      "main": [
        [
          {
            "node": "AI - Simulate Outcomes",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Webhook - Scenario Input": {
      "main": [
        [
          {
            "node": "Prepare Scenario Context",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "JS - Build Prompt Context": {
      "main": [
        [
          {
            "node": "Wait - Rate Limit Buffer",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Schedule - Weekly Simulation": {
      "main": [
        [
          {
            "node": "Prepare Scenario Context",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Filter - Valid Scenario Types": {
      "main": [
        [
          {
            "node": "Fetch Historical Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "JS - Format Simulation Report": {
      "main": [
        [
          {
            "node": "Log Simulation to Google Sheet",
            "type": "main",
            "index": 0
          },
          {
            "node": "Notify via Slack",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Log Simulation to Google Sheet": {
      "main": [
        [
          {
            "node": "Respond to Webhook",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Python - Parse & Summarize History": {
      "main": [
        [
          {
            "node": "Wait For Data",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Credentials you'll need

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• openAiApi

About this workflow

This workflow simulates business decision scenarios using Google Sheets data and AI analysis, generating what-if reports and recommendations for pricing, campaign, or hiring moves, and logs results to Google Sheets and Slack. Listens for incoming scenario requests via webhook or…

Source: https://n8n.io/workflows/16183/ — original creator credit. Request a take-down →

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