Oneclick AI Squad This workflow corresponds to n8n.io template #5987 — we link there as the canonical source.
This workflow follows the Emailsend → HTTP Request 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 →
{
"id": "wOBVDQjh99n0BuRm",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Track Ingredient Price Trends & Get Smart Buying Suggestions via API, Database & Slack",
"tags": [],
"nodes": [
{
"id": "192d198b-cdfe-4356-a0f3-173f0ec4d5c5",
"name": "Daily Price Check",
"type": "n8n-nodes-base.cron",
"position": [
0,
100
],
"parameters": {},
"typeVersion": 1
},
{
"id": "c97114c9-4e78-4e13-94a2-1b4442b1e8da",
"name": "Fetch API Prices",
"type": "n8n-nodes-base.httpRequest",
"position": [
220,
0
],
"parameters": {
"url": "https://api.example-food-prices.com/ingredients",
"options": {}
},
"typeVersion": 4.1
},
{
"id": "a55e9aa2-4641-4f39-9e8c-e6b6498df4d3",
"name": "Store Price Data",
"type": "n8n-nodes-base.postgres",
"position": [
440,
100
],
"parameters": {
"table": "price_history",
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"columns": {
"0": "i",
"1": "n",
"2": "g",
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"value": {},
"schema": [],
"mappingMode": "autoMapInputData",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {}
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.4
},
{
"id": "448ff71f-7fee-40d8-a733-0f3d426cd8a2",
"name": "Calculate Trends",
"type": "n8n-nodes-base.postgres",
"position": [
660,
100
],
"parameters": {
"query": "WITH price_trends AS (\n SELECT \n ingredient,\n price,\n timestamp,\n LAG(price) OVER (PARTITION BY ingredient ORDER BY timestamp) as prev_price,\n LAG(timestamp) OVER (PARTITION BY ingredient ORDER BY timestamp) as prev_timestamp\n FROM price_history\n WHERE timestamp >= NOW() - INTERVAL '30 days'\n)\nSELECT \n ingredient,\n price as current_price,\n prev_price,\n CASE \n WHEN prev_price IS NULL THEN 0\n ELSE ((price - prev_price) / prev_price) * 100\n END as price_change_percent,\n timestamp,\n CASE \n WHEN price < prev_price THEN 'DECREASING'\n WHEN price > prev_price THEN 'INCREASING'\n ELSE 'STABLE'\n END as trend\nFROM price_trends\nWHERE prev_price IS NOT NULL\nORDER BY ingredient, timestamp DESC;",
"options": {},
"operation": "executeQuery"
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.4
},
{
"id": "61a33bca-5a1b-4525-b15a-67493c313613",
"name": "Generate Recommendations",
"type": "n8n-nodes-base.code",
"position": [
880,
100
],
"parameters": {
"jsCode": "// Analyze trends and generate buying recommendations\nconst items = $input.all();\nconst recommendations = [];\n\nfor (const item of items) {\n const data = item.json;\n let recommendation = {\n ingredient: data.ingredient,\n current_price: data.current_price,\n price_change_percent: data.price_change_percent,\n trend: data.trend,\n recommendation: '',\n urgency: '',\n reason: ''\n };\n \n // Generate recommendations based on price trends\n if (data.price_change_percent < -10) {\n recommendation.recommendation = 'BUY NOW';\n recommendation.urgency = 'HIGH';\n recommendation.reason = `Price dropped by ${Math.abs(data.price_change_percent).toFixed(1)}% - excellent buying opportunity`;\n } else if (data.price_change_percent < -5) {\n recommendation.recommendation = 'CONSIDER BUYING';\n recommendation.urgency = 'MEDIUM';\n recommendation.reason = `Price decreased by ${Math.abs(data.price_change_percent).toFixed(1)}% - good time to stock up`;\n } else if (data.price_change_percent > 15) {\n recommendation.recommendation = 'AVOID BUYING';\n recommendation.urgency = 'HIGH';\n recommendation.reason = `Price increased by ${data.price_change_percent.toFixed(1)}% - wait for better prices`;\n } else if (data.price_change_percent > 5) {\n recommendation.recommendation = 'WAIT';\n recommendation.urgency = 'MEDIUM';\n recommendation.reason = `Price increased by ${data.price_change_percent.toFixed(1)}% - consider delaying purchase`;\n } else {\n recommendation.recommendation = 'MONITOR';\n recommendation.urgency = 'LOW';\n recommendation.reason = 'Price stable - normal purchasing timing';\n }\n \n recommendations.push(recommendation);\n}\n\nreturn recommendations.map(rec => ({ json: rec }));"
},
"typeVersion": 2
},
{
"id": "c1d236c2-059c-48da-a767-bb4d18772c05",
"name": "Store Recommendations",
"type": "n8n-nodes-base.postgres",
"position": [
1100,
100
],
"parameters": {
"table": "buying_recommendations",
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"columns": {
"0": "i",
"1": "n",
"2": "g",
"3": "r",
"4": "e",
"5": "d",
"6": "i",
"7": "e",
"8": "n",
"9": "t",
"10": ",",
"11": " ",
"12": "c",
"13": "u",
"14": "r",
"15": "r",
"16": "e",
"17": "n",
"18": "t",
"19": "_",
"20": "p",
"21": "r",
"22": "i",
"23": "c",
"24": "e",
"25": ",",
"26": " ",
"27": "p",
"28": "r",
"29": "i",
"30": "c",
"31": "e",
"32": "_",
"33": "c",
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"36": "n",
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"value": {},
"schema": [],
"mappingMode": "autoMapInputData",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {}
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.4
},
{
"id": "298a4e63-584c-472a-af2b-320cc5278529",
"name": "Get Dashboard Data",
"type": "n8n-nodes-base.postgres",
"position": [
1320,
100
],
"parameters": {
"query": "SELECT \n ingredient,\n current_price,\n price_change_percent,\n trend,\n recommendation,\n urgency,\n reason,\n generated_at\nFROM buying_recommendations \nWHERE generated_at >= CURRENT_DATE\nORDER BY \n CASE urgency \n WHEN 'HIGH' THEN 1 \n WHEN 'MEDIUM' THEN 2 \n WHEN 'LOW' THEN 3 \n END,\n price_change_percent ASC;",
"options": {},
"operation": "executeQuery"
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.4
},
{
"id": "656ed3fc-386b-4fb1-b34e-a558ad8a3edf",
"name": "Generate Dashboard HTML",
"type": "n8n-nodes-base.code",
"position": [
1540,
100
],
"parameters": {
"jsCode": "// Create HTML dashboard\nconst items = $input.all();\nconst data = items.map(item => item.json);\n\nconst html = `\n<!DOCTYPE html>\n<html>\n<head>\n <title>Price Fluctuation Dashboard</title>\n <style>\n body { font-family: Arial, sans-serif; margin: 20px; background-color: #f5f5f5; }\n .container { max-width: 1200px; margin: 0 auto; }\n .header { background: #2c3e50; color: white; padding: 20px; border-radius: 8px; margin-bottom: 20px; }\n .card { background: white; padding: 20px; margin: 10px 0; border-radius: 8px; box-shadow: 0 2px 4px rgba(0,0,0,0.1); }\n .high-urgency { border-left: 5px solid #e74c3c; }\n .medium-urgency { border-left: 5px solid #f39c12; }\n .low-urgency { border-left: 5px solid #27ae60; }\n .price-info { display: flex; justify-content: space-between; align-items: center; }\n .price-change { font-weight: bold; }\n .positive { color: #e74c3c; }\n .negative { color: #27ae60; }\n .recommendation { font-size: 1.1em; font-weight: bold; }\n .buy-now { color: #27ae60; }\n .consider-buying { color: #f39c12; }\n .wait, .avoid-buying { color: #e74c3c; }\n .monitor { color: #3498db; }\n .summary { display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 20px; margin-bottom: 20px; }\n .stat-card { background: #3498db; color: white; text-align: center; padding: 20px; border-radius: 8px; }\n </style>\n</head>\n<body>\n <div class=\"container\">\n <div class=\"header\">\n <h1>\ud83c\udf7d\ufe0f Price Fluctuation Dashboard</h1>\n <p>Food Industry Ingredient Price Monitoring & Buying Recommendations</p>\n <p>Last Updated: ${new Date().toLocaleString()}</p>\n </div>\n \n <div class=\"summary\">\n <div class=\"stat-card\">\n <h3>${data.filter(d => d.urgency === 'HIGH').length}</h3>\n <p>High Priority Items</p>\n </div>\n <div class=\"stat-card\">\n <h3>${data.filter(d => d.recommendation === 'BUY NOW').length}</h3>\n <p>Buy Now Opportunities</p>\n </div>\n <div class=\"stat-card\">\n <h3>${data.filter(d => d.trend === 'DECREASING').length}</h3>\n <p>Decreasing Prices</p>\n </div>\n <div class=\"stat-card\">\n <h3>${data.filter(d => d.trend === 'INCREASING').length}</h3>\n <p>Increasing Prices</p>\n </div>\n </div>\n \n <div class=\"recommendations\">\n ${data.map(item => `\n <div class=\"card ${item.urgency.toLowerCase()}-urgency\">\n <div class=\"price-info\">\n <div>\n <h3>${item.ingredient}</h3>\n <p class=\"recommendation ${item.recommendation.toLowerCase().replace(/\\s+/g, '-')}\">\n ${item.recommendation}\n </p>\n </div>\n <div>\n <div>Current Price: $${item.current_price}</div>\n <div class=\"price-change ${item.price_change_percent < 0 ? 'negative' : 'positive'}\">\n ${item.price_change_percent > 0 ? '+' : ''}${item.price_change_percent.toFixed(1)}%\n </div>\n <div>Trend: ${item.trend}</div>\n </div>\n </div>\n <div style=\"margin-top: 10px; padding: 10px; background: #f8f9fa; border-radius: 4px;\">\n <strong>Reason:</strong> ${item.reason}\n </div>\n <div style=\"margin-top: 5px; font-size: 0.9em; color: #666;\">\n <strong>Urgency:</strong> ${item.urgency}\n </div>\n </div>\n `).join('')}\n </div>\n </div>\n</body>\n</html>\n`;\n\nreturn [{ json: { html: html } }];"
},
"typeVersion": 2
},
{
"id": "804a042f-f37f-426e-8f0f-334b8358a34e",
"name": "Send Email Report",
"type": "n8n-nodes-base.emailSend",
"position": [
1760,
0
],
"parameters": {
"options": {
"attachments": "data:text/html;base64,{{ $json.html | base64 }}"
},
"subject": "Daily Price Fluctuation Report - {{ $now.format('YYYY-MM-DD') }}",
"toEmail": "user@example.com",
"fromEmail": "user@example.com"
},
"credentials": {
"smtp": {
"name": "<your credential>"
}
},
"typeVersion": 2.1
},
{
"id": "357cc9b4-9d9c-4e25-b5b4-8cf9c233e2ed",
"name": "Send Slack Alert",
"type": "n8n-nodes-base.httpRequest",
"position": [
1760,
200
],
"parameters": {
"url": "https://hooks.slack.com/services/YOUR/SLACK/WEBHOOK",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "text",
"value": "\ud83c\udf7d\ufe0f Daily Price Update: {{ $('Get Dashboard Data').all().filter(item => item.json.urgency === 'HIGH').length }} high priority items need attention!"
},
{
"name": "attachments",
"value": "={{ $('Get Dashboard Data').all().filter(item => item.json.urgency === 'HIGH').map(item => ({ color: item.json.recommendation === 'BUY NOW' ? 'good' : 'danger', fields: [{ title: item.json.ingredient, value: `${item.json.recommendation} - ${item.json.reason}`, short: false }] })) }}"
}
]
}
},
"typeVersion": 4.1
},
{
"id": "5aef607f-be87-4792-a423-e17cc4410e02",
"name": "Setup Database",
"type": "n8n-nodes-base.postgres",
"position": [
220,
200
],
"parameters": {
"query": "CREATE TABLE IF NOT EXISTS price_history (\n id SERIAL PRIMARY KEY,\n ingredient VARCHAR(100) NOT NULL,\n price DECIMAL(10,2) NOT NULL,\n unit VARCHAR(50) NOT NULL,\n supplier VARCHAR(100),\n timestamp TIMESTAMP NOT NULL,\n created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP\n);\n\nCREATE TABLE IF NOT EXISTS buying_recommendations (\n id SERIAL PRIMARY KEY,\n ingredient VARCHAR(100) NOT NULL,\n current_price DECIMAL(10,2) NOT NULL,\n price_change_percent DECIMAL(5,2),\n trend VARCHAR(20),\n recommendation VARCHAR(50),\n urgency VARCHAR(20),\n reason TEXT,\n generated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP\n);\n\nCREATE INDEX IF NOT EXISTS idx_price_history_ingredient_timestamp ON price_history(ingredient, timestamp);\nCREATE INDEX IF NOT EXISTS idx_recommendations_generated_at ON buying_recommendations(generated_at);",
"options": {},
"operation": "executeQuery"
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.4
},
{
"id": "d84be769-2983-45a2-854c-d7bd972ecc36",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
380,
-560
],
"parameters": {
"width": 1000,
"height": 520,
"content": "## \ud83d\udccc Workflow Overview: Price Fluctuation Dashboard\n\n- Daily Price Check \u2013 Triggers the workflow daily to monitor price changes.\n\n- Fetch API Prices \u2013 Retrieves the latest prices from an external API.\n\n- Setup Database \u2013 Ensures database tables are ready before inserting data.\n\n- Store Price Data \u2013 Saves current prices to the database for tracking.\n\n- Calculate Trends \u2013 Analyzes historical prices to detect patterns.\n\n- Generate Recommendations \u2013 Suggests actions based on price trends (e.g., buy/sell).\n\n- Store Recommendations \u2013 Saves recommendations for future reporting.\n\n- Get Dashboard Data \u2013 Gathers the necessary data for dashboard generation.\n\n- Generate Dashboard HTML \u2013 Builds an HTML dashboard to visualize insights.\n\n- Send Email Report \u2013 Emails the dashboard report to users.\n\n- Send Slack Alert \u2013 Sends key alerts or recommendations to Slack channels."
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "38fb136e-f3ea-4656-91fd-ecd473469990",
"connections": {
"Setup Database": {
"main": [
[
{
"node": "Store Price Data",
"type": "main",
"index": 0
}
]
]
},
"Calculate Trends": {
"main": [
[
{
"node": "Generate Recommendations",
"type": "main",
"index": 0
}
]
]
},
"Fetch API Prices": {
"main": [
[
{
"node": "Store Price Data",
"type": "main",
"index": 0
}
]
]
},
"Store Price Data": {
"main": [
[
{
"node": "Calculate Trends",
"type": "main",
"index": 0
}
]
]
},
"Daily Price Check": {
"main": [
[
{
"node": "Fetch API Prices",
"type": "main",
"index": 0
},
{
"node": "Setup Database",
"type": "main",
"index": 0
}
]
]
},
"Get Dashboard Data": {
"main": [
[
{
"node": "Generate Dashboard HTML",
"type": "main",
"index": 0
}
]
]
},
"Store Recommendations": {
"main": [
[
{
"node": "Get Dashboard Data",
"type": "main",
"index": 0
}
]
]
},
"Generate Dashboard HTML": {
"main": [
[
{
"node": "Send Email Report",
"type": "main",
"index": 0
},
{
"node": "Send Slack Alert",
"type": "main",
"index": 0
}
]
]
},
"Generate Recommendations": {
"main": [
[
{
"node": "Store Recommendations",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
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About this workflow
This automated n8n workflow monitors ingredient price changes from external APIs or manual sources, analyzes historical trends, and provides smart buying recommendations. The system tracks price fluctuations in a PostgreSQL database, generates actionable insights, and sends…
Source: https://n8n.io/workflows/5987/ — original creator credit. Request a take-down →
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