広告分析
上級
これはMarket Research, AI Summarization分野の自動化ワークフローで、25個のノードを含みます。主にIf, Set, Code, Merge, SplitOutなどのノードを使用。 GPT-4とGemini AIの比較に基づくMeta広告効果分析
前提条件
- •Google Sheets API認証情報
- •OpenAI API Key
- •Facebook Graph API認証情報
- •Google Gemini API Key
使用ノード (25)
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"id": "YrhmqkmhYl2ghAKN",
"meta": {
"instanceId": "d5e1aee00419f7d76c99b6815681c983a5e0b4d87bfcf461d2e125e2786ef532",
"templateCredsSetupCompleted": true
},
"name": "Ads Analysis",
"tags": [
{
"id": "tITAFvUSOpVVIBvI",
"name": "MetaAds",
"createdAt": "2025-07-05T02:24:26.705Z",
"updatedAt": "2025-07-05T02:24:26.705Z"
},
{
"id": "8ZOxg8cY0fPL8g0s",
"name": "ReadyToUse",
"createdAt": "2025-07-10T04:08:19.089Z",
"updatedAt": "2025-07-10T04:08:19.089Z"
}
],
"nodes": [
{
"id": "02512611-49a2-4319-9423-2a8c84cda262",
"name": "スケジュールトリガー",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
0,
-432
],
"parameters": {
"rule": {
"interval": [
{}
]
}
},
"typeVersion": 1.2
},
{
"id": "46d2cd63-dd9b-41de-a050-a7b0106ec6c7",
"name": "広告を取得",
"type": "n8n-nodes-base.facebookGraphApi",
"position": [
672,
-544
],
"parameters": {
"edge": "ads",
"node": "={{ $json.campaign_id ?? $('Set parameters').item.json.campaign_id }}",
"options": {
"fields": {
"field": [
{
"name": "=id,name,adset_id,creative{id,object_story_id,object_type,image_url,video_id,object_story_spec{video_data{video_id,image_url}}}"
}
]
}
},
"graphApiVersion": "v22.0"
},
"credentials": {
"facebookGraphApi": {
"id": "jF7Lc9HyK76Jr9Xm",
"name": "KH | Facebook Graph"
}
},
"typeVersion": 1
},
{
"id": "90adc41b-f6bf-4a03-894d-3ae50067f64d",
"name": "インサイトを取得",
"type": "n8n-nodes-base.facebookGraphApi",
"position": [
1120,
-480
],
"parameters": {
"edge": "insights",
"node": "={{ $json.id }}",
"options": {
"fields": {
"field": [
{
"name": "ad_id,ad_name,adset_id,campaign_id,spend,impressions,clicks,reach,frequency,actions,action_values,video_p25_watched_actions,video_p50_watched_actions,video_p75_watched_actions,video_p100_watched_actions"
}
]
}
},
"graphApiVersion": "v22.0"
},
"credentials": {
"facebookGraphApi": {
"id": "jF7Lc9HyK76Jr9Xm",
"name": "KH | Facebook Graph"
}
},
"typeVersion": 1
},
{
"id": "e9ef5bb7-b017-4068-abe2-937c077d9630",
"name": "広告を分割",
"type": "n8n-nodes-base.splitOut",
"position": [
896,
-544
],
"parameters": {
"options": {},
"fieldToSplitOut": "data"
},
"executeOnce": false,
"typeVersion": 1
},
{
"id": "bdff8dcb-4319-484a-b7b9-6a25c3a957df",
"name": "インサイトを分割",
"type": "n8n-nodes-base.splitOut",
"position": [
1344,
-480
],
"parameters": {
"options": {},
"fieldToSplitOut": "data"
},
"typeVersion": 1
},
{
"id": "a4b5eb06-0a3b-4092-b682-dbb77ef9f7a6",
"name": "指標を設定",
"type": "n8n-nodes-base.set",
"position": [
1792,
-672
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "8bb35599-d421-4f61-a4c7-f77c60233ba9",
"name": "spend",
"type": "string",
"value": "={{ $json.spend }}"
},
{
"id": "28321e91-fd2f-49e7-92e1-c45a89f67702",
"name": "impressions",
"type": "string",
"value": "={{ $json.impressions }}"
},
{
"id": "0c9319e6-b233-456b-878b-d30515473326",
"name": "link_click",
"type": "string",
"value": "={{ $json.actions.find(action => action.action_type.includes('link_click'))?.value || 0 }}"
},
{
"id": "52248e0e-c428-4d5d-a593-5c43d84398ee",
"name": "app_installs",
"type": "string",
"value": "={{ $json.actions.find(action => action.action_type.includes('app_install'))?.value || 0 }}"
},
{
"id": "0e8282f2-a9cd-4209-87f7-1f10d794b65b",
"name": "complete_registration",
"type": "string",
"value": "={{ $json.actions.find(action => action.action_type.includes('complete_registration'))?.value || 0 }}"
},
{
"id": "709915f4-b44b-434e-9193-39ea390ccbb0",
"name": "add_to_cart",
"type": "string",
"value": "={{ $json.actions.find(action => action.action_type.includes('add_to_cart'))?.value || 0 }}"
},
{
"id": "62420b81-8f39-4c88-ae1e-8a20c4d1a13f",
"name": "initiate_checkout",
"type": "string",
"value": "={{ $json.actions.find(action => action.action_type.includes('initiate_checkout'))?.value || 0 }}"
},
{
"id": "9bc0b5fe-6639-4b6d-b31d-924b25b6818d",
"name": "purchase",
"type": "string",
"value": "={{ $json.actions.find(action => action.action_type.includes('purchase'))?.value || 0 }}"
},
{
"id": "96859718-a1f3-4678-8b40-110e0e38964f",
"name": "value",
"type": "string",
"value": "={{ $json.action_values ? $json.action_values.find(action => action.action_type.includes('purchase'))?.value || 0 : 0 }}"
},
{
"id": "82193e6a-e80c-429c-9066-56ac3985647f",
"name": "ad_id",
"type": "string",
"value": "={{ $json.ad_id }}"
},
{
"id": "04316c4e-1417-46d5-9368-5335f9899dd6",
"name": "ad_name",
"type": "string",
"value": "={{ $json.ad_name }}"
},
{
"id": "114d6153-66ff-4087-b82e-df19abbd52dc",
"name": "campaign_id",
"type": "string",
"value": "={{ $json.campaign_id }}"
},
{
"id": "58d3f46a-ecd5-4590-9194-76cfe4541dc3",
"name": "adset_id",
"type": "string",
"value": "={{ $json.adset_id }}"
},
{
"id": "fa3c43ea-17f4-41ab-94e5-d75d9b386c23",
"name": "video_image_url",
"type": "string",
"value": "={{ $json.creative.object_story_spec.video_data.image_url }}"
},
{
"id": "000a2f08-6fca-4790-bcaf-d0937c2b70f0",
"name": "image_url",
"type": "string",
"value": "={{ $json.creative.image_url }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "f891f10b-02c3-4eab-ad22-e01f8c6d3e20",
"name": "パラメータを設定",
"type": "n8n-nodes-base.set",
"position": [
224,
-432
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "a2f4de51-3c9b-41dd-94bd-cdab162261ba",
"name": "source",
"type": "string",
"value": "Sheets"
},
{
"id": "3c3bb838-3411-4347-b98c-f05d1ff60a8d",
"name": "campaign_id",
"type": "string",
"value": ""
},
{
"id": "418cf02d-3573-4f78-8495-553b5a0f47e3",
"name": "benchmarks_data",
"type": "string",
"value": "=Ad ID,Ad name,Ad delivery,Frequency,Reach,Impressions,CTR (link click-through rate),\"CPM (cost per 1,000 impressions) (USD)\",Link clicks,CPC (cost per link click) (USD),IPM,App Installs,Cost per App Install (USD),CR install to reg,Registrations completed,Cost per registration completed (USD),Results,Result indicator,Cost per results,Amount spent (USD),Adds to cart,Cost per add to cart (USD),Checkouts initiated,Cost per checkout initiated (USD),Purchases,Searches,Checkouts initiated conversion value\n120222559945080510,How-to-fly-earn.mp4,not_delivering,2.253171,1312196,2956602,0.787593,2.876305,23286,0.365202,5.80598944,17166,0.495403,0.25381568,4357,1.951822,4357,actions:app_custom_event.fb_mobile_complete_registration,1.95182235,8504.09,515,16.512796,136,62.530074,,19042,7666249.29\n120227998563210510,EASY JUNE 13.jpg,active,2.044556,892309,1824376,1.141212,2.786471,20820,0.244168,3.96354699,7231,0.703024,0.19941917,1442,3.525361,82,actions:app_custom_event.fb_mobile_initiated_checkout,61.9947561,5083.57,360,14.121028,83,61.247831,,9336,4367509.01\n120218673707160510,EASY MARCH ITALY - 1.jpg,not_delivering,1.800396,818312,1473286,0.84505,1.963522,12450,0.232356,2.63356877,3880,0.745575,0.23840206,925,3.127384,925,actions:app_custom_event.fb_mobile_complete_registration,3.12738378,2892.83,194,14.911495,61,47.423443,,5721,2333824.7\n120216673487350510,Flying20Private.mp4,not_delivering,1.915076,301010,576457,0.468899,2.564927,2703,0.547011,2.84496502,1640,0.901567,0.28414634,466,3.172897,459,actions:app_custom_event.fb_mobile_complete_registration,3.2212854,1478.57,121,12.219587,35,42.244857,,2904,1238511.1\n120226828283920510,DJoPkbKzfcU.mp4,not_delivering,1.713265,517876,887259,0.837636,2.505728,7432,0.299143,4.41133874,3914,0.56802,0.25038324,980,2.268602,980,actions:app_custom_event.fb_mobile_complete_registration,2.26860204,2223.23,110,20.211182,29,76.663103,,4559,1405339.92\n120215360661600510,EASY-1 New.jpg,inactive,1.796525,382927,687938,0.715035,2.079548,4919,0.290831,1.89697327,1305,1.096245,0.27126437,354,4.041243,354,actions:app_custom_event.fb_mobile_complete_registration,4.04124294,1430.6,75,19.074667,29,49.331034,,2295,688904.04"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "423b6343-a63c-42b3-9804-4088e8e1694a",
"name": "条件分岐",
"type": "n8n-nodes-base.if",
"position": [
448,
-432
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "e682854e-6f62-4016-8406-897dc46e2837",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.source }}",
"rightValue": "Meta"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "104f7e12-094c-4f7f-8ec4-420866771334",
"name": "広告詳細を取得",
"type": "n8n-nodes-base.facebookGraphApi",
"position": [
896,
-288
],
"parameters": {
"node": "={{ $json.AdID }}",
"options": {
"fields": {
"field": [
{
"name": "id,name,adset_id,creative{id,object_story_id,object_type,image_url,video_id,object_story_spec{video_data{video_id,image_url}}}"
}
]
}
},
"graphApiVersion": "v22.0"
},
"credentials": {
"facebookGraphApi": {
"id": "jF7Lc9HyK76Jr9Xm",
"name": "KH | Facebook Graph"
}
},
"typeVersion": 1
},
{
"id": "b1111c61-bb8a-4f7d-958f-8a09dc75c910",
"name": "マージ",
"type": "n8n-nodes-base.merge",
"position": [
1568,
-480
],
"parameters": {
"mode": "combine",
"options": {},
"advanced": true,
"mergeByFields": {
"values": [
{
"field1": "id",
"field2": "ad_id"
}
]
}
},
"typeVersion": 3.2
},
{
"id": "b5b5eb35-4402-471e-a15c-7b6f38a46c18",
"name": "分割",
"type": "n8n-nodes-base.splitOut",
"position": [
2416,
-480
],
"parameters": {
"options": {},
"fieldToSplitOut": "message.content.creatives"
},
"typeVersion": 1
},
{
"id": "2a067c01-1113-41f1-8165-484f83e2c86c",
"name": "構造化出力パーサー",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
2224,
64
],
"parameters": {
"jsonSchemaExample": "{\n \"ad_id\": \"9847213\",\n \"evaluation\": \"high\",\n \"significance\": \"yes\",\n \"summary\": \"CTR and CPC are significantly better than benchmarks, with a strong funnel down to Checkouts Initiated.\",\n \"recommendation\": \"scale\"\n}"
},
"typeVersion": 1.3
},
{
"id": "62321b02-c786-4397-96dd-c86532968664",
"name": "Google Gemini チャットモデル",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
2032,
48
],
"parameters": {
"options": {
"temperature": 0.4
}
},
"credentials": {
"googlePalmApi": {
"id": "ZIfu0CPV4qEzGAfw",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "b599b087-9f76-4183-8b39-c15cba123e0c",
"name": "CSVをOpenAI用に準備",
"type": "n8n-nodes-base.code",
"position": [
1792,
-480
],
"parameters": {
"jsCode": "// Определяем заголовки CSV один раз, они будут одинаковыми для всех строк.\nconst header = \"ad_name,ad_id,spend,impressions,clicks,app_installs,registrations,purchases,purchase_value\";\n\n// Используем .map() для преобразования КАЖДОГО входящего элемента\n// Метод .map() вернет новый массив той же длины, что и items\nreturn items.map(item => {\n // Внутри .map() мы работаем с одним 'item' за раз.\n // Получаем его json-содержимое\n const currentJson = item.json;\n\n // Извлекаем данные для ТЕКУЩЕГО элемента, создавая строку со значениями\n const row = [\n `\"${currentJson.name.replace(/\"/g, '\"\"')}\"`, // Экранируем кавычки\n currentJson.ad_id || 0,\n currentJson.spend || 0,\n currentJson.impressions || 0,\n currentJson.clicks || 0,\n currentJson.actions?.find(a => a.action_type.includes('app_install'))?.value || 0,\n currentJson.actions?.find(a => a.action_type.includes('complete_registration'))?.value || 0,\n currentJson.actions?.find(a => a.action_type.includes('purchase'))?.value || 0,\n currentJson.action_values?.find(a => a.action_type.includes('purchase'))?.value || 0\n ].join(',');\n\n // Возвращаем новую структуру для ТЕКУЩЕГО элемента.\n // Она будет содержать все старые данные + новое поле с CSV.\n return {\n json: {\n ...currentJson, // Сохраняем все исходные данные\n creative_csv_data: `${header}\\n${row}` // Добавляем новое поле с CSV\n }\n };\n});"
},
"typeVersion": 2
},
{
"id": "5dac1e5f-a814-48a7-beaf-b0657d1ff926",
"name": "CSVをGemini用に準備",
"type": "n8n-nodes-base.code",
"position": [
1808,
-160
],
"parameters": {
"jsCode": "// Определяем заголовки CSV один раз, они будут одинаковыми для всех строк.\nconst header = \"ad_name,ad_id,spend,impressions,clicks,app_installs,registrations,purchases,purchase_value\";\n\n// Используем .map() для преобразования КАЖДОГО входящего элемента\n// Метод .map() вернет новый массив той же длины, что и items\nreturn items.map(item => {\n // Внутри .map() мы работаем с одним 'item' за раз.\n // Получаем его json-содержимое\n const currentJson = item.json;\n\n // Извлекаем данные для ТЕКУЩЕГО элемента, создавая строку со значениями\n const row = [\n `\"${currentJson.name.replace(/\"/g, '\"\"')}\"`, // Экранируем кавычки\n currentJson.ad_id || 0,\n currentJson.spend || 0,\n currentJson.impressions || 0,\n currentJson.clicks || 0,\n currentJson.actions?.find(a => a.action_type.includes('app_install'))?.value || 0,\n currentJson.actions?.find(a => a.action_type.includes('complete_registration'))?.value || 0,\n currentJson.actions?.find(a => a.action_type.includes('purchase'))?.value || 0,\n currentJson.action_values?.find(a => a.action_type.includes('purchase'))?.value || 0\n ].join(',');\n\n // Возвращаем новую структуру для ТЕКУЩЕГО элемента.\n // Она будет содержать все старые данные + новое поле с CSV.\n return {\n json: {\n ...currentJson, // Сохраняем все исходные данные\n creative_csv_data: `${header}\\n${row}` // Добавляем новое поле с CSV\n }\n };\n});"
},
"typeVersion": 2
},
{
"id": "9d019e72-f72f-4e52-8ec2-cdf83fb57700",
"name": "Geminiからの広告データ",
"type": "n8n-nodes-base.googleSheets",
"position": [
2432,
-160
],
"parameters": {
"columns": {
"value": {
"AdID": "={{ $json.output.ad_id }}",
"summary G": "={{ $json.output.summary }}",
"evaluation G": "={{ $json.output.evaluation }}",
"significance G": "={{ $json.output.significance }}",
"recommendation G": "={{ $json.output.recommendation }}"
},
"schema": [
{
"id": "FileName",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "FileName",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "CreativeID",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "CreativeID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Type",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Type",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Timestamp",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Timestamp",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "campaign_id",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "campaign_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "AdsetID",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "AdsetID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "AdID",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "AdID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Image",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Image",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Impressions",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Impressions",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "spend",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "spend",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "link_click",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "link_click",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "app_install",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "app_install",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "complete_registration",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "complete_registration",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "add_to_cart",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "add_to_cart",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "initiate_checkout",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "initiate_checkout",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "purchase",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "purchase",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "value",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "value",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "evaluation",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "evaluation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "significance",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "significance",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "summary",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "summary",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "recommendation",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "recommendation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "evaluation G",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "evaluation G",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "significance G",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "significance G",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "summary G",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "summary G",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "recommendation G",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "recommendation G",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "row_number",
"type": "number",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "row_number",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"AdID"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "update",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw/edit#gid=0",
"cachedResultName": "Creatives"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "=1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "0drwHzGo1eKmiTc6",
"name": "KH | Google Sheets "
}
},
"typeVersion": 4.6,
"alwaysOutputData": true
},
{
"id": "4214e518-1d16-4d4f-83c1-271fe0ab4e61",
"name": "OpenAIからの広告データ",
"type": "n8n-nodes-base.googleSheets",
"position": [
2640,
-480
],
"parameters": {
"columns": {
"value": {
"AdID": "={{ $json.ad_id }}",
"summary": "={{ $json.summary }}",
"evaluation": "={{ $json.evaluation }}",
"significance": "={{ $json.significance }}",
"recommendation": "={{ $json.recommendation }}"
},
"schema": [
{
"id": "FileName",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "FileName",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "CreativeID",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "CreativeID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Type",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Type",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Timestamp",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Timestamp",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "campaign_id",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "campaign_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "AdsetID",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "AdsetID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "AdID",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "AdID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Image",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Image",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Impressions",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Impressions",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "spend",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "spend",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "link_click",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "link_click",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "app_install",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "app_install",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "complete_registration",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "complete_registration",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "add_to_cart",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "add_to_cart",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "initiate_checkout",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "initiate_checkout",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "purchase",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "purchase",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "value",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "value",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "evaluation",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "evaluation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "significance",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "significance",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "summary",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "summary",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "recommendation",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "recommendation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "row_number",
"type": "number",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "row_number",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"AdID"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "update",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw/edit#gid=0",
"cachedResultName": "Creatives"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "=1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "0drwHzGo1eKmiTc6",
"name": "KH | Google Sheets "
}
},
"typeVersion": 4.6,
"alwaysOutputData": true
},
{
"id": "bed8d683-fe25-4910-98c4-23ae96418579",
"name": "データを4.1-NANOに送信",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
2016,
-480
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-nano",
"cachedResultName": "GPT-4.1-NANO"
},
"options": {
"maxTokens": 6000,
"temperature": 0.4
},
"messages": {
"values": [
{
"role": "system",
"content": "=You are the lead performance marketer at Digital Agency, a Meta Ads specialist.\nYour core strength is deep, objective analysis of creatives using funnel metrics (Impressions → Clicks → Installs → Registrations → Add to Cart → Checkouts Initiated).\nYou compare test creatives with internal benchmarks and give clear recommendations on whether to scale, keep testing, or stop a creative.\nYour goal is to help make decisions, not just repeat the data."
},
{
"content": "=**BENCHMARKS_DATA (top-performing creatives with calculated metrics like CTR, CPC, CPA, ROAS, etc.)**\n*This is a CSV string with data from your top-performing creatives. All key metrics are pre-calculated here.*\n{{ $('Set parameters').item.json.benchmarks_data }}\n\n**ANALYSIS_DATA (raw test data without calculated metrics)**:\n\n{{ $json.creative_csv_data }}\n\n*Context*:\n\t•\tEasyBusy is a business aggregator.\n\t•\tDue to a long sales cycle (~30 days) and high average order value, there are no Purchases in the data.\n\t•\tWe use Checkouts Initiated as a proxy conversion metric and also track the full funnel.\n\n**Your task**:\n\t1.\tCalculate the same metrics for the test creatives as in the benchmark data (CTR, CPC, CPA, ROAS, etc.).\n\t2.\tCompare each test creative against the benchmarks:\n\t•\tMetric-by-metric (e.g. higher CTR but worse CPC)\n\t•\tFunnel quality (is there drop-off or strength at any step?)\n\t3.\tAnswer the following:\n\t•\tDo we have enough data to draw conclusions for each creative?\n\t•\tWhich creatives are ready to scale now? Why?\n\t•\tWhich creatives should continue testing?\n\t•\tWhich creatives should be stopped?\n\nOUTPUT FORMAT — ONLY JSON ARRAY OF CREATIVES:\n\nDo not write any explanation, markdown, or formatting outside of the array. Just return a single JSON array like this:\nYou must include ALL creatives in a SINGLE JSON array — not split across multiple responses. \nRespond in ONE single message. Do NOT return one object per message.\n\n**Each object must follow this structure**:\n{\n \"ad_id\": \"string (ad_id from ANALYSIS_DATA dataset)\",\n \"evaluation\": \"high | medium | low\",\n \"significance\": \"yes | no\",\n \"summary\": \"2–3 sentence explanation of why this creative got this score\",\n \"recommendation\": \"scale | optimize | stop\"\n}\n\n*Example*:\n[\n {\n \"ad_id\": \"1202153606616005\",\n \"evaluation\": \"high\",\n \"significance\": \"yes\",\n \"summary\": \"CTR and CPC are significantly better than benchmarks, with a strong funnel down to Checkouts Initiated.\",\n \"recommendation\": \"scale\"\n },\n {\n \"ad_id\": \"92021533361600510\",\n \"evaluation\": \"low\",\n \"significance\": \"yes\",\n \"summary\": \"Low CTR and high CPC. Almost no meaningful downstream activity.\",\n \"recommendation\": \"stop\"\n }\n]\n\nIf there isn’t enough data, set \"significance\": \"no\" and clearly explain the reason in summary. Still provide the other fields.\n\n**Important**:\n\t•\tNo markdown\n\t•\tNo extra text\n\t•\tOutput = only one clean JSON array"
},
{
"role": "assistant",
"content": "=Do not return each creative in a separate message. You must return a SINGLE JSON array that includes ALL creatives from the dataset."
}
]
},
"jsonOutput": true
},
"credentials": {
"openAiApi": {
"id": "ev7u8Pmik6FUikE1",
"name": "OpenAi account"
}
},
"typeVersion": 1.8
},
{
"id": "acbba7e0-6a6f-4138-981e-7bc7b7d6e82c",
"name": "データをGeminiに送信",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
2032,
-160
],
"parameters": {
"text": "=You are the lead performance marketer at Digital Agency, a Meta Ads specialist.\nYour core strength is deep, objective analysis of creatives using funnel metrics (Impressions → Clicks → Installs → Registrations → Add to Cart → Checkouts Initiated). You compare test creatives with internal benchmarks and give clear recommendations on whether to scale, keep testing, or stop a creative.\nYour goal is to help make decisions, not just repeat the data.\n\nINPUT DATA\n**1. BENCHMARKS_DATA**:\n*This is a CSV string with data from your top-performing creatives. All key metrics are pre-calculated here.*\n{{ $('Set parameters').item.json.benchmarks_data }}\n\n**2. ANALYSIS_DATA (raw test data without calculated metrics)**:\n{{ $json.creative_csv_data }}\n\nContext:\n\t•\tEasyBusy is a business aggregator.\n\t•\tDue to a long sales cycle (~30 days) and high average order value, there are no Purchases in the data.\n\t•\tWe use Checkouts Initiated as a proxy conversion metric and also track the full funnel.\n\n**Your task:**\n1. Calculate metrics for each creative in ANALYSIS_DATA. Use the following formulas:\n- CTR (link click-through rate) = Link clicks / Impressions\n- CPC (cost per link click) = Amount spent (USD) / Link clicks\n- IPM (Installs per 1000 impressions) = App Installs / (Impressions / 1000)\n- Cost per App Install = Amount spent (USD) / App Installs\n- CR install to reg = Registrations completed / App Installs\n- Cost per registration completed = Amount spent (USD) / Registrations completed\n- Cost per add to cart = Amount spent (USD) / Adds to cart\n- Cost per checkout initiated = Amount spent (USD) / Checkouts initiated\n- If a denominator is zero, the resulting metric should be 0 or null.\n2. Analyze each creative from ANALYSIS_DATA according to the following rules:\n- Rule for determining statistical significance (significance):\n--Consider the data sufficient (\"significance\": \"yes\") if BOTH of the following conditions are met:\n--- Amount spent (USD) > 49\n--- Impressions > 10,000\nOtherwise, set \"significance\": \"no\".\n-Rule for evaluation (evaluation):\n-- Compare the key metrics of the test creative (CTR, CPC, Cost per App Install, Cost per checkout initiated) against the average values of the same metrics from the BENCHMARKS_DATA file.\n-- \"high\": The creative significantly outperforms the benchmark averages on key funnel metrics (e.g., higher CTR, and lower CPC and Cost per checkout initiated).\n-- \"medium\": The creative shows mixed results or performs on par with the benchmarks. For example, a good CTR but an expensive Cost per checkout initiated.\n-- \"low\": The creative significantly underperforms the benchmarks on most key metrics.\n3. Based on your analysis, provide a final JSON object containing the ad_id from the input data, and your calculated values for evaluation, significance, summary, and recommendation. For the summary, provide a 2-3 sentence explanation. If there is not enough data, set \"significance\" to \"no\" and explain why in the summary.",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2.1,
"alwaysOutputData": true
},
{
"id": "c763d9da-66e1-41a6-881f-6f3f210395aa",
"name": "広告指標",
"type": "n8n-nodes-base.googleSheets",
"position": [
2112,
-672
],
"parameters": {
"columns": {
"value": {
"AdID": "={{ $json.ad_id }}",
"Type": "={{ $('Merge').item.json.creative.object_type }}",
"Image": "==IMAGE(\"{{ $json.video_image_url ?? $json.image_url }}\",1)",
"spend": "={{ $json.spend }}",
"value": "={{ $json.value }}",
"AdsetID": "={{ $json.adset_id }}",
"FileName": "={{ $json.ad_name }}",
"purchase": "={{ $json.purchase }}",
"CreativeID": "={{ $('Merge').item.json.creative.id }}",
"link_click": "={{ $('Insights Split Out').item.json.clicks }}",
"Impressions": "={{ $json.impressions }}",
"add_to_cart": "={{ $json.add_to_cart }}",
"app_install": "={{ $json.app_installs }}",
"campaign_id": "={{ $json.campaign_id }}",
"initiate_checkout": "={{ $json.initiate_checkout }}",
"complete_registration": "={{ $json.complete_registration }}"
},
"schema": [
{
"id": "FileName",
"type": "string",
"display": true,
"required": false,
"displayName": "FileName",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "CreativeID",
"type": "string",
"display": true,
"required": false,
"displayName": "CreativeID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Type",
"type": "string",
"display": true,
"required": false,
"displayName": "Type",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Timestamp",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "Timestamp",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "campaign_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "campaign_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "AdsetID",
"type": "string",
"display": true,
"required": false,
"displayName": "AdsetID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "AdID",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "AdID",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Image",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Image",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Impressions",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Impressions",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "spend",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "spend",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "link_click",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "link_click",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "app_install",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "app_install",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "complete_registration",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "complete_registration",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "add_to_cart",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "add_to_cart",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "initiate_checkout",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "initiate_checkout",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "purchase",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "purchase",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "value",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "value",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "evaluation",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "evaluation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "significance",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "significance",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "summary",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "summary",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "recommendation",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "recommendation",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"AdID"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw/edit#gid=0",
"cachedResultName": "Creatives"
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "=1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "0drwHzGo1eKmiTc6",
"name": "KH | Google Sheets "
}
},
"typeVersion": 4.6
},
{
"id": "1b303d83-c74f-44a9-89e3-3963d707048f",
"name": "シートから広告を取得",
"type": "n8n-nodes-base.googleSheets",
"position": [
672,
-288
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1754847770,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw/edit#gid=1754847770",
"cachedResultName": "Test Ads Analysis"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1gwBOLHpez5fFX9C2m6PoZcsw5LLcjjbR7448jn6cimw/edit?usp=drivesdk",
"cachedResultName": "AutoTest_of_Creatives_v2"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "0drwHzGo1eKmiTc6",
"name": "KH | Google Sheets "
}
},
"typeVersion": 4.6
},
{
"id": "5ab1c7cc-3016-4125-ad8a-20f07fb66731",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
-64,
-1200
],
"parameters": {
"color": 5,
"width": 672,
"height": 640,
"content": "### Ads Performance Analysis with AI\n\nThis workflow automates the in-depth analysis of Meta Ads creatives by leveraging the analytical power of AI models (OpenAI and Google Gemini). It fetches performance data, compares it against historical benchmarks, and provides actionable recommendations (\"scale\", \"optimize\", \"stop\") for each creative.\n\nThe system is designed for high flexibility and can be used in two primary ways:\n1. **As a standalone tool:** By setting the `source` to \"Meta\" and providing a `campaign_id` in the configuration node, it will automatically analyze all active ads in a campaign.\n2. **As a continuation of the \"Creative Testing Automation\" workflow:** By setting the `source` to \"Sheets\", it can read a list of newly created `AdID`s from a Google Sheet and analyze them.\n\nThe core of this workflow is its AI-driven analysis. It feeds raw performance metrics and pre-defined benchmarks (stored in the configuration node) to AI models, which then act as expert performance marketers to evaluate each creative's potential.\n\n**Key Features:**\n- **Dual AI Analysis:** Runs parallel analyses using both OpenAI and Google Gemini for comparative insights.\n- **Dynamic Benchmarking:** Easily update performance benchmarks in a central configuration node to keep the AI's analysis relevant.\n- **Resilient & Fault-Tolerant:** The workflow is architected to be robust. It first logs raw metrics to a Google Sheet and then updates the same row with AI analysis. If an AI model fails, the core data is still saved.\n- **Flexible Data Sourcing:** Pulls data directly from Meta Ads or from a preparatory Google Sheet."
},
"typeVersion": 1
},
{
"id": "0bb38ad0-19df-45c0-a6c1-6f3389989661",
"name": "付箋1",
"type": "n8n-nodes-base.stickyNote",
"position": [
64,
-288
],
"parameters": {
"color": 6,
"width": 544,
"height": 352,
"content": "**⚙️ 1. Main Configuration**\n\nThis is the control center for the entire workflow.\n\n**1. Choose a Source (source):**\n- **`Meta`** - to analyze an entire ad campaign (you'll need to set the `campaign_id` below).\n- **`sheets`** - to analyze creatives from a Google Sheet (you'll need to configure the \"Get Ads from Sheet\" node).\n\n**2. Add Your Benchmarks (benchmarks_data):**\n- Paste your top-performing creative data here in CSV format(a standard export from Ads Manager is perfect for this). The AI will use this for comparison and analysis.\n- **The higher the quality of your benchmarks, the more accurate the results.**"
},
"typeVersion": 1
},
{
"id": "521dc7b9-0c91-4ad6-9deb-782144bf3b72",
"name": "付箋2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1536,
-912
],
"parameters": {
"color": 7,
"width": 528,
"height": 256,
"content": "**📈 2. Metrics Preparation**\n\nThis node \"unpacks\" the data from the Meta API response, preparing it for the Google Sheet and for the AI.\n\n- The main metrics (spend, impressions, clicks, actions) are already set up.\n- You can add extraction for **custom conversions** or any other fields you need from the Facebook response here.\n\nAll fields added here will be written to the Google Sheet."
},
"typeVersion": 1
},
{
"id": "9ce178d1-f191-4ece-8c12-146256cec783",
"name": "付箋3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1952,
-352
],
"parameters": {
"color": 4,
"width": 624,
"height": 256,
"content": "**🤖 3. AI Scoring **\n\nDon't be afraid to **experiment with the prompts!**\n\n- The template includes a quality base prompt, but it can and should be adapted to your specific tasks, KPIs, and business context.\n- Try different phrasing to find the most effective combination for your goals. **The quality of the analysis directly depends on the quality of the prompt!**"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "8b469281-9218-42b9-95b6-5de9b7e853a8",
"connections": {
"423b6343-a63c-42b3-9804-4088e8e1694a": {
"main": [
[
{
"node": "46d2cd63-dd9b-41de-a050-a7b0106ec6c7",
"type": "main",
"index": 0
}
],
[
{
"node": "1b303d83-c74f-44a9-89e3-3963d707048f",
"type": "main",
"index": 0
}
]
]
},
"b1111c61-bb8a-4f7d-958f-8a09dc75c910": {
"main": [
[
{
"node": "b599b087-9f76-4183-8b39-c15cba123e0c",
"type": "main",
"index": 0
},
{
"node": "a4b5eb06-0a3b-4092-b682-dbb77ef9f7a6",
"type": "main",
"index": 0
},
{
"node": "5dac1e5f-a814-48a7-beaf-b0657d1ff926",
"type": "main",
"index": 0
}
]
]
},
"46d2cd63-dd9b-41de-a050-a7b0106ec6c7": {
"main": [
[
{
"node": "e9ef5bb7-b017-4068-abe2-937c077d9630",
"type": "main",
"index": 0
}
]
]
},
"b5b5eb35-4402-471e-a15c-7b6f38a46c18": {
"main": [
[
{
"node": "4214e518-1d16-4d4f-83c1-271fe0ab4e61",
"type": "main",
"index": 0
}
]
]
},
"a4b5eb06-0a3b-4092-b682-dbb77ef9f7a6": {
"main": [
[
{
"node": "c763d9da-66e1-41a6-881f-6f3f210395aa",
"type": "main",
"index": 0
}
]
]
},
"90adc41b-f6bf-4a03-894d-3ae50067f64d": {
"main": [
[
{
"node": "bdff8dcb-4319-484a-b7b9-6a25c3a957df",
"type": "main",
"index": 0
}
]
]
},
"e9ef5bb7-b017-4068-abe2-937c077d9630": {
"main": [
[
{
"node": "90adc41b-f6bf-4a03-894d-3ae50067f64d",
"type": "main",
"index": 0
},
{
"node": "b1111c61-bb8a-4f7d-958f-8a09dc75c910",
"type": "main",
"index": 0
}
]
]
},
"104f7e12-094c-4f7f-8ec4-420866771334": {
"main": [
[
{
"node": "90adc41b-f6bf-4a03-894d-3ae50067f64d",
"type": "main",
"index": 0
},
{
"node": "b1111c61-bb8a-4f7d-958f-8a09dc75c910",
"type": "main",
"index": 0
}
]
]
},
"f891f10b-02c3-4eab-ad22-e01f8c6d3e20": {
"main": [
[
{
"node": "423b6343-a63c-42b3-9804-4088e8e1694a",
"type": "main",
"index": 0
}
]
]
},
"02512611-49a2-4319-9423-2a8c84cda262": {
"main": [
[
{
"node": "f891f10b-02c3-4eab-ad22-e01f8c6d3e20",
"type": "main",
"index": 0
}
]
]
},
"1b303d83-c74f-44a9-89e3-3963d707048f": {
"main": [
[
{
"node": "104f7e12-094c-4f7f-8ec4-420866771334",
"type": "main",
"index": 0
}
]
]
},
"bdff8dcb-4319-484a-b7b9-6a25c3a957df": {
"main": [
[
{
"node": "b1111c61-bb8a-4f7d-958f-8a09dc75c910",
"type": "main",
"index": 1
}
]
]
},
"acbba7e0-6a6f-4138-981e-7bc7b7d6e82c": {
"main": [
[
{
"node": "9d019e72-f72f-4e52-8ec2-cdf83fb57700",
"type": "main",
"index": 0
}
]
]
},
"bed8d683-fe25-4910-98c4-23ae96418579": {
"main": [
[
{
"node": "b5b5eb35-4402-471e-a15c-7b6f38a46c18",
"type": "main",
"index": 0
}
]
]
},
"5dac1e5f-a814-48a7-beaf-b0657d1ff926": {
"main": [
[
{
"node": "acbba7e0-6a6f-4138-981e-7bc7b7d6e82c",
"type": "main",
"index": 0
}
]
]
},
"b599b087-9f76-4183-8b39-c15cba123e0c": {
"main": [
[
{
"node": "bed8d683-fe25-4910-98c4-23ae96418579",
"type": "main",
"index": 0
}
]
]
},
"62321b02-c786-4397-96dd-c86532968664": {
"ai_languageModel": [
[
{
"node": "acbba7e0-6a6f-4138-981e-7bc7b7d6e82c",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"2a067c01-1113-41f1-8165-484f83e2c86c": {
"ai_outputParser": [
[
{
"node": "acbba7e0-6a6f-4138-981e-7bc7b7d6e82c",
"type": "ai_outputParser",
"index": 0
}
]
]
}
}
}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
上級 - 市場調査, AI要約
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
関連ワークフロー
毎日の WhatsApp グループ スマート分析：GPT-4.1 による分析と音声メッセージの transcrição
毎日の WhatsApp グループ インタラクティブ分析：GPT-4.1 分析と音声メッセージ文字起こし
If
Set
Code
+
If
Set
Code
52 ノードDaniel Lianes
その他
01 AIメディアバイヤーでFacebook広告のパフォーマンスを分析し、インサイトをGoogle Sheetsへ送信
Gemini AIを使用してFacebook広告を分析し、インサイトをGoogle Sheetsに送信
If
Set
Code
+
If
Set
Code
34 ノードJJ Tham
市場調査
MetaAdsクリエイティブインサイトリサーチャーv1.4
Google VisionとVideo Intelligence APIを使ってMeta広告のクリエイティブを分析する
If
Set
Code
+
If
Set
Code
32 ノードKirill Khatkevich
市場調査
n8nノードの探索（可視化リファレンスライブラリ内）
n8nノードを可視化リファレンスライブラリで探索
If
Ftp
Set
+
If
Ftp
Set
113 ノードI versus AI
その他
アイデア捕集テンプレート
Reddit、YouTube、Xを分析してコンテンツ戦略レポートを生成するGeminiの使用
If
Set
Code
+
If
Set
Code
34 ノードSheryl
市場調査
コンテンツ集約
Gemini AIを使ってウェブ記事からLinkedInとX/Twitterへのソーシャルメディア投稿を自動化する
If
Set
Xml
+
If
Set
Xml
34 ノードVadim
コンテンツ作成
