Online Marketing Weekly Report
工作流概述
这是一个包含51个节点的复杂工作流，主要用于自动化处理各种任务。
工作流源代码
{
"id": "knmxcsujuHmViJl4",
"meta": {
"instanceId": "558d88703fb65b2d0e44613bc35916258b0f0bf983c5d4730c00c424b77ca36a"
},
"name": "Online Marketing Weekly Report",
"tags": [],
"nodes": [
{
"id": "f145b442-3036-4769-b7ad-62c97fa5d662",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-1580,
-220
],
"parameters": {
"rule": {
"interval": [
{
"field": "weeks",
"triggerAtDay": [
1
],
"triggerAtHour": 7
}
]
}
},
"typeVersion": 1.2
},
{
"id": "9b25dfe7-cabe-4051-8d03-5f9b1f42621a",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-1380,
120
],
"parameters": {
"model": "gpt-4o",
"options": {}
},
"credentials": {
"openAiApi": {
"id": "niikB3HA4fT5WAqt",
"name": "OpenAi account"
}
},
"typeVersion": 1
},
{
"id": "f04d67a6-fb37-434d-8fd7-988db33f8cde",
"name": "Google_Ads",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-400,
120
],
"parameters": {
"name": "Google_Ads",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "nRGs7Ogv7eU1mJQl",
"cachedResultName": "Google Ads Report: Weekly Subflow ROAS"
},
"description": "Call this tool to get the output of the Google Ads Workflow"
},
"typeVersion": 1.3
},
{
"id": "179c2464-bf17-4a9b-8c5b-508a4acf746f",
"name": "Meta_Ads",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-300,
120
],
"parameters": {
"name": "Meta_Ads",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "9sC80Rt1eqgrfphk",
"cachedResultName": "Meta Ads Report: Weekly Subflow ROAS"
},
"description": "Call this tool to get the output of the Meta Ads Workflow"
},
"typeVersion": 1.3
},
{
"id": "f963f694-cf30-4b81-9ee1-3ad383714770",
"name": "Analytics_Domain_1",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-1180,
120
],
"parameters": {
"name": "EP_Data",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "ploQFf5BtgCC6ryu",
"cachedResultName": "GA Report: EP Subflow Weekly"
},
"description": "Call this tool to get the output of the SER Data Workflow"
},
"typeVersion": 1.3
},
{
"id": "093d83fd-6788-418b-ac38-925b04be2515",
"name": "Analytics_Domain_3",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-860,
120
],
"parameters": {
"name": "SBW_Data",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "ECmFUVocSLqB3afJ",
"cachedResultName": "GA Report: SBW Subflow Weekly"
},
"description": "Call this tool to get the output of the SBW Data Workflow"
},
"typeVersion": 1.3
},
{
"id": "57612276-4a48-4a6c-997c-f6c4f1196ed7",
"name": "Analytics_Domain_2",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-1020,
120
],
"parameters": {
"name": "SER_Data",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "EWAE7Qx70cHZuXte",
"cachedResultName": "GA Report: SER Subflow Weekly"
},
"description": "Call this tool to get the output of the SER Data Workflow"
},
"typeVersion": 1.3
},
{
"id": "3dfea4cf-87fb-44d5-9b95-304406da6b18",
"name": "Analytics_Domain_4",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-700,
120
],
"parameters": {
"name": "SZO_Data",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "eyPh3eaqrBLAcLKF",
"cachedResultName": "GA Report: SZO Subflow Weekly"
},
"description": "Call this tool to get the output of the SZO Data Workflow"
},
"typeVersion": 1.3
},
{
"id": "79f1cd20-6133-4c72-8942-5b1f55adbb7f",
"name": "Analytics_Domain_5",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
-540,
120
],
"parameters": {
"name": "UCH_Data",
"workflowId": {
"__rl": true,
"mode": "list",
"value": "ErIeoUuyF4fqMbhL",
"cachedResultName": "GA Report: UCH Subflow Weekly"
},
"description": "Call this tool to get the output of the UCH Data Workflow"
},
"typeVersion": 1.3
},
{
"id": "0740d70f-a582-4a12-ab12-08b46504e8f8",
"name": "Execute Workflow Trigger",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
-1580,
460
],
"parameters": {},
"typeVersion": 1
},
{
"id": "2449b1be-0ba8-41ae-9ea5-86028da736f0",
"name": "Calculator",
"type": "@n8n/n8n-nodes-langchain.toolCalculator",
"position": [
380,
680
],
"parameters": {},
"typeVersion": 1
},
{
"id": "e8b884f1-2013-4c25-a641-8181528db173",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1660,
360
],
"parameters": {
"color": 6,
"width": 2340,
"height": 460,
"content": "## Sub-Workflow: Google Analytics Data"
},
"typeVersion": 1
},
{
"id": "f7d290eb-07d1-413d-ba12-184229e519c0",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1660,
1440
],
"parameters": {
"color": 5,
"width": 2340,
"height": 460,
"content": "## Sub-Workflow: Meta Ads Data"
},
"typeVersion": 1
},
{
"id": "c78da3ec-fb47-4373-8850-e1af89d7330e",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1660,
-280
],
"parameters": {
"width": 2340,
"height": 540,
"content": "## Main Workflow: Weekly Report Assistant"
},
"typeVersion": 1
},
{
"id": "79ae6b22-0067-4d51-bc64-e0360d2096f3",
"name": "Calculator1",
"type": "@n8n/n8n-nodes-langchain.toolCalculator",
"position": [
440,
1200
],
"parameters": {},
"typeVersion": 1
},
{
"id": "d7608c67-4b10-4860-b683-de265b95cb03",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1660,
880
],
"parameters": {
"color": 4,
"width": 2340,
"height": 500,
"content": "## Sub-Workflow: Google Ads Data"
},
"typeVersion": 1
},
{
"id": "c047cc54-1598-4294-a398-cdb23ea8be4d",
"name": "Calculator3",
"type": "@n8n/n8n-nodes-langchain.toolCalculator",
"position": [
460,
1760
],
"parameters": {},
"typeVersion": 1
},
{
"id": "165717a8-b215-4e0e-a5e9-586feaec261e",
"name": "Call Google Analytics data: Last 7 days",
"type": "n8n-nodes-base.googleAnalytics",
"position": [
-1320,
460
],
"parameters": {
"metricsGA4": {
"metricValues": [
{
"listName": "screenPageViews"
},
{},
{
"listName": "sessions"
},
{
"listName": "sessionsPerUser"
},
{
"name": "averageSessionDuration",
"listName": "other"
},
{
"name": "ecommercePurchases",
"listName": "other"
},
{
"name": "averagePurchaseRevenue",
"listName": "other"
},
{
"name": "purchaseRevenue",
"listName": "other"
}
]
},
"propertyId": {
"__rl": true,
"mode": "list",
"value": "345060083",
"cachedResultUrl": "https://analytics.google.com/analytics/web/#/p345060083/",
"cachedResultName": "https://www.ep-reisen.de – GA4"
},
"dimensionsGA4": {
"dimensionValues": [
{}
]
},
"additionalFields": {}
},
"credentials": {
"googleAnalyticsOAuth2": {
"id": "KJj8aAwdrmU2STrI",
"name": "Google Analytics account"
}
},
"typeVersion": 2
},
{
"id": "da636e2a-4396-4809-98ea-c04abdfc6b73",
"name": "Call Google Analytics data: Last 7 days (previous year)",
"type": "n8n-nodes-base.googleAnalytics",
"position": [
-400,
460
],
"parameters": {
"endDate": "={{ $json.endDate }}",
"dateRange": "custom",
"startDate": "={{ $json.startDate }}",
"metricsGA4": {
"metricValues": [
{
"listName": "screenPageViews"
},
{},
{
"listName": "sessions"
},
{
"listName": "sessionsPerUser"
},
{
"name": "averageSessionDuration",
"listName": "other"
},
{
"name": "ecommercePurchases",
"listName": "other"
},
{
"name": "averagePurchaseRevenue",
"listName": "other"
},
{
"name": "purchaseRevenue",
"listName": "other"
}
]
},
"propertyId": {
"__rl": true,
"mode": "list",
"value": "345060083",
"cachedResultUrl": "https://analytics.google.com/analytics/web/#/p345060083/",
"cachedResultName": "https://www.ep-reisen.de – GA4"
},
"dimensionsGA4": {
"dimensionValues": [
{}
]
},
"additionalFields": {}
},
"credentials": {
"googleAnalyticsOAuth2": {
"id": "KJj8aAwdrmU2STrI",
"name": "Google Analytics account"
}
},
"typeVersion": 2
},
{
"id": "f1ac5ff4-1b09-442f-96b0-4f1562dffebb",
"name": "Calculation same period previous year",
"type": "n8n-nodes-base.code",
"position": [
-620,
980
],
"parameters": {
"jsCode": "// Aktuelles Datum
const today = new Date();
// Berechnung des Enddatums (letzter Tag vor dem aktuellen Datum im Vorjahr)
const end = new Date(today.getFullYear() - 1, today.getMonth(), today.getDate() - 1);
// Berechnung des Startdatums (7 Tage vor dem Enddatum)
const start = new Date(end);
start.setDate(end.getDate() - 6);
// Formatierung zu YYYYMMDD
function formatDate(date) {
const year = date.getFullYear();
const month = String(date.getMonth() + 1).padStart(2, '0');
const day = String(date.getDate()).padStart(2, '0');
return `${year}${month}${day}`;
}
// Ausgabe
const startDate = formatDate(start);
const endDate = formatDate(end);
return {
startDate,
endDate
};"
},
"typeVersion": 2
},
{
"id": "bc224327-ca75-451a-841f-7cd8c59c5925",
"name": "Format data input (previous year)",
"type": "n8n-nodes-base.code",
"position": [
-240,
980
],
"parameters": {
"jsCode": "const inputData = items[0].json.results;
const totals = {
impressions: 0,
clicks: 0,
conversions: 0,
costMicros: 0,
conversionsValue: 0
};
inputData.forEach(campaign => {
totals.impressions += parseInt(campaign.metrics.impressions) || 0;
totals.clicks += parseInt(campaign.metrics.clicks) || 0;
totals.conversions += parseFloat(campaign.metrics.conversions) || 0;
totals.costMicros += parseInt(campaign.metrics.costMicros) || 0;
totals.conversionsValue += parseFloat(campaign.metrics.conversionsValue) || 0;
});
const results = {
impressions: totals.impressions,
clicks: totals.clicks,
conversions: totals.conversions,
cost_micros: totals.costMicros,
ctr: totals.clicks / totals.impressions,
cost_per_conversion: totals.costMicros / totals.conversions,
cpm: (totals.costMicros / (totals.impressions / 1000)),
roas: totals.conversionsValue / (totals.costMicros / 1000000)
};
return results;"
},
"typeVersion": 2
},
{
"id": "5b9dbc30-4a92-43d2-b9bf-477141aa4024",
"name": "Format data input (current year)",
"type": "n8n-nodes-base.code",
"position": [
-1200,
980
],
"parameters": {
"jsCode": "const inputData = items[0].json.results;
const totals = {
impressions: 0,
clicks: 0,
conversions: 0,
costMicros: 0,
conversionsValue: 0
};
inputData.forEach(campaign => {
totals.impressions += parseInt(campaign.metrics.impressions) || 0;
totals.clicks += parseInt(campaign.metrics.clicks) || 0;
totals.conversions += parseFloat(campaign.metrics.conversions) || 0;
totals.costMicros += parseInt(campaign.metrics.costMicros) || 0;
totals.conversionsValue += parseFloat(campaign.metrics.conversionsValue) || 0;
});
const results = {
impressions: totals.impressions,
clicks: totals.clicks,
conversions: totals.conversions,
cost_micros: totals.costMicros,
ctr: totals.clicks / totals.impressions,
cost_per_conversion: totals.costMicros / totals.conversions,
cpm: (totals.costMicros / (totals.impressions / 1000)),
roas: totals.conversionsValue / (totals.costMicros / 1000000)
};
return results;"
},
"typeVersion": 2
},
{
"id": "fdb70b1a-8891-469f-9920-3623cb40760e",
"name": "Assign data from input (current year)",
"type": "n8n-nodes-base.set",
"position": [
-1020,
980
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9c2f8b9a-e964-49a0-8837-efb0dfd7bcae",
"name": "Impressions",
"type": "number",
"value": "={{ $json.impressions }}"
},
{
"id": "8b524518-1268-4971-b5c9-ae7da09d94f9",
"name": "CPM",
"type": "number",
"value": "={{ $json.cpm }}"
},
{
"id": "ca7279b9-c643-425f-aa99-cb17146e9994",
"name": "Clicks",
"type": "number",
"value": "={{ $json.clicks }}"
},
{
"id": "591288f7-e8cf-445e-872a-5b83f997b825",
"name": "CTR",
"type": "number",
"value": "={{ $json.ctr }}"
},
{
"id": "dc1a43da-3f3a-4dca-bbde-904222d7f693",
"name": "Conversions",
"type": "number",
"value": "={{ $json.conversions }}"
},
{
"id": "eac0b53e-c452-40b8-92bc-8af8ea349984",
"name": "=Cost per Conversion",
"type": "number",
"value": "={{ $json.cost_per_conversion }}"
},
{
"id": "4b5d569a-26c9-4a2f-be48-6814860d33c1",
"name": "ROAS",
"type": "number",
"value": "={{ $json.roas }}"
},
{
"id": "b96439be-189d-4ebe-b49e-d5c31fefe9f0",
"name": "Spend",
"type": "number",
"value": "={{ $json.cost_micros }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "bef77ef4-b6ef-48c3-b0b7-5a12a3f75b05",
"name": "Summarize input (current year)",
"type": "n8n-nodes-base.summarize",
"position": [
-820,
980
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "Impressions",
"aggregation": "sum"
},
{
"field": "CPM",
"aggregation": "average"
},
{
"field": "Clicks",
"aggregation": "sum"
},
{
"field": "CTR",
"aggregation": "average"
},
{
"field": "Conversions",
"aggregation": "sum"
},
{
"field": "Cost per Conversion",
"aggregation": "average"
},
{
"field": "Spend",
"aggregation": "sum"
},
{
"field": "ROAS",
"aggregation": "average"
}
]
}
},
"typeVersion": 1
},
{
"id": "2be072fe-24fd-47f5-8026-31b98666de84",
"name": "Assign input (previous year)",
"type": "n8n-nodes-base.set",
"position": [
-80,
980
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9c2f8b9a-e964-49a0-8837-efb0dfd7bcae",
"name": "Impressions",
"type": "number",
"value": "={{ $json.impressions }}"
},
{
"id": "8b524518-1268-4971-b5c9-ae7da09d94f9",
"name": "CPM",
"type": "number",
"value": "={{ $json.cpm }}"
},
{
"id": "ca7279b9-c643-425f-aa99-cb17146e9994",
"name": "Clicks",
"type": "number",
"value": "={{ $json.clicks }}"
},
{
"id": "591288f7-e8cf-445e-872a-5b83f997b825",
"name": "CTR",
"type": "number",
"value": "={{ $json.ctr }}"
},
{
"id": "dc1a43da-3f3a-4dca-bbde-904222d7f693",
"name": "Conversions",
"type": "number",
"value": "={{ $json.conversions }}"
},
{
"id": "eac0b53e-c452-40b8-92bc-8af8ea349984",
"name": "=Cost per conversion",
"type": "number",
"value": "={{ $json.cost_per_conversion }}"
},
{
"id": "76bda144-0cb4-4614-a658-ddb31726ecb9",
"name": "ROAS",
"type": "number",
"value": "={{ $json.roas }}"
},
{
"id": "b96439be-189d-4ebe-b49e-d5c31fefe9f0",
"name": "Spend",
"type": "number",
"value": "={{ $json.cost_micros }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "87381409-c9e5-4d1f-a118-a9e592fa8805",
"name": "Summarize input (previous year)",
"type": "n8n-nodes-base.summarize",
"position": [
100,
980
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "Impressions",
"aggregation": "sum"
},
{
"field": "CPM",
"aggregation": "average"
},
{
"field": "Clicks",
"aggregation": "sum"
},
{
"field": "CTR",
"aggregation": "average"
},
{
"field": "Conversions",
"aggregation": "sum"
},
{
"field": "Cost per conversion",
"aggregation": "average"
},
{
"field": "Spend",
"aggregation": "sum"
},
{
"field": "ROAS",
"aggregation": "average"
}
]
}
},
"typeVersion": 1
},
{
"id": "000507e0-7806-4686-b157-56e9d58bd9db",
"name": "Calculate date format for Google Ads request (last 7 days)",
"type": "n8n-nodes-base.code",
"position": [
-1600,
980
],
"parameters": {
"jsCode": "// Aktuelles Datum
const today = new Date();
// Berechnung des Enddatums (letzter Tag vor dem aktuellen Datum)
const end = new Date(today);
end.setDate(today.getDate() - 1);
// Berechnung des Startdatums (7 Tage vor dem Enddatum)
const start = new Date(end);
start.setDate(end.getDate() - 6);
// Formatierung zu YYYYMMDD
function formatDate(date) {
const year = date.getFullYear();
const month = String(date.getMonth() + 1).padStart(2, '0');
const day = String(date.getDate()).padStart(2, '0');
return `${year}${month}${day}`;
}
// Ausgabe
const startDate = formatDate(start);
const endDate = formatDate(end);
return { startDate, endDate };"
},
"typeVersion": 2
},
{
"id": "a1b4d36a-c322-4771-bcf3-226870fcf000",
"name": "Call Google Ads Data: Last 7 days",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1380,
980
],
"parameters": {
"url": "https://googleads.googleapis.com/v17/customers/3300525230/googleAds:search",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "query",
"value": "=SELECT
campaign.name,
metrics.impressions,
metrics.average_cpm,
metrics.clicks,
metrics.ctr,
metrics.conversions,
metrics.cost_per_conversion,
metrics.cost_micros,
metrics.conversions_value
FROM campaign
WHERE segments.date >= '{{ $json.startDate }}' AND segments.date <= '{{ $json.endDate }}'"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "developer-token",
"value": "fzQ2U5IcU4ZH0vBDn4Slww"
}
]
},
"nodeCredentialType": "googleAdsOAuth2Api"
},
"credentials": {
"googleOAuth2Api": {
"id": "yNLz0qjgW7jN4Osv",
"name": "Google account"
},
"googleAdsOAuth2Api": {
"id": "gEPlb6nlwRX35x6R",
"name": "Google Ads account"
}
},
"typeVersion": 4.2
},
{
"id": "7246c0af-4e9d-4037-bc1d-c4fd16aae7d3",
"name": "Call Google Ads Data: Last 7 days (previous year)",
"type": "n8n-nodes-base.httpRequest",
"position": [
-420,
980
],
"parameters": {
"url": "https://googleads.googleapis.com/v17/customers/3300525230/googleAds:search",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "query",
"value": "=SELECT
campaign.name,
metrics.impressions,
metrics.average_cpm,
metrics.clicks,
metrics.ctr,
metrics.conversions,
metrics.cost_per_conversion,
metrics.cost_micros,
metrics.conversions_value
FROM campaign
WHERE segments.date >= '{{ $json.startDate }}' AND segments.date <= '{{ $json.endDate }}'"
}
]
},
"headerParameters": {
"parameters": [
{
"name": "developer-token",
"value": "fzQ2U5IcU4ZH0vBDn4Slww"
}
]
},
"nodeCredentialType": "googleAdsOAuth2Api"
},
"credentials": {
"googleOAuth2Api": {
"id": "yNLz0qjgW7jN4Osv",
"name": "Google account"
},
"googleAdsOAuth2Api": {
"id": "gEPlb6nlwRX35x6R",
"name": "Google Ads account"
}
},
"typeVersion": 4.2
},
{
"id": "13074a3d-6cf4-4ad7-9e26-002f8120e640",
"name": "Call Meta Ads Data: Last 7 days",
"type": "n8n-nodes-base.facebookGraphApi",
"position": [
-1380,
1540
],
"parameters": {
"edge": "insights",
"node": "act_54337533",
"options": {
"queryParametersJson": "={
\"fields\": \"impressions,cpm,inline_link_clicks,inline_link_click_ctr,conversions,cost_per_conversion,spend,action_values,purchase_roas\",
\"time_range\": {
\"since\": \"{{ $json.currentPeriod.since }}\",
\"until\": \"{{ $json.currentPeriod.until }}\"
}
}"
},
"graphApiVersion": "v20.0"
},
"credentials": {
"facebookGraphApi": {
"id": "9q3YgP6zvgKBO4aj",
"name": "Facebook Graph account"
}
},
"typeVersion": 1
},
{
"id": "06a32368-f9f1-4311-bd17-3fea6b0d2888",
"name": "Call Meta Ads Data: Last 7 days (previous year)",
"type": "n8n-nodes-base.facebookGraphApi",
"position": [
-640,
1540
],
"parameters": {
"edge": "insights",
"node": "act_54337533",
"options": {
"queryParametersJson": "={
\"fields\": \"impressions,cpm,inline_link_clicks,inline_link_click_ctr,conversions,cost_per_conversion,spend,action_values,purchase_roas\",
\"time_range\": {
\"since\": \"{{$node['Calculate date format for meta ads request s'].json.lastYear.since}}\",
\"until\": \"{{$node['Calculate date format for meta ads request s'].json.lastYear.until}}\"
}
}"
},
"graphApiVersion": "v20.0"
},
"credentials": {
"facebookGraphApi": {
"id": "9q3YgP6zvgKBO4aj",
"name": "Facebook Graph account"
}
},
"typeVersion": 1
},
{
"id": "a13919d1-5680-44ea-826b-44afc0034702",
"name": "Summarize Meta input (current year)",
"type": "n8n-nodes-base.summarize",
"position": [
-920,
1540
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "Impressions",
"aggregation": "sum"
},
{
"field": "CPM",
"aggregation": "average"
},
{
"field": "Clicks",
"aggregation": "sum"
},
{
"field": "CTR",
"aggregation": "average"
},
{
"field": "Conversions",
"aggregation": "sum"
},
{
"field": "Cost per conversion",
"aggregation": "average"
},
{
"field": "Spend",
"aggregation": "sum"
},
{
"field": "ROAS",
"aggregation": "average"
}
]
}
},
"typeVersion": 1
},
{
"id": "1afce576-0d2a-41bb-a94b-5d6eaae1fe3e",
"name": "Assign Meta data from input (current year)",
"type": "n8n-nodes-base.set",
"position": [
-1140,
1540
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9c2f8b9a-e964-49a0-8837-efb0dfd7bcae",
"name": "Impressions",
"type": "number",
"value": "={{ $json.data[0].impressions }}"
},
{
"id": "8b524518-1268-4971-b5c9-ae7da09d94f9",
"name": "CPM",
"type": "number",
"value": "={{ $json.data[0].cpm }}"
},
{
"id": "ca7279b9-c643-425f-aa99-cb17146e9994",
"name": "Clicks",
"type": "number",
"value": "={{ $json.data[0].inline_link_clicks }}"
},
{
"id": "591288f7-e8cf-445e-872a-5b83f997b825",
"name": "CTR",
"type": "number",
"value": "={{ $json.data[0].inline_link_click_ctr }}"
},
{
"id": "dc1a43da-3f3a-4dca-bbde-904222d7f693",
"name": "Conversions",
"type": "number",
"value": "={{ $json.data[0].conversions[0].value }}"
},
{
"id": "eac0b53e-c452-40b8-92bc-8af8ea349984",
"name": "=Cost per conversion",
"type": "number",
"value": "={{ $json.data[0].cost_per_conversion[0].value }}"
},
{
"id": "c6cac2d8-b8f8-4b2a-9bcc-1c325db78799",
"name": "ROAS",
"type": "number",
"value": "={{ $json.data[0].purchase_roas[0].value }}"
},
{
"id": "b96439be-189d-4ebe-b49e-d5c31fefe9f0",
"name": "Spend",
"type": "number",
"value": "={{ $json.data[0].spend }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "0d400918-eb14-4bb1-8950-27b39e651264",
"name": "Assign Meta data input (previous year)",
"type": "n8n-nodes-base.set",
"position": [
-340,
1540
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9c2f8b9a-e964-49a0-8837-efb0dfd7bcae",
"name": "Impressions",
"type": "number",
"value": "={{ $json.data[0].impressions }}"
},
{
"id": "8b524518-1268-4971-b5c9-ae7da09d94f9",
"name": "CPM",
"type": "number",
"value": "={{ $json.data[0].cpm }}"
},
{
"id": "ca7279b9-c643-425f-aa99-cb17146e9994",
"name": "Clicks",
"type": "number",
"value": "={{ $json.data[0].inline_link_clicks }}"
},
{
"id": "591288f7-e8cf-445e-872a-5b83f997b825",
"name": "CTR",
"type": "number",
"value": "={{ $json.data[0].inline_link_click_ctr }}"
},
{
"id": "dc1a43da-3f3a-4dca-bbde-904222d7f693",
"name": "Conversions",
"type": "number",
"value": "={{ $json.data[0].conversions[0].value }}"
},
{
"id": "eac0b53e-c452-40b8-92bc-8af8ea349984",
"name": "=Cost per conversion",
"type": "number",
"value": "={{ $json.data[0].cost_per_conversion[0].value }}"
},
{
"id": "b866032c-07ac-440b-a81a-d9787926b9d6",
"name": "ROAS",
"type": "number",
"value": "={{ $json.data[0].purchase_roas[0].value }}"
},
{
"id": "b96439be-189d-4ebe-b49e-d5c31fefe9f0",
"name": "Spend",
"type": "number",
"value": "={{ $json.data[0].spend }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "faf34f2a-f6d3-4510-aeee-6b25174abc08",
"name": "Summarize Meta data input (previous year)",
"type": "n8n-nodes-base.summarize",
"position": [
-40,
1540
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "Impressions",
"aggregation": "sum"
},
{
"field": "CPM",
"aggregation": "average"
},
{
"field": "Clicks",
"aggregation": "sum"
},
{
"field": "CTR",
"aggregation": "average"
},
{
"field": "Conversions",
"aggregation": "sum"
},
{
"field": "Cost per conversion",
"aggregation": "average"
},
{
"field": "Spend",
"aggregation": "sum"
},
{
"field": "ROAS",
"aggregation": "average"
}
]
}
},
"typeVersion": 1
},
{
"id": "3985f30a-94ab-45be-a511-b9ae0d4f3bb0",
"name": "Format all Meta data for LLM",
"type": "n8n-nodes-base.code",
"position": [
160,
1540
],
"parameters": {
"jsCode": "const currentData = $('Summarize Meta input (current year)').first().json;
const previousData = $('Summarize Meta data input (previous year)').first().json;
function parseNumber(value) {
if (typeof value === 'string') {
return parseFloat(value.replace(/\./g, '').replace(',', '.'));
}
return value || 0;
}
function formatNumber(number, decimals = 0) {
if (number === 0) return \"0\";
return parseNumber(number).toLocaleString('de-DE', {
minimumFractionDigits: decimals,
maximumFractionDigits: decimals
});
}
function calculateCPM(cpm) {
return parseNumber(cpm);
}
return [{
current_impressions: formatNumber(currentData.sum_Impressions),
current_cpm: formatNumber(calculateCPM(currentData.average_CPM), 2),
current_clicks: formatNumber(currentData.sum_Clicks),
current_ctr: formatNumber(parseNumber(currentData.average_CTR), 2),
current_conversions: formatNumber(currentData.sum_Conversions, 2),
current_cost_per_conversion: formatNumber(currentData.average_Cost_per_conversion, 2),
current_cost: formatNumber(currentData.sum_Spend, 2),
current_roas: formatNumber(parseNumber(currentData.average_ROAS), 2),
previous_impressions: formatNumber(previousData.sum_Impressions),
previous_cpm: formatNumber(calculateCPM(previousData.average_CPM), 2),
previous_clicks: formatNumber(previousData.sum_Clicks),
previous_ctr: formatNumber(parseNumber(previousData.average_CTR), 2),
previous_conversions: formatNumber(previousData.sum_Conversions, 2),
previous_cost_per_conversion: formatNumber(previousData.average_Cost_per_conversion || 0, 2),
previous_cost: formatNumber(previousData.sum_Spend, 2),
previous_roas: formatNumber(parseNumber(previousData.average_ROAS), 2)
}];"
},
"typeVersion": 2
},
{
"id": "146d6907-66af-41ff-ab32-b2a3ec5787b6",
"name": "Processing for Google Ads report",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
400,
980
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4o",
"cachedResultName": "GPT-4O"
},
"options": {},
"messages": {
"values": [
{
"content": "=Please analyze the following data and output the results in table form:
| Metric | Last 7 Days | Previous Year | Percentage Change |
|--------|-------------|---------------|-------------------|
| Total Impressions | {{$json.current_impressions}} | {{$json.previous_impressions}} | Percentage Change |
| CPM | {{$json.current_cpm}} | {{$json.previous_cpm}} | Percentage Change |
| Total Clicks | {{$json.current_clicks}} | {{$json.previous_clicks}} | Percentage Change |
| CTR | {{$json.current_ctr}} | {{$json.previous_ctr}} | Percentage Change |
| Conversions | {{$json.current_conversions}} | {{$json.previous_conversions}} | Percentage Change |
| Cost per Conversion | {{$json.current_cost_per_conversion}} | {{$json.previous_cost_per_conversion}} | Percentage Change |
| ROAS | {{ $json.current_roas }} | {{ $json.previous_roas }} | Percentage Change |
| Costs | {{$json.current_cost}} | {{$json.previous_cost}} | Percentage Change |
Number format:
- Period (.) for thousands (e.g. 4.000)
- Comma (,) for decimal numbers (e.g. 3,4)
- Display CPM, Cost per Conversion, ROAS and Costs in €
- CTR in percent
Please write a brief summary of the analyzed data above the table (in max 3 sentences!)
IMPORTANT:
Write nothing except the summary and the table below it!
NO INTRODUCTION, NO CONCLUSION!"
}
]
}
},
"credentials": {
"openAiApi": {
"id": "niikB3HA4fT5WAqt",
"name": "OpenAi account"
}
},
"typeVersion": 1.7
},
{
"id": "2fd2a795-caa4-4194-8049-4955c1d54dd9",
"name": "Format all Google data for LLM",
"type": "n8n-nodes-base.code",
"position": [
260,
980
],
"parameters": {
"jsCode": "const currentData = $('Summarize input (current year)').first().json;
const previousData = $('Summarize input (previous year)').first().json;
function formatNumber(number, decimals = 0) {
if (number === 0) return \"0\";
return number.toLocaleString('de-DE', {
minimumFractionDigits: decimals,
maximumFractionDigits: decimals
});
}
function calculateCPM(costMicros, impressions) {
if (impressions === 0) return 0;
return (costMicros / 1000000 / impressions) * 1000;
}
return [{
current_impressions: formatNumber(currentData.sum_Impressions),
current_cpm: formatNumber(calculateCPM(currentData.sum_Spend, currentData.sum_Impressions), 2),
current_clicks: formatNumber(currentData.sum_Clicks),
current_ctr: formatNumber(currentData.average_CTR * 100, 2),
current_conversions: formatNumber(currentData.sum_Conversions, 2),
current_cost_per_conversion: formatNumber(currentData.average_Cost_per_Conversion / 1000000, 2),
current_cost: formatNumber(currentData.sum_Spend / 1000000, 2),
current_roas: formatNumber(currentData.average_ROAS, 2),
previous_impressions: formatNumber(previousData.sum_Impressions),
previous_cpm: formatNumber(calculateCPM(previousData.sum_Spend, previousData.sum_Impressions), 2),
previous_clicks: formatNumber(previousData.sum_Clicks),
previous_ctr: formatNumber(previousData.average_CTR * 100, 2),
previous_conversions: formatNumber(previousData.sum_Conversions, 2),
previous_cost_per_conversion: formatNumber(previousData.average_Cost_per_conversion / 1000000, 2),
previous_cost: formatNumber(previousData.sum_Spend / 1000000, 2),
previous_roas: formatNumber(previousData.average_ROAS, 2)
}];"
},
"typeVersion": 2
},
{
"id": "e7e357e7-3f16-4b6e-ae50-c6741bbe8357",
"name": "Assign Google Analytics data input (current year)",
"type": "n8n-nodes-base.set",
"position": [
-1080,
460
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9c2f8b9a-e964-49a0-8837-efb0dfd7bcae",
"name": "Page views",
"type": "number",
"value": "={{ $json.screenPageViews }}"
},
{
"id": "8b524518-1268-4971-b5c9-ae7da09d94f9",
"name": "Users",
"type": "number",
"value": "={{ $json.totalUsers }}"
},
{
"id": "ca7279b9-c643-425f-aa99-cb17146e9994",
"name": "Sessions",
"type": "number",
"value": "={{ $json.sessions }}"
},
{
"id": "591288f7-e8cf-445e-872a-5b83f997b825",
"name": "Sessions per user",
"type": "number",
"value": "={{ $json.sessionsPerUser }}"
},
{
"id": "dc1a43da-3f3a-4dca-bbde-904222d7f693",
"name": "Session duration",
"type": "number",
"value": "={{ $json.averageSessionDuration }}"
},
{
"id": "eac0b53e-c452-40b8-92bc-8af8ea349984",
"name": "=Conversions",
"type": "number",
"value": "={{ $json.ecommercePurchases }}"
},
{
"id": "b96439be-189d-4ebe-b49e-d5c31fefe9f0",
"name": "Value per Conversion",
"type": "number",
"value": "={{ $json.averagePurchaseRevenue }}"
},
{
"id": "94835d43-2fc8-49c0-97f0-6f0f8699337a",
"name": "Revenue",
"type": "number",
"value": "={{ $json.purchaseRevenue }}"
},
{
"id": "d70f8138-3b84-4b88-a98f-eb929e1cc29a",
"name": "date",
"type": "string",
"value": "={{ $json.date }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "9f16d330-9288-42bc-9a21-beb002c0ce4f",
"name": "Summarize Google Analytics input (current year)",
"type": "n8n-nodes-base.summarize",
"position": [
-860,
460
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "Page views",
"aggregation": "sum"
},
{
"field": "Users",
"aggregation": "sum"
},
{
"field": "Sessions",
"aggregation": "sum"
},
{
"field": "Sessions per user",
"aggregation": "average"
},
{
"field": "Session duration",
"aggregation": "average"
},
{
"field": "Conversions",
"aggregation": "sum"
},
{
"field": "Value per Conversion",
"aggregation": "average"
},
{
"field": "Revenue",
"aggregation": "sum"
},
{
"field": "date"
}
]
}
},
"typeVersion": 1
},
{
"id": "9355325f-35c2-4663-922e-d7ccec873fea",
"name": "Calculate date format for meta ads request s",
"type": "n8n-nodes-base.code",
"position": [
-1600,
1540
],
"parameters": {
"jsCode": "// Aktuelles Datum
const now = new Date();
// Gestern als Ende-Datum
const yesterday = new Date(now);
yesterday.setDate(now.getDate() - 1);
// Start-Datum (7 Tage vor gestern)
const weekStart = new Date(yesterday);
weekStart.setDate(yesterday.getDate() - 6);
// Vorjahreszeitraum
const lastYearStart = new Date(weekStart);
lastYearStart.setFullYear(weekStart.getFullYear() - 1);
const lastYearEnd = new Date(yesterday);
lastYearEnd.setFullYear(yesterday.getFullYear() - 1);
// Formatierung YYYY-MM-DD
function formatDate(date) {
return date.toISOString().split('T')[0];
}
// Ausgabe
items[0] = {
json: {
currentPeriod: {
since: formatDate(weekStart),
until: formatDate(yesterday)
},
lastYear: {
since: formatDate(lastYearStart),
until: formatDate(lastYearEnd)
}
}
};
return items;"
},
"typeVersion": 2
},
{
"id": "7677727b-606b-4377-9057-032e91d1faae",
"name": "Calculation same period previous year1",
"type": "n8n-nodes-base.code",
"position": [
-620,
460
],
"parameters": {
"jsCode": "return {
// Berechnung des Startdatums: Vorjahr, gleiche Woche, 7 Tage zurück
startDate: (() => {
const date = new Date();
date.setFullYear(date.getFullYear() - 1); // Zurück ins Vorjahr
date.setDate(date.getDate() - 7); // 7 Tage zurück
return date.toISOString().split('T')[0];
})(),
// Berechnung des Enddatums: Vorjahr, heutiges Datum
endDate: (() => {
const date = new Date();
date.setFullYear(date.getFullYear() - 1); // Zurück ins Vorjahr
return date.toISOString().split('T')[0];
})(),
};
"
},
"typeVersion": 2
},
{
"id": "d49d00f4-7336-40b7-8833-d2e8c9eacb5b",
"name": "Assign Google Analytics data input (previous year)",
"type": "n8n-nodes-base.set",
"position": [
-180,
460
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9c2f8b9a-e964-49a0-8837-efb0dfd7bcae",
"name": "Page views",
"type": "number",
"value": "={{ $json.screenPageViews }}"
},
{
"id": "8b524518-1268-4971-b5c9-ae7da09d94f9",
"name": "Users",
"type": "number",
"value": "={{ $json.totalUsers }}"
},
{
"id": "ca7279b9-c643-425f-aa99-cb17146e9994",
"name": "Sessions",
"type": "number",
"value": "={{ $json.sessions }}"
},
{
"id": "591288f7-e8cf-445e-872a-5b83f997b825",
"name": "Sessions per user",
"type": "number",
"value": "={{ $json.sessionsPerUser }}"
},
{
"id": "dc1a43da-3f3a-4dca-bbde-904222d7f693",
"name": "Session duration",
"type": "number",
"value": "={{ $json.averageSessionDuration }}"
},
{
"id": "eac0b53e-c452-40b8-92bc-8af8ea349984",
"name": "=Conversions",
"type": "number",
"value": "={{ $json.ecommercePurchases }}"
},
{
"id": "b96439be-189d-4ebe-b49e-d5c31fefe9f0",
"name": "Value per conversion",
"type": "number",
"value": "={{ $json.averagePurchaseRevenue }}"
},
{
"id": "94835d43-2fc8-49c0-97f0-6f0f8699337a",
"name": "Revenue",
"type": "number",
"value": "={{ $json.purchaseRevenue }}"
},
{
"id": "dd8255c6-65b1-41ce-b596-70c09108d6e2",
"name": "=date",
"type": "string",
"value": "={{ $json.date }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "a6f72675-f055-4270-8fff-05d61da6f3f9",
"name": "Summarize Google Analytics input (previous year)",
"type": "n8n-nodes-base.summarize",
"position": [
40,
460
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "Page views",
"aggregation": "sum"
},
{
"field": "Users",
"aggregation": "sum"
},
{
"field": "Sessions",
"aggregation": "sum"
},
{
"field": "Sessions per user",
"aggregation": "average"
},
{
"field": "Session duration",
"aggregation": "average"
},
{
"field": "Conversions",
"aggregation": "sum"
},
{
"field": "Value per conversion",
"aggregation": "average"
},
{
"field": "Revenue",
"aggregation": "sum"
},
{
"field": "date"
}
]
}
},
"typeVersion": 1
},
{
"id": "61311c11-59d2-4b77-afc5-52b1d66afbd7",
"name": "Send mail report",
"type": "n8n-nodes-base.emailSend",
"position": [
560,
-220
],
"parameters": {
"html": "={{ $json.output }}",
"options": {},
"subject": "Weekly Report: Online Marketing Report",
"toEmail": "friedemann.schuetz@ep-reisen.de",
"fromEmail": "friedemann.schuetz@posteo.de"
},
"credentials": {
"smtp": {
"id": "A71x7hx6lKj7nxp1",
"name": "SMTP account"
}
},
"typeVersion": 2.1
},
{
"id": "928d15f2-141c-4e88-abcc-60799793bde7",
"name": "Processing for Meta Ads Report",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
400,
1540
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4o",
"cachedResultName": "GPT-4O"
},
"options": {},
"messages": {
"values": [
{
"content": "=Please analyze the following data and output the results in table form:
| Metric | Last 7 Days | Previous Year | Percentage Change |
|--------|-------------|---------------|-------------------|
| Total Impressions | {{$json.current_impressions}} | {{$json.previous_impressions}} | Percentage Change |
| CPM | {{$json.current_cpm}} | {{$json.previous_cpm}} | Percentage Change |
| Total Clicks | {{$json.current_clicks}} | {{$json.previous_clicks}} | Percentage Change |
| CTR | {{$json.current_ctr}} | {{$json.previous_ctr}} | Percentage Change |
| Conversions | {{$json.current_conversions}} | {{$json.previous_conversions}} | Percentage Change |
| Cost per Conversion | {{$json.current_cost_per_conversion}} | {{$json.previous_cost_per_conversion}} | Percentage Change |
| ROAS | {{ $json.current_roas }} | {{ $json.previous_roas }} | Percentage Change |
| Costs | {{$json.current_cost}} | {{$json.previous_cost}} | Percentage Change |
Number format:
- Period (.) for thousands (e.g. 4.000)
- Comma (,) for decimal numbers (e.g. 3,4)
- Display CPM, Cost per Conversion, ROAS and Costs in €
- CTR in percent
Please write a brief summary of the analyzed data above the table (in max 3 sentences!)
IMPORTANT:
Write nothing except the summary and the table below it!
NO INTRODUCTION, NO CONCLUSION!"
}
]
}
},
"credentials": {
"openAiApi": {
"id": "niikB3HA4fT5WAqt",
"name": "OpenAi account"
}
},
"typeVersion": 1.7
},
{
"id": "ce9175bd-b355-47eb-8dd8-dd26292e0061",
"name": "Processing for Google Analytics Report",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
400,
460
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4o",
"cachedResultName": "GPT-4O"
},
"options": {},
"messages": {
"values": [
{
"content": "=Please analyze the following data and output the results in table form:
| Metric | Last 7 Days | Previous Year | Percentage Change |
|-------------------------------|-------------|---------------|-------------------|
| Total Page Views | {{ $('Summarize Google Analytics input (current year)').item.json.sum_Page_views }} | {{ $json.sum_Page_views }} | Percentage Change |
| Total Users | {{ $('Summarize Google Analytics input (current year)').item.json.sum_Users }} | {{ $json.sum_Users }} | Percentage Change |
| Total Sessions | {{ $('Summarize Google Analytics input (current year)').item.json.sum_Sessions }} | {{ $json.sum_Sessions }} | Percentage Change |
| Average Sessions per User | {{ $('Summarize Google Analytics input (current year)').item.json.average_Sessions_per_user }} | {{ $json.average_Sessions_per_user }} | Percentage Change |
| Average Session Duration | {{ $('Summarize Google Analytics input (current year)').item.json.average_Session_duration }} | {{ $json.average_Session_duration }} | Percentage Change |
| Total Purchases | {{ $('Summarize Google Analytics input (current year)').item.json.sum_Conversions }} | {{ $json.sum_Conversions }} | Percentage Change |
| Average Revenue per Purchase | {{ $('Summarize Google Analytics input (current year)').item.json.average_Value_per_Conversion }} | {{ $json.average_Value_per_conversion }} | Percentage Change |
| Total Revenue | {{ $('Summarize Google Analytics input (current year)').item.json.sum_Revenue }} | {{ $('Summarize Google Analytics input (previous year)').item.json.sum_Revenue }} | Percentage Change |
Number format:
- Period (.) for thousands (e.g. 4.000)
- Comma (,) for decimal numbers (e.g. 3,4)
- Convert Average Session Duration to minutes instead of seconds
- Average Revenue per Purchase and Total Revenue in €
Please write a brief summary of the analyzed data above the table (in max 3 sentences!)
IMPORTANT:
Write nothing except the summary and the table below it!
NO INTRODUCTION, NO CONCLUSION!"
}
]
}
},
"credentials": {
"openAiApi": {
"id": "niikB3HA4fT5WAqt",
"name": "OpenAi account"
}
},
"typeVersion": 1.7
},
{
"id": "c960aed4-83c9-4f7f-b341-0eb29d4c3733",
"name": "Processing for Telegram Report",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
0,
0
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini",
"cachedResultName": "GPT-4O-MINI"
},
"options": {},
"messages": {
"values": [
{
"content": "=Convert the following text from HTML to plain text:
{{ $json.output }}
Please format the table so that each evaluation (Domain 1, Domain 2, Domain 3, Domain 4, Domain 5, Google Ads, Meta Ads) is its own paragraph! Also, please display only the summary (without the table), but incorporate the numbers into the running text!
Example:
Domain 1:
xx,xxx page views (+x.xx%)
xx,xxx users (-x.xx%)
Domain 2:
xx,xxx page views (+x.xx%)
xx,xxx users (-x.xx%)
<userStyle>Normal</userStyle>"
}
]
}
},
"credentials": {
"openAiApi": {
"id": "niikB3HA4fT5WAqt",
"name": "OpenAi account"
}
},
"typeVersion": 1.7
},
{
"id": "542bad2f-fad2-4e6d-b7af-499c7cd2b35c",
"name": "Weekly Report Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-900,
-220
],
"parameters": {
"text": "=# Expert in Data Processing and Email Generation in N8N
YOU ARE AN EXPERT IN DATA PROCESSING AND EMAIL GENERATION IN N8N. YOUR TASK IS TO CREATE AN ENGLISH-LANGUAGE HTML EMAIL THAT COMPREHENSIVELY SUMMARIZES GOOGLE ANALYTICS AND GOOGLE ADS DATA FROM VARIOUS WORKFLOWS. YOU MUST FORMAT THE CAPTURED DATA ACCORDING TO THE SPECIFIED SPECIFICATIONS AND DESIGN THE EMAIL FOR OPTIMAL READABILITY.
## Instructions
### 1. Collect Summary
- First, retrieve the summary and table for `Analytics_Domain_1` from the `Analytics_Domain_1` workflow.
- Second, retrieve the summary and table for `Analytics_Domain_2` from the `Analytics_Domain_2` workflow.
- Third, retrieve the summary and table for `Analytics_Domain_3` from the `Analytics_Domain_3` workflow.
- Fourth, retrieve the summary and table for `Analytics_Domain_4` from the `Analytics_Domain_4` workflow.
- Fifth, retrieve the summary and table for `Analytics_Domain_5` from the `Analytics_Domain_5` workflow.
- Sixth, retrieve the summary and table for `Google_Ads` from the `Google_Ads` workflow.
- Seventh, retrieve the summary and table for `Meta_Ads` from the `Meta_Ads` workflow.
### 2. Email Structure
- Begin the email with the following introduction:
\"Hi Freddy,
Here is your weekly Online Marketing Report for the last 7 days from Domain 1, Domain 2, Domain 3, Domain 4, Domain 5, as well as Google Ads and Meta Ads!\"
- Create a separate section for each dataset:
- **Domain 1**: Contains the summary and table from `Analytics_Domain_1`
- **Domain 2**: Contains the summary and table from `Analytics_Domain_2`
- **Domain 3**: Contains the summary and table from `Analytics_Domain_3`
- **Domain 4**: Contains the summary and table from `Analytics_Domain_4`
- **Domain 5**: Contains the summary and table from `Analytics_Domain_5`
- **Google Ads**: Contains the summary and table from `Google Ads`
- **Meta Ads**: Contains the summary and table from `Meta Ads`
- Present the sections clearly and readably as HTML.
### 3. Design and Formatting
- Use simple HTML structures with clear section titles (e.g., `<h2>` for titles).
- Present the summary as a paragraph (e.g., `<p>`).
- The table should be cleanly formatted (e.g., with `<table>`, `<tr>`, `<td>`).
- Keep the presentation clear and easy to read.
### 4. No Conclusion, No Signature
### HTML Output Structure
```html
<!DOCTYPE html>
<html>
<head>
<style>
body {
font-family: Arial, sans-serif;
line-height: 1.6;
}
h2 {
color: #333;
}
table {
width: 100%;
border-collapse: collapse;
margin: 10px 0;
}
table, th, td {
border: 1px solid #ddd;
}
th, td {
padding: 8px;
text-align: left;
}
th {
background-color: #f4f4f4;
}
</style>
</head>
<body>
<p>Hi,</p>
<p>Here is your weekly Online Marketing Report for the last 7 days from Domain 1, Domain 2, Domain 3, Domain 4, Domain 5, as well as Google Ads and Meta Ads!</p>
<h2>Domain 1</h2>
<p>[Summary from Analytics_Domain_1 will be inserted here]</p>
<table>
[Table content from Analytics_Domain_1 will be inserted here]
</table>
<h2>Domain 2</h2>
<p>[Summary from Analytics_Domain_2 will be inserted here]</p>
<table>
[Table content from Analytics_Domain_2 will be inserted here]
</table>
</body>
</html>
```
### 5. Output
- Format the entire HTML content as a string for email transmission.
### What Not to Do
- No unwanted closings or signatures
- No unstructured, hard-to-read data formatting
- No missing sections or titles
- No copying of data without HTML formatting",
"options": {},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "2a405e35-5d34-4f3c-a5e8-81e958cc550a",
"name": "Send Telegram report",
"type": "n8n-nodes-base.telegram",
"position": [
560,
0
],
"parameters": {
"text": "={{ $json.message.content }}",
"chatId": "1810565648",
"additionalFields": {}
},
"credentials": {
"telegramApi": {
"id": "0hnyvxyUMN77sBmU",
"name": "Telegram account"
}
},
"typeVersion": 1.2
},
{
"id": "eb8e59fe-2dbd-49e6-a055-a01f7419d8f3",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-2120,
-280
],
"parameters": {
"width": 440,
"height": 2180,
"content": "Welcome to Online Marketing Weekly Report Workflow!
This workflow has the following sequence:
1. time trigger (e.g. every Monday at 7 a.m.)
2. retrieval of Online Marketing data from the last 7 days (via sub workflows)
3. assignment and summary of the data
4. retrieval of Online Marketing data from the same time period of the previous year
5. allocation and summary of the data
6. preparation in tabular form and brief analysis by AI.
7. sending the report as an email
8. preparation in short form by AI for Telegram (optional)
9. sending as Telegram message.
The following accesses are required for the workflow:
- Google Analytics (via Google Analytics API): [Documentation](https://docs.n8n.io/integrations/builtin/credentials/google/)
- Google Ads (via HTTP Request -> Google Ads API):[Documentation](https://docs.n8n.io/integrations/builtin/credentials/google/)
- Meta Ads (via Facebook Graph API): [Documentation](https://docs.n8n.io/integrations/builtin/credentials/facebookgraph/)
- AI API access (e.g. via OpenAI, Anthropic, Google or Ollama)
- SMTP access data (for sending the mail)
- Telegram access data (optional for sending as Telegram message): [Documentation](https://docs.n8n.io/integrations/builtin/credentials/telegram/)
You can contact me via LinkedIn, if you have any questions: https://www.linkedin.com/in/friedemann-schuetz"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"timezone": "Europe/Berlin",
"callerPolicy": "workflowsFromSameOwner",
"executionOrder": "v1"
},
"versionId": "0595b0a6-3130-4041-b3b1-41e820edd985",
"connections": {
"Meta_Ads": {
"ai_tool": [
[
{
"node": "Weekly Report Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Calculator": {
"ai_tool": [
[
{
"node": "Processing for Google Analytics Report",
"type": "ai_tool",
"index": 0
}
]
]
},
"Google_Ads": {
"ai_tool": [
[
{
"node": "Weekly Report Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Calculator1": {
"ai_tool": [
[
{
"node": "Processing for Google Ads report",
"type": "ai_tool",
"index": 0
}
]
]
},
"Calculator3": {
"ai_tool": [
[
{
"node": "Processing for Meta Ads Report",
"type": "ai_tool",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Weekly Report Agent",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Weekly Report Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Analytics_Domain_1": {
"ai_tool": [
[
{
"node": "Weekly Report Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Analytics_Domain_2": {
"ai_tool": [
[
{
"node": "Weekly Report Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Analytics_Domain_3": {
"ai_tool": [
[
{
"node": "Weekly Report Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Analytics_Domain_4": {
"ai_tool": [
[
{
"node": "Weekly Report Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Analytics_Domain_5": {
"ai_tool": [
[
{
"node": "Weekly Report Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Weekly Report Agent": {
"main": [
[
{
"node": "Processing for Telegram Report",
"type": "main",
"index": 0
},
{
"node": "Send mail report",
"type": "main",
"index": 0
}
]
]
},
"Send Telegram report": {
"main": [
[]
]
},
"Execute Workflow Trigger": {
"main": [
[
{
"node": "Call Google Analytics data: Last 7 days",
"type": "main",
"index": 0
}
]
]
},
"Assign input (previous year)": {
"main": [
[
{
"node": "Summarize input (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Format all Meta data for LLM": {
"main": [
[
{
"node": "Processing for Meta Ads Report",
"type": "main",
"index": 0
}
]
]
},
"Format all Google data for LLM": {
"main": [
[
{
"node": "Processing for Google Ads report",
"type": "main",
"index": 0
}
]
]
},
"Processing for Telegram Report": {
"main": [
[
{
"node": "Send Telegram report",
"type": "main",
"index": 0
}
]
]
},
"Summarize input (current year)": {
"main": [
[
{
"node": "Calculation same period previous year",
"type": "main",
"index": 0
}
]
]
},
"Call Meta Ads Data: Last 7 days": {
"main": [
[
{
"node": "Assign Meta data from input (current year)",
"type": "main",
"index": 0
}
]
]
},
"Summarize input (previous year)": {
"main": [
[
{
"node": "Format all Google data for LLM",
"type": "main",
"index": 0
}
]
]
},
"Format data input (current year)": {
"main": [
[
{
"node": "Assign data from input (current year)",
"type": "main",
"index": 0
}
]
]
},
"Call Google Ads Data: Last 7 days": {
"main": [
[
{
"node": "Format data input (current year)",
"type": "main",
"index": 0
}
]
]
},
"Format data input (previous year)": {
"main": [
[
{
"node": "Assign input (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Summarize Meta input (current year)": {
"main": [
[
{
"node": "Call Meta Ads Data: Last 7 days (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Assign data from input (current year)": {
"main": [
[
{
"node": "Summarize input (current year)",
"type": "main",
"index": 0
}
]
]
},
"Calculation same period previous year": {
"main": [
[
{
"node": "Call Google Ads Data: Last 7 days (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Assign Meta data input (previous year)": {
"main": [
[
{
"node": "Summarize Meta data input (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Calculation same period previous year1": {
"main": [
[
{
"node": "Call Google Analytics data: Last 7 days (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Call Google Analytics data: Last 7 days": {
"main": [
[
{
"node": "Assign Google Analytics data input (current year)",
"type": "main",
"index": 0
}
]
]
},
"Summarize Meta data input (previous year)": {
"main": [
[
{
"node": "Format all Meta data for LLM",
"type": "main",
"index": 0
}
]
]
},
"Assign Meta data from input (current year)": {
"main": [
[
{
"node": "Summarize Meta input (current year)",
"type": "main",
"index": 0
}
]
]
},
"Calculate date format for meta ads request s": {
"main": [
[
{
"node": "Call Meta Ads Data: Last 7 days",
"type": "main",
"index": 0
}
]
]
},
"Call Meta Ads Data: Last 7 days (previous year)": {
"main": [
[
{
"node": "Assign Meta data input (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Summarize Google Analytics input (current year)": {
"main": [
[
{
"node": "Calculation same period previous year1",
"type": "main",
"index": 0
}
]
]
},
"Summarize Google Analytics input (previous year)": {
"main": [
[
{
"node": "Processing for Google Analytics Report",
"type": "main",
"index": 0
}
]
]
},
"Assign Google Analytics data input (current year)": {
"main": [
[
{
"node": "Summarize Google Analytics input (current year)",
"type": "main",
"index": 0
}
]
]
},
"Call Google Ads Data: Last 7 days (previous year)": {
"main": [
[
{
"node": "Format data input (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Assign Google Analytics data input (previous year)": {
"main": [
[
{
"node": "Summarize Google Analytics input (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Call Google Analytics data: Last 7 days (previous year)": {
"main": [
[
{
"node": "Assign Google Analytics data input (previous year)",
"type": "main",
"index": 0
}
]
]
},
"Calculate date format for Google Ads request (last 7 days)": {
"main": [
[
{
"node": "Call Google Ads Data: Last 7 days",
"type": "main",
"index": 0
}
]
]
}
}
}功能特点
- 自动检测新邮件
- AI智能内容分析
- 自定义分类规则
- 批量处理能力
- 详细的处理日志
技术分析
节点类型及作用
- Scheduletrigger
- @N8N/N8N Nodes Langchain.Lmchatopenai
- @N8N/N8N Nodes Langchain.Toolworkflow
- Executeworkflowtrigger
- @N8N/N8N Nodes Langchain.Toolcalculator
复杂度评估
配置难度：
维护难度：
扩展性：
实施指南
前置条件
- 有效的Gmail账户
- n8n平台访问权限
- Google API凭证
- AI分类服务订阅
配置步骤
- 在n8n中导入工作流JSON文件
- 配置Gmail节点的认证信息
- 设置AI分类器的API密钥
- 自定义分类规则和标签映射
- 测试工作流执行
- 配置定时触发器（可选）
关键参数
| 参数名称 | 默认值 | 说明 |
|---|---|---|
| maxEmails | 50 | 单次处理的最大邮件数量 |
| confidenceThreshold | 0.8 | 分类置信度阈值 |
| autoLabel | true | 是否自动添加标签 |
最佳实践
优化建议
- 定期更新AI分类模型以提高准确性
- 根据邮件量调整处理批次大小
- 设置合理的分类置信度阈值
- 定期清理过期的分类规则
安全注意事项
- 妥善保管API密钥和认证信息
- 限制工作流的访问权限
- 定期审查处理日志
- 启用双因素认证保护Gmail账户
性能优化
- 使用增量处理减少重复工作
- 缓存频繁访问的数据
- 并行处理多个邮件分类任务
- 监控系统资源使用情况
故障排除
常见问题
邮件未被正确分类
检查AI分类器的置信度阈值设置，适当降低阈值或更新训练数据。
Gmail认证失败
确认Google API凭证有效且具有正确的权限范围，重新进行OAuth授权。
调试技巧
- 启用详细日志记录查看每个步骤的执行情况
- 使用测试邮件验证分类逻辑
- 检查网络连接和API服务状态
- 逐步执行工作流定位问题节点
错误处理
工作流包含以下错误处理机制：
- 网络超时自动重试（最多3次）
- API错误记录和告警
- 处理失败邮件的隔离机制
- 异常情况下的回滚操作