Automatisation Google Drive avec n8n : optimisation des fichiers Amazon
Ce workflow n8n a pour objectif d'optimiser les fichiers Amazon Ads en utilisant des données provenant de Google Drive. Dans un contexte où les entreprises cherchent à améliorer leur efficacité publicitaire, ce workflow permet de récupérer des fichiers XLSX et CSV, de les analyser grâce à l'intelligence artificielle d'OpenAI, et d'envoyer des recommandations par email. Les cas d'usage incluent l'optimisation des campagnes publicitaires et la gestion des données de performance.
- Étape 1 : le workflow est déclenché manuellement.
- Étape 2 : il utilise le nœud 'List Files' pour lister les fichiers disponibles sur Google Drive.
- Étape 3 : une condition vérifie si le fichier est au format XLSX.
- Étape 4 : si c'est le cas, le fichier est ouvert et son contenu est extrait.
- Étape 5 : les données extraites sont ensuite fusionnées avec celles d'un fichier CSV.
- Étape 6 : l'IA analyse les données et génère des recommandations. Enfin,
- Étape 7 : les résultats sont envoyés par email aux utilisateurs concernés. Ce workflow permet ainsi de gagner du temps et d'améliorer la prise de décision grâce à des analyses basées sur des données concrètes.
Workflow n8n Google Drive, OpenAI, Amazon Ads : vue d'ensemble
Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.
Workflow n8n Google Drive, OpenAI, Amazon Ads : détail des nœuds
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"id": "Agn9dzf5YTqcmQGN",
"meta": {
"instanceId": "8029058e18ae4ed6081000c1270d96039ad05959052aa2034dd96a215849bcf7",
"templateCredsSetupCompleted": true
},
"name": "Amazon Ads AI Optimization",
"tags": [
{
"id": "vjZ7QzTW2i7StzqX",
"name": "AI Flow",
"createdAt": "2025-04-10T00:32:55.235Z",
"updatedAt": "2025-04-10T00:32:55.235Z"
}
],
"nodes": [
{
"id": "0286c917-d771-4835-a5f8-71f79a5e59e8",
"name": "List Files",
"type": "n8n-nodes-base.googleDrive",
"position": [
-100,
-800
],
"parameters": {
"filter": {
"folderId": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": "<choose report folder>"
}
},
"options": {},
"resource": "fileFolder",
"searchMethod": "query"
},
"credentials": {
"googleDriveOAuth2Api": {
"id": "UPKjIF2z8RkkmP21",
"name": "Google Drive account"
}
},
"typeVersion": 3
},
{
"id": "7d9b0c0a-86ee-4aae-8d73-66f409b0a57f",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1620,
-540
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o",
"cachedResultName": "gpt-4o"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "qszlkCg3ypMJEWvt",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "d3d58b0a-3107-4525-92a8-d54332e9a8a5",
"name": "is XLSX",
"type": "n8n-nodes-base.if",
"position": [
540,
-800
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "820b48a1-676d-400b-894f-3b3a5203eca7",
"operator": {
"type": "string",
"operation": "contains"
},
"leftValue": "={{ $json.name }}",
"rightValue": ".xlsx"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "884e4a08-3b19-4485-aba7-c69887607b82",
"name": "Get File",
"type": "n8n-nodes-base.googleDrive",
"position": [
100,
-800
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
},
"options": {
"binaryPropertyName": "data",
"googleFileConversion": {
"conversion": {}
}
},
"operation": "download"
},
"credentials": {
"googleDriveOAuth2Api": {
"id": "UPKjIF2z8RkkmP21",
"name": "Google Drive account"
}
},
"typeVersion": 3
},
{
"id": "c72fde38-de38-4734-a7e8-aa70e8638cad",
"name": "Merge XLSX and CSV",
"type": "n8n-nodes-base.merge",
"position": [
1200,
-800
],
"parameters": {},
"typeVersion": 3.1
},
{
"id": "cd23e23c-9bb7-4b8d-90ab-8917783cf1ab",
"name": "Format Data",
"type": "n8n-nodes-base.code",
"position": [
1420,
-800
],
"parameters": {
"jsCode": "const result = {};\n\nfor (const item of items) {\n const fileName = item.json.fileName || item.json.name || 'unknown_file';\n const baseName = fileName\n .split('.')[0]\n .replace(/\\s+/g, '_')\n .toLowerCase()\n .replace(/\\s*\\(\\d+\\)$/, '')\n .replace(/_+$/, '')\n .trim();\n\n // regex → result key\n const map = [\n { key: 'search_terms', regex: /search_term/ },\n { key: 'campaigns', regex: /campaign/ },\n { key: 'targeting', regex: /targeting/ },\n { key: 'placement', regex: /placement/ },\n { key: 'budgets', regex: /budget/ },\n ];\n\n const entry = map.find(m => m.regex.test(baseName));\n const mappedKey = entry ? entry.key : null;\n\n console.log('fileName:', fileName);\n console.log('baseName:', baseName);\n console.log('mappedKey:', mappedKey);\n\n if (!mappedKey) {\n throw new Error(`${fileName} → ${baseName} → Unrecognized file name structure`);\n }\n result[mappedKey] = result[mappedKey] || [];\n result[mappedKey].push(item.json);\n}\n\nreturn [{ json: result }];\n\n\n\n"
},
"typeVersion": 2
},
{
"id": "02172577-d867-45a4-96ea-eb105169deff",
"name": "Set fileName",
"type": "n8n-nodes-base.set",
"position": [
320,
-800
],
"parameters": {
"options": {
"dotNotation": true,
"ignoreConversionErrors": false
},
"assignments": {
"assignments": [
{
"id": "a467fabb-d7d0-482d-8a6a-afcd97cc0d8c",
"name": "fileName",
"type": "string",
"value": "={{ $json.name }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "31db008f-20e4-4fe3-a9d0-1815b3802690",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-140,
-1040
],
"parameters": {
"color": 3,
"width": 180,
"height": 200,
"content": "## Change\nChoose the \"folder\" in the filter options to the folder containing your Ad reports\n"
},
"typeVersion": 1
},
{
"id": "0ba8c273-8369-4009-9b93-b0fb243a3c85",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1640,
-1000
],
"parameters": {
"width": 260,
"content": "## AI Analysis\nUses GPT-4o to process the bundled reports and generate optimization instructions.\nPasses system instructions and cleaned data as input."
},
"typeVersion": 1
},
{
"id": "451bb016-1766-4688-aafc-75937e0d5c3f",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-660,
-580
],
"parameters": {
"width": 540,
"height": 700,
"content": "## Amazon Ads Report Scheduling Instructions\nTo run this workflow, schedule the following Sponsored Products reports in the Amazon Ads Console:\n\nUse \"Detailed\" for:\n\nSearch Term Report → Sponsored_Products_Search_Term_Detailed_L30\n\nTargeting Report → Sponsored_Products_Targeting_Detailed_L30\n\nUse \"Summary\" for:\n\nCampaign Report → Sponsored_Products_Campaign_L30\n\nPlacement Report → Sponsored_Products_Placement_L30\n\nBudget Report → Sponsored_Products_Budget_L30\n\nShared settings for all reports:\n\nDate Range: Last 30 Days\n\nFrequency: Daily\n\nFormat: .xlsx or .csv\n\nDelivery: Email + Console Download\n\nMake sure filenames match expectations so the workflow can route them correctly."
},
"typeVersion": 1
},
{
"id": "a671a4f1-05b0-4d7c-9cc1-8c2838593e34",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-60,
-580
],
"parameters": {
"width": 400,
"height": 520,
"content": "## Report Delivery\n\nHow to get reports into Google Drive\n\nUse one of the following:\n\n📥 Manual Upload – Download emailed reports and move them to your Drive folder\n\n🤖 Automation – Use n8n to watch Gmail for no-reply@amazon.com, extract attachments, and upload to Drive\n\n💻 Drive Sync Folder – Use a local folder synced to Google Drive with rules for report types\n\nReports must match expected filenames so the flow can identify and classify them."
},
"typeVersion": 1
},
{
"id": "63a7f391-2bc7-41f9-a53f-e742950c60bf",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
360,
-580
],
"parameters": {
"width": 360,
"height": 520,
"content": "## Upgrade! 🚀\n\nApply for an Amazon Advertising API developer account to unlock full automation:\n\nGenerate reports programmatically via the Reports API\n\nFetch report files directly into n8n using HTTP or custom nodes\n\nEliminate email + Drive dependency entirely\n\n🔗 https://advertising.amazon.com/API/docs/en-us/\n\nOnce approved, you can schedule report generation and download all required data securely and automatically.\n**Double click** to edit me. [Guide](https://docs.n8n.io/workflows/sticky-notes/)"
},
"typeVersion": 1
},
{
"id": "e5a24705-0ad5-4629-b183-d279bdca8b29",
"name": "Preserve File Name",
"type": "n8n-nodes-base.set",
"position": [
980,
-900
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "d6883fe9-d04f-4c86-bc9a-f4dd526afca2",
"name": "fileName",
"type": "string",
"value": "={{ $('is XLSX').item.json.fileName }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "3c315a0c-a89e-490a-9a82-e3d96d2b94c7",
"name": "Email Optimizations",
"type": "n8n-nodes-base.gmail",
"position": [
2016,
-800
],
"webhookId": "b9d7c1a9-a1a3-4b97-97c9-a272f0e97127",
"parameters": {
"sendTo": "={{ $('Email Options').first().json.send_to }}",
"message": "={{\n (() => {\n let raw = $node[\"AI Analyze\"].json[\"text\"];\n\n // 🔧 Remove triple backticks and optional \"json\" tag\n raw = raw.replace(/^```json\\s*/i, \"\").replace(/```$/, \"\").trim();\n\n let data;\n\n try {\n data = JSON.parse(raw);\n } catch (err) {\n return `<p><strong>❌ Failed to parse AI output.</strong><br>${err.message}</p>`;\n }\n\n let msg = \"<h2>Amazon Ads Optimization Instructions</h2>\";\n\n // Optional Summary Totals\n const totalSpend = (data.campaign_adjustments || []).reduce((sum, c) => sum + (c.projected_daily_spend_usd || 0), 0);\n const totalSales = (data.campaign_adjustments || []).reduce((sum, c) => sum + (c.projected_daily_sales_usd || 0), 0);\n msg += `<p><strong>Total Budget Increase Recommended:</strong><br>`;\n msg += `Estimated daily spend: <strong>$${totalSpend.toFixed(2)}</strong><br>`;\n msg += `Estimated daily sales: <strong>$${totalSales.toFixed(2)}</strong></p>`;\n\n // Campaign Adjustments\n msg += \"<h3>Campaign Adjustments:</h3><ul>\";\n (data.campaign_adjustments || []).forEach(c => {\n msg += `<li><strong>${c.campaign_name}</strong><ul>`;\n if (c.default_bid_multiplier !== undefined) {\n const percent = Math.round((1 - c.default_bid_multiplier) * 100);\n msg += `<li>Default bid × ${c.default_bid_multiplier} (<em>–${percent}%</em>)</li>`;\n }\n if (c.bid_adjustments) {\n msg += \"<li>Bid adjustments:<ul>\";\n msg += `<li>Top of Search: ${c.bid_adjustments.top_of_search ?? 0}%</li>`;\n msg += `<li>Rest of Search: ${c.bid_adjustments.rest_of_search ?? 0}%</li>`;\n msg += `<li>Product pages: ${c.bid_adjustments.product_pages ?? 0}%</li>`;\n msg += \"</ul></li>\";\n }\n if (c.budget_change?.action !== \"none\") {\n msg += `<li>Budget: ${c.budget_change.action} by ${c.budget_change.percent}%</li>`;\n }\n if (c.projected_daily_spend_usd && c.projected_daily_sales_usd) {\n msg += `<li>Est. daily spend: $${c.projected_daily_spend_usd.toFixed(2)}</li>`;\n msg += `<li>Est. daily sales: $${c.projected_daily_sales_usd.toFixed(2)}</li>`;\n if (c.estimated_acos_percent !== undefined) {\n msg += `<li>ACoS: ${c.estimated_acos_percent}%</li>`;\n }\n if (c.estimated_roas_multiple !== undefined) {\n const color = c.estimated_roas_multiple < 1.0 ? 'red' : 'green';\n msg += `<li>ROAS: <span style=\"color:${color}\">${c.estimated_roas_multiple.toFixed(2)}x</span></li>`;\n }\n }\n msg += \"</ul></li>\";\n });\n msg += \"</ul>\";\n\n // Keyword Recommendations\n if ((data.keyword_recommendations?.add_exact?.length || 0) > 0 ||\n (data.keyword_recommendations?.negative?.length || 0) > 0) {\n msg += \"<h3>Keyword Recommendations:</h3><ul>\";\n (data.keyword_recommendations.add_exact || []).forEach(k => {\n msg += `<li>Add exact: \"<strong>${k.term}</strong>\" in <em>${k.campaign_name} / ${k.ad_group_name}</em> at <strong>$${k.suggested_bid}</strong></li>`;\n });\n (data.keyword_recommendations.negative || []).forEach(n => {\n if (typeof n === 'string') {\n msg += `<li>Negative: \"<strong>${n}</strong>\"</li>`;\n } else {\n msg += `<li>Negative: \"<strong>${n.term}</strong>\" in <em>${n.campaign_name || 'Unspecified Campaign'}</em></li>`;\n }\n });\n msg += \"</ul>\";\n }\n\n // Targeting Recommendations\n if ((data.targeting_recommendations || []).length > 0) {\n msg += \"<h3>Targeting Recommendations:</h3><ul>\";\n data.targeting_recommendations.forEach(t => {\n const valueText = t.value ? ` by ${t.value}` : \"\";\n msg += `<li>${t.target} in <em>${t.campaign_name} / ${t.ad_group_name}</em>: <strong>${t.action}</strong>${valueText}</li>`;\n });\n msg += \"</ul>\";\n }\n\n return msg;\n })()\n}}\n",
"options": {},
"subject": "={{ $('Email Options').first().json.subject }}"
},
"credentials": {
"gmailOAuth2": {
"id": "6m7O3IpXy4mCRogW",
"name": "Brian Gmail"
}
},
"typeVersion": 2.1
},
{
"id": "f4fc0a70-2df9-4b7b-b60c-856b1b74ead7",
"name": "Extract XLSX Data",
"type": "n8n-nodes-base.extractFromFile",
"position": [
760,
-900
],
"parameters": {
"options": {},
"operation": "xlsx"
},
"typeVersion": 1
},
{
"id": "d0618a5b-1995-474d-a969-38e856b1b91a",
"name": "Extract CSV Data",
"type": "n8n-nodes-base.extractFromFile",
"position": [
760,
-700
],
"parameters": {
"options": {},
"binaryPropertyName": "=data"
},
"typeVersion": 1
},
{
"id": "67f9d0a2-2f34-416a-bc11-ef776e6e4ab3",
"name": "Preserve CSV File Name",
"type": "n8n-nodes-base.set",
"position": [
980,
-700
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "d6883fe9-d04f-4c86-bc9a-f4dd526afca2",
"name": "fileName",
"type": "string",
"value": "={{ $('is XLSX').item.json.fileName }}"
}
]
},
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "818205c9-0fe9-4fe6-8556-657f087ba7b9",
"name": "When clicking ‘Test workflow’",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-500,
-800
],
"parameters": {},
"typeVersion": 1
},
{
"id": "1612753d-0b7f-4ae5-9ec0-8ad39f1003b1",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-580,
-1040
],
"parameters": {
"width": 220,
"content": "## Trigger\nYou may replace this with a scheduled event or poll the folder for changes."
},
"typeVersion": 1
},
{
"id": "158da856-b682-4f98-afcc-4fa12b978db0",
"name": "Email Options",
"type": "n8n-nodes-base.set",
"position": [
-300,
-800
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "60c2189a-2ca3-43ac-bffc-371bbc3c123b",
"name": "send_to",
"type": "string",
"value": "<enter send to email address>"
},
{
"id": "c6f588b3-b8b9-4a83-817b-a68de36d2570",
"name": "subject",
"type": "string",
"value": "<enter the email subject for report emails>"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "4f1f251e-5cfb-468d-9531-9c2ba2c875f6",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-320,
-1040
],
"parameters": {
"color": 3,
"width": 160,
"content": "## Change!\nEdit these email options."
},
"typeVersion": 1
},
{
"id": "ca2f4a7c-5aa9-4f6a-bc04-aedce5e0aaed",
"name": "AI Analyze",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1640,
-800
],
"parameters": {
"text": "={{JSON.stringify($json)}}",
"messages": {
"messageValues": [
{
"message": "You are an Amazon Ads Optimization Assistant. You will receive five structured datasets from Sponsored Products reports:\n- search_terms\n- campaigns\n- targeting\n- placement\n- budgets\n\nYour goal is to generate precise performance recommendations for bid strategy, targeting, and budget scaling.\n\n---\n\n1. Campaign Adjustments:\nFor each campaign, return:\n- campaign_name (string)\n- default_bid_multiplier (float, optional — only if bid should change)\n- bid_adjustments: { top_of_search, rest_of_search, product_pages } (percentages)\n- budget_change: { action: increase | decrease | none, percent: float }\n- projected_daily_spend_usd (float)\n- projected_daily_sales_usd (float)\n- estimated_acos_percent (float)\n- estimated_roas_multiple (float)\n\nBase projections on historical 30-day data. If a budget increase is recommended, scale projected spend and sales proportionally. Return NaN only if data is insufficient.\n\n---\n\n2. Keyword Recommendations:\nRecommend at least 5 exact-match keywords to add. Each must include:\n- term\n- campaign_name\n- ad_group_name\n- suggested_bid (USD)\n\nAlso return at least 3 negative keywords:\n- { term: \"...\", campaign_name?: \"...\" }\n\nDo not return keyword recommendations that lack campaign and ad group names.\n\n---\n\n3. Targeting Recommendations:\nRecommend at least 3 targets to pause or increase bids. Return:\n- target (ASIN, keyword, or match group)\n- campaign_name\n- ad_group_name\n- action: \"pause\" or \"increase_bid\"\n- value: float (if increasing bid)\n\n---\n\nRespond ONLY with a JSON object in this exact format. Do NOT include backticks, code blocks, or explanations:\n\n{\n \"campaign_adjustments\": [...],\n \"keyword_recommendations\": {\n \"add_exact\": [...],\n \"negative\": [...]\n },\n \"targeting_recommendations\": [...]\n}\n\n"
}
]
},
"promptType": "define"
},
"typeVersion": 1.6
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "286aae2a-f8df-489d-9f03-89d0b50b1800",
"connections": {
"is XLSX": {
"main": [
[
{
"node": "Extract XLSX Data",
"type": "main",
"index": 0
}
],
[
{
"node": "Extract CSV Data",
"type": "main",
"index": 0
}
]
]
},
"Get File": {
"main": [
[
{
"node": "Set fileName",
"type": "main",
"index": 0
}
]
]
},
"AI Analyze": {
"main": [
[
{
"node": "Email Optimizations",
"type": "main",
"index": 0
}
]
]
},
"List Files": {
"main": [
[
{
"node": "Get File",
"type": "main",
"index": 0
}
]
]
},
"Format Data": {
"main": [
[
{
"node": "AI Analyze",
"type": "main",
"index": 0
}
]
]
},
"Set fileName": {
"main": [
[
{
"node": "is XLSX",
"type": "main",
"index": 0
}
]
]
},
"Email Options": {
"main": [
[
{
"node": "List Files",
"type": "main",
"index": 0
}
]
]
},
"Extract CSV Data": {
"main": [
[
{
"node": "Preserve CSV File Name",
"type": "main",
"index": 0
}
]
]
},
"Extract XLSX Data": {
"main": [
[
{
"node": "Preserve File Name",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Analyze",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Merge XLSX and CSV": {
"main": [
[
{
"node": "Format Data",
"type": "main",
"index": 0
}
]
]
},
"Preserve File Name": {
"main": [
[
{
"node": "Merge XLSX and CSV",
"type": "main",
"index": 0
}
]
]
},
"Preserve CSV File Name": {
"main": [
[
{
"node": "Merge XLSX and CSV",
"type": "main",
"index": 1
}
]
]
},
"When clicking ‘Test workflow’": {
"main": [
[
{
"node": "Email Options",
"type": "main",
"index": 0
}
]
]
}
}
}Workflow n8n Google Drive, OpenAI, Amazon Ads : pour qui est ce workflow ?
Ce workflow s'adresse aux équipes marketing et aux responsables de la publicité dans les entreprises de taille moyenne à grande, qui utilisent Google Drive pour gérer leurs données publicitaires. Un niveau technique intermédiaire est recommandé pour sa mise en place.
Workflow n8n Google Drive, OpenAI, Amazon Ads : problème résolu
Ce workflow résout le problème de la gestion manuelle des fichiers de données publicitaires, qui peut être chronophage et sujet à des erreurs. En automatisant le processus d'extraction, d'analyse et d'envoi des recommandations, les utilisateurs peuvent se concentrer sur des tâches à plus forte valeur ajoutée. Cela réduit également le risque d'erreurs humaines et améliore la réactivité des équipes face aux performances des campagnes.
Workflow n8n Google Drive, OpenAI, Amazon Ads : étapes du workflow
Étape 1 : le workflow est déclenché manuellement.
- Étape 1 : il liste les fichiers disponibles sur Google Drive grâce au nœud 'List Files'.
- Étape 2 : une condition vérifie si le fichier est au format XLSX.
- Étape 3 : si c'est le cas, le fichier est ouvert et son contenu est extrait.
- Étape 4 : les données extraites sont fusionnées avec celles d'un fichier CSV.
- Étape 5 : l'IA d'OpenAI analyse les données et génère des recommandations.
- Étape 6 : les résultats sont envoyés par email aux utilisateurs concernés.
Workflow n8n Google Drive, OpenAI, Amazon Ads : guide de personnalisation
Pour personnaliser ce workflow, vous pouvez modifier le nœud 'List Files' afin de filtrer les fichiers selon vos besoins spécifiques, comme par exemple en changeant le type de fichier recherché. Vous pouvez également ajuster les paramètres du nœud 'OpenAI Chat Model' pour affiner les recommandations générées par l'IA. Pensez à mettre à jour les adresses email dans le nœud 'Email Optimizations' pour vous assurer que les bonnes personnes reçoivent les résultats. Enfin, vous pouvez ajouter d'autres nœuds pour intégrer des outils supplémentaires selon vos besoins.