{ "edges": [ { "to": "89cfab60-7ffc-4f5d-990e-ec3f467ec4c8", "from": "1fc78f67-9545-498f-a358-b6e6f7ba5e4b", "toPort": "0", "fromPort": "0" }, { "to": "2e2d2d11-eab2-4c3a-a125-3851d339c15f", "from": "1fc78f67-9545-498f-a358-b6e6f7ba5e4b", "toPort": "0", "fromPort": "0" }, { "to": "a9d7e01b-156f-4a53-bf79-7c1c48a17291", "from": "1fc78f67-9545-498f-a358-b6e6f7ba5e4b", "toPort": "0", "fromPort": "0" }, { "to": "13d1eb98-12ce-4292-ab2b-9d249bf19c10", "from": "7a13da50-3454-4a18-bc47-80b44596cac0", "toPort": "0", "fromPort": "0" }, { "to": "1fc78f67-9545-498f-a358-b6e6f7ba5e4b", "from": "13d1eb98-12ce-4292-ab2b-9d249bf19c10", "toPort": "0", "fromPort": "0" }, { "to": "ca1d803a-9e5f-46a9-bd0f-18df642f0031", "from": "b99f6cc0-c4fe-46ac-bb19-bff96a989ee4", "toPort": "0", "fromPort": "0" }, { "to": "7a13da50-3454-4a18-bc47-80b44596cac0", "from": "ca1d803a-9e5f-46a9-bd0f-18df642f0031", "toPort": "0", "fromPort": "0" }, { "to": "ef590b98-aba5-43f4-813b-e5c69958cce2", "from": "5ab101bf-4c34-4a26-b186-55db6425c508", "toPort": "0", "fromPort": "0" }, { "to": "5ab101bf-4c34-4a26-b186-55db6425c508", "from": "a9d7e01b-156f-4a53-bf79-7c1c48a17291", "toPort": "0", "fromPort": "0" } ], "nodes": [ { "id": "b99f6cc0-c4fe-46ac-bb19-bff96a989ee4", "name": "Weekly Monday Trigger", "type": "trigger", "params": { "kind": "n8n-nodes-base.scheduleTrigger", "rule": { "interval": [ { "field": "cronExpression", "expression": "0 9 * * MON" } ] } }, "position": [ -400, 464 ] }, { "id": "ca1d803a-9e5f-46a9-bd0f-18df642f0031", "name": "Get Last 7 Days Orders", "type": "integration", "params": { "limit": 500, "options": {}, "service": "shopify", "operation": "getAll", "__originalType": "n8n-nodes-base.shopify" }, "position": [ -176, 464 ] }, { "id": "7a13da50-3454-4a18-bc47-80b44596cac0", "name": "Aggregate Sales Data", "type": "code", "params": { "jsCode": "// Aggregate order data for analysis\nconst orders = $input.all();\n\nlet totalRevenue = 0;\nlet orderCount = orders.length;\nlet productCounts = {};\nlet dailySales = {};\n\norders.forEach(order => {\n const orderData = order.json;\n \n // Calculate revenue\n totalRevenue += parseFloat(orderData.total_price || 0);\n \n // Track daily sales\n const date = orderData.created_at.split('T')[0];\n dailySales[date] = (dailySales[date] || 0) + parseFloat(orderData.total_price || 0);\n \n // Count products\n orderData.line_items?.forEach(item => {\n const productName = item.name;\n productCounts[productName] = (productCounts[productName] || 0) + item.quantity;\n });\n});\n\n// Get top 5 products\nconst topProducts = Object.entries(productCounts)\n .sort(([,a], [,b]) => b - a)\n .slice(0, 5)\n .map(([name, count]) => ({ name, quantity: count }));\n\n// Calculate average order value\nconst avgOrderValue = orderCount > 0 ? (totalRevenue / orderCount).toFixed(2) : 0;\n\n// Previous week for comparison (mock data - would typically come from sheets)\nconst previousWeekRevenue = totalRevenue * 0.95; // Simulated previous week\n\nreturn {\n totalRevenue: totalRevenue.toFixed(2),\n orderCount,\n avgOrderValue,\n topProducts,\n dailySales,\n previousWeekRevenue: previousWeekRevenue.toFixed(2),\n revenueChange: (((totalRevenue - previousWeekRevenue) / previousWeekRevenue) * 100).toFixed(1)\n};" }, "position": [ 0, 464 ] }, { "id": "13d1eb98-12ce-4292-ab2b-9d249bf19c10", "name": "Gemini Sales Analysis", "type": "http", "params": { "url": "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent", "method": "POST", "options": {}, "sendBody": true, "sendHeaders": true, "authentication": "genericCredentialType", "bodyParameters": { "parameters": [ { "name": "contents", "value": "=[{\"parts\":[{\"text\":\"Analyze this week's Shopify sales data and provide insights:\\n\\nTotal Revenue: ${{ $json.totalRevenue }}\\nOrder Count: {{ $json.orderCount }}\\nAverage Order Value: ${{ $json.avgOrderValue }}\\nRevenue Change from Last Week: {{ $json.revenueChange }}%\\n\\nTop Products:\\n{{ $json.topProducts.map(p => `${p.name}: ${p.quantity} sold`).join('\\n') }}\\n\\nDaily Sales:\\n{{ Object.entries($json.dailySales).map(([date, amount]) => `${date}: $${amount}`).join('\\n') }}\\n\\nPlease provide:\\n1. Key insights about sales performance\\n2. Trends you notice in the data\\n3. 2-3 actionable recommendations\\n4. Risk assessment if revenue declined\\n\\nFormat as JSON with keys: insights, trends, recommendations, risks\"}]}]" } ] }, "genericAuthType": "httpHeaderAuth", "headerParameters": { "parameters": [ { "name": "Content-Type", "value": "application/json" } ] } }, "position": [ 208, 464 ] }, { "id": "1fc78f67-9545-498f-a358-b6e6f7ba5e4b", "name": "Parse AI Response", "type": "set", "params": { "options": {}, "assignments": { "assignments": [ { "id": "analysis", "name": "aiInsights", "type": "object", "value": "={{ JSON.parse($json.candidates[0].content.parts[0].text) }}" }, { "id": "metrics", "name": "weeklyMetrics", "type": "object", "value": "={{ $('Aggregate Sales Data').item.json }}" } ] } }, "position": [ 400, 464 ] }, { "id": "89cfab60-7ffc-4f5d-990e-ec3f467ec4c8", "name": "Post to Slack Channel", "type": "integration", "params": { "text": "📊 **Weekly Sales Report** ({{ $now.minus({days: 7}).toFormat('MMM dd') }} - {{ $now.toFormat('MMM dd') }})\n\n**Metrics:**\n• Revenue: ${{ $json.weeklyMetrics.totalRevenue }} ({{ $json.weeklyMetrics.revenueChange }}%)\n• Orders: {{ $json.weeklyMetrics.orderCount }}\n• Avg Order Value: ${{ $json.weeklyMetrics.avgOrderValue }}\n\n**AI Insights:**\n{{ $json.aiInsights.insights }}\n\n**Trends:**\n{{ $json.aiInsights.trends }}\n\n**Recommendations:**\n{{ $json.aiInsights.recommendations }}", "select": "channel", "service": "slack", "channelId": { "__rl": true, "mode": "name", "value": "#sales" }, "operation": "read", "otherOptions": {} }, "position": [ 560, 464 ] }, { "id": "2e2d2d11-eab2-4c3a-a125-3851d339c15f", "name": "Email Report to Stakeholders", "type": "integration", "params": { "message": "

Weekly Sales Analysis

Period: {{ $now.minus({days: 7}).toFormat('MMM dd') }} - {{ $now.toFormat('MMM dd') }}

\n\n

Key Metrics

Total Revenue: ${{ $json.weeklyMetrics.totalRevenue }} ({{ $json.weeklyMetrics.revenueChange > 0 ? '+' : '' }}{{ $json.weeklyMetrics.revenueChange }}%)
Order Count: {{ $json.weeklyMetrics.orderCount }}
Average Order Value: ${{ $json.weeklyMetrics.avgOrderValue }}

\n\n

AI-Generated Insights

\n\n

Trends

\n\n

Recommendations

\n\n

Top Products This Week

${p.name}: ${p.quantity} sold

", "options": {}, "service": "gmail", "subject": "Weekly Sales Report - {{ $now.toFormat('MMM dd, yyyy') }}", "operation": "read" }, "position": [ 736, 464 ] }, { "id": "a9d7e01b-156f-4a53-bf79-7c1c48a17291", "name": "Log Metrics to Google Sheets", "type": "integration", "params": { "service": "googleSheets", "operation": "appendRow", "documentId": { "__rl": true, "mode": "id", "value": "your-spreadsheet-id" } }, "position": [ 560, 672 ] }, { "id": "5ab101bf-4c34-4a26-b186-55db6425c508", "name": "Check Revenue Drop >20%", "type": "if", "params": { "options": {}, "conditions": { "options": { "leftValue": "", "caseSensitive": true, "typeValidation": "strict" }, "combinator": "and", "conditions": [ { "id": "revenue-drop-check", "operator": { "type": "number", "operation": "lt" }, "leftValue": "={{ parseFloat($json.weeklyMetrics.revenueChange) }}", "rightValue": -20 } ] } }, "position": [ 736, 672 ] }, { "id": "ef590b98-aba5-43f4-813b-e5c69958cce2", "name": "Send Revenue Drop Alert", "type": "integration", "params": { "text": "🚨 **Revenue Alert** 🚨\n\nSignificant revenue drop detected!\n\n📉 This week: ${{ $json.weeklyMetrics.totalRevenue }}\n📊 Change: {{ $json.weeklyMetrics.revenueChange }}%\n\n**Immediate attention required:**\n• Review marketing campaigns\n• Check inventory levels\n• Analyze customer feedback\n• Consider promotional strategies\n\n**AI Risk Assessment:**\n{{ $json.aiInsights.risks || 'Review recommended for declining performance' }}", "select": "channel", "service": "slack", "channelId": { "__rl": true, "mode": "name", "value": "#alerts" }, "operation": "read", "otherOptions": {} }, "position": [ 960, 656 ] } ] }

Analyze Shopify orders with Gemini AI and send weekly Slack insights