Clasificación de palabras clave
Este es unautomatización que contiene 40 nodos.Utiliza principalmente nodos como Set, Filter, Airtable, SplitOut, Aggregate. Clasificación de palabras clave SEO y creación de estrategia de contenido con IA y Airtable
- •Clave de API de Airtable
- •Clave de API de OpenAI
Nodos utilizados (40)
Categoría
{
"id": "mGgSDkJTDBI4mq1J",
"meta": {
"instanceId": "642e489d8be5ef18e94f4513d3dbcdb97cfdc6b36fc67668bf60c866346c5a09",
"templateCredsSetupCompleted": true
},
"name": "Categorize Keywords",
"tags": [
{
"id": "AZvUGDdqsfK0AaPB",
"name": "Content Creation",
"createdAt": "2025-09-09T14:22:23.903Z",
"updatedAt": "2025-09-09T14:22:23.903Z"
}
],
"nodes": [
{
"id": "478452bb-0bf2-46c0-8644-d4f9bd2e31c7",
"name": "Al hacer clic en 'Probar flujo de trabajo'",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-1024,
864
],
"parameters": {},
"typeVersion": 1
},
{
"id": "95bd2d16-c8eb-4841-8a89-61f60bb111ac",
"name": "Nota adhesiva",
"type": "n8n-nodes-base.stickyNote",
"position": [
48,
224
],
"parameters": {
"width": 520,
"height": 540,
"content": "## Gets KWs from Master List and Categorizes\nCategorizes keywords as Quick Wins, Authority Builders, Emerging Topics, and Unknown."
},
"typeVersion": 1
},
{
"id": "c222ee7d-0791-40ad-9780-e3d067d01ffa",
"name": "Nota adhesiva1",
"type": "n8n-nodes-base.stickyNote",
"position": [
848,
144
],
"parameters": {
"width": 520,
"height": 260,
"content": "## Send All Categorized Keywords to Airtable\n"
},
"typeVersion": 1
},
{
"id": "b99967c3-a895-47bf-9b57-cbdde4f3394b",
"name": "Nota adhesiva2",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
448
],
"parameters": {
"width": 1720,
"height": 460,
"content": "## Creates Title and Description for each categorized keyword.\nSends to Airtable"
},
"typeVersion": 1
},
{
"id": "4d98bb25-96b6-4e2c-8e1d-1b9929259ea5",
"name": "Agente: Crear Oportunidades de Contenido",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1440,
1504
],
"parameters": {
"text": "=For each of the {{ $('Edit Fields2').item.json.number_of_clusters }} clusters, consider its:\n- cluster_name: {{ $json.cluster_name }}\n- core_topic: {{ $json.core_topic }}\n- intent_pattern:{{ $json.intent_pattern }}\n- keywords: {{ $json.keywords }}\n- reasoning: {{ $json.reasoning }}\n- primary_keyword: {{ $json.primary_keyword }}\nTo create one hub article and 5 spoke articles.\n\nYou are creating a hub and spoke content strategy. For each hub and spoke article, you will create:\n- title: an seo-optimized title that is engaging and reflects the article content. It is around 60 characters long.\n- description: 3 to 5 paragraphs desribing the article\n- keyword: the primary keyword of the article\n\nTo create the clusters group all keywords with the same cluster_name. Give each cluster a name and type of either hub or spoke. There will be one hub article and up to 5 spoke articles per cluster.\n\nThe hub article serves as the central piece of content that provides a broad overview of a main topic. The spoke articles are detailed content pieces that branch out from the hub, each focusing on specific subtopics.\n\nImportant: Each cluster as defined above should have one hub article and up to 5 spoke articles. Always make sure that hub and spoke articles are created for each cluster.\nConsider the following when creating the hub and spoke articles.\n1. cluster_name\n2. title\n- SEO-optimized\n- Under 62 characters\n3. description\n- 3-5 paragraphs desribing the article\n4. type \n- hub or spoke\n\nReturn a single-line JSON object with this structure for each cluster (no line breaks). \n {\n \"cluster_name\": \"descriptive name\",\n \"title\": \"the title\",\n \"description\": \"the description\",\n \"type\": \"either hub or spoke\",\n \"keyword\": \"the primary keyword\"\n \"reasoning\": \"reasoning for the cluster\"\n }\n\nImportant: Return ONLY the JSON array with NO line breaks (\\n), NO extra quotations, NO extra spaces, and NO additional text.\n\n\n\n",
"options": {
"systemMessage": "You are an AI content strategist specializing in creating seo-optimized hub and spoke content structures. For each cluster, create one main hub article and up to 5 supporting spoke articles that comprehensively cover the topic while maintaining SEO best practices and user intent.\n"
},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "88679472-31f9-499f-86f0-7b06fa058f0b",
"name": "Nota adhesiva4",
"type": "n8n-nodes-base.stickyNote",
"position": [
32,
1072
],
"parameters": {
"width": 800,
"height": 520,
"content": "## Clusters KWs from Master KW All Variations List\nCreates clusters based on semantic similarity and search intent."
},
"typeVersion": 1
},
{
"id": "b482852c-8502-4b0d-b42e-819a1cb02e9a",
"name": "Nota adhesiva5",
"type": "n8n-nodes-base.stickyNote",
"position": [
880,
1072
],
"parameters": {
"width": 1120,
"height": 260,
"content": "## Adds Cluster and Keywords to Clusters Sheet\n"
},
"typeVersion": 1
},
{
"id": "1bb158eb-5092-4aa9-be97-98c3fd8a4125",
"name": "Nota adhesiva6",
"type": "n8n-nodes-base.stickyNote",
"position": [
880,
1360
],
"parameters": {
"width": 1600,
"height": 460,
"content": "## Create Hub and Spoke Content Opportunities\nCreates title and description for Hub and Spoke content opportunities.\nPrompted (at the moment) to create 5 supporting articles for each pillar."
},
"typeVersion": 1
},
{
"id": "a52ef80c-284c-491b-a4c5-509748fffd10",
"name": "Nota adhesiva7",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
0
],
"parameters": {
"color": 3,
"width": 2544,
"height": 920,
"content": "## Categorize and Create Content Opportunities\n"
},
"typeVersion": 1
},
{
"id": "656ea262-9516-4ef9-9ac7-3748d18d0ae9",
"name": "Nota adhesiva8",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
960
],
"parameters": {
"color": 3,
"width": 2540,
"height": 920,
"content": "## Cluster and Create Content Opportunities\n"
},
"typeVersion": 1
},
{
"id": "85391b1c-4813-4466-a710-4055f8788421",
"name": "Filtrar Desconocidos",
"type": "n8n-nodes-base.filter",
"position": [
880,
560
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fa613938-57a8-49f6-a01b-723028c6cbf3",
"operator": {
"type": "string",
"operation": "notEquals"
},
"leftValue": "={{ $json.fields.Category }}",
"rightValue": "Unknown"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "7ad32cab-aa16-4f85-ac97-9b4c395ef649",
"name": "Establecer Campos de Tabla de Categorías",
"type": "n8n-nodes-base.set",
"position": [
944,
240
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "3f1f38b9-8941-4047-8904-270b17bfc2ed",
"name": "keyword",
"type": "string",
"value": "={{ JSON.parse($json.output).keyword }}"
},
{
"id": "849f572c-1339-4a83-bd4c-2b4c13cd80d4",
"name": "category",
"type": "string",
"value": "={{ JSON.parse($json.output).category }}"
},
{
"id": "5909d7fe-6050-490d-bf90-ad0817d882a0",
"name": "reasoning",
"type": "string",
"value": "={{ JSON.parse($json.output).reasoning }}"
},
{
"id": "aeb81379-fba7-483d-828c-427f2851ee87",
"name": "msv",
"type": "number",
"value": "={{ JSON.parse($json.output).msv }}"
},
{
"id": "3b7b8188-de51-4a6b-95cb-73a8de200996",
"name": "kw_difficulty",
"type": "number",
"value": "={{ JSON.parse($json.output).kw_difficulty }}"
},
{
"id": "013f802d-6c2e-4519-8104-5d3951f845cd",
"name": "search_intent",
"type": "string",
"value": "={{ JSON.parse($json.output).search_intent }}"
},
{
"id": "a2799b9e-8c28-4c02-8162-2874cae2bf2b",
"name": "competition",
"type": "string",
"value": "={{ JSON.parse($json.output).competition }}"
},
{
"id": "7929eaff-788c-43fa-899f-cd04953f8f7f",
"name": "cpc",
"type": "number",
"value": "={{ JSON.parse($json.output).cpc }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "43bb97fe-3742-4f59-a010-6f62e78015f7",
"name": "Tabla de Categorías",
"type": "n8n-nodes-base.airtable",
"position": [
1168,
240
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set Airtable Fields').item.json.airtable_base_id }}"
},
"table": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set Airtable Fields').item.json.categories_table_id }}"
},
"columns": {
"value": {
"CPC": "={{ $json.cpc }}",
"MSV": "={{ $json.msv }}",
"Keyword": "={{ $json.keyword }}",
"Category": "={{ $json.category }}",
"Reasoning": "={{ $json.reasoning }}",
"Competition": "={{ $json.competition }}",
"KW Difficulty": "={{ $json.kw_difficulty }}",
"Search Intent": "={{ $json.search_intent }}"
},
"schema": [
{
"id": "Category",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Category",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Keyword",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Keyword",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Reasoning",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Reasoning",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "MSV",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "MSV",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "KW Difficulty",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "KW Difficulty",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Search Intent",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Search Intent",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Competition",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Competition",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "CPC",
"type": "number",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "CPC",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "create"
},
"credentials": {
"airtableTokenApi": {
"id": "IdMuG6Ja3xc0kVnw",
"name": "Airtable Personal Access Token account"
}
},
"typeVersion": 2.1
},
{
"id": "e20decb0-fd75-4cd4-8b4c-3143d2dd9217",
"name": "Establecer Contenido desde Campos de Categoría",
"type": "n8n-nodes-base.set",
"position": [
1104,
560
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "cae1e309-cab6-472a-9bfc-75448a504455",
"name": "keyword",
"type": "string",
"value": "={{ $json.fields.Keyword }}"
},
{
"id": "1c725316-fa66-401c-b028-6039c7845540",
"name": "category",
"type": "string",
"value": "={{ $json.fields.Category }}"
},
{
"id": "328a070b-312e-4c39-bacb-970d0e485e7a",
"name": "reasoning",
"type": "string",
"value": "={{ $json.fields.Reasoning }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "852c9c71-f2bd-4aa6-abed-5f6a4aee633d",
"name": "Agente de IA de Categorías",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
192,
368
],
"parameters": {
"text": "=Please categorize the following keywords according to the rules. Ensure every keyword is processed and included in the output.\n\nKeyword to Categorize and Data for Categorization:\n {{ $json.keyword }}\n{{ $json.msv }}\n{{ $json.search_intent }}\n{{ $json.kw_difficulty }}\n{{ $json.competition }}\n{{ $json.cpc }}\n",
"options": {
"systemMessage": "You are an AI agent specialized in analyzing and categorizing SEO keywords and search intent signals.\n\nCategorization Rules:\n1. Quick Wins:\n - MSV > 100 AND KW Difficulty < 30\n - These are opportunities for relatively fast ranking\n\n2. Authority Builders:\n - KW Difficulty > 50 AND MSV > 200\n - High-value terms worth investing in for authority building\n\n3. Emerging Topics:\n - MSV < 100 OR (doesn't fit Quick Wins AND shows future potential)\n - Focus on search intent and growth potential\n- Represent trends or novel concepts that are likely to grow in popularity\n\n4. Intent Signals:\n - People Also Ask questions\n - Direct user questions that show search intent\n - Good opportunities for featured snippets and AI results\n - Categorize here even if metrics are missing\n\n5. Semantic Topics:\n - Autocomplete suggestions and semantic subtopics\n - Related concepts that build topic authority\n - Categorize here even if metrics are missing\n\n6. Unknown:\n - Keywords that don't fit other categories\n - Or have insufficient data and aren't questions/semantic topics\n\nReturn only a JSON object for each keyword with these exact fields:\n{\n \"keyword\": \"exact keyword text\",\n \"category\": \"Quick Wins|Authority Builders|Emerging Topics|Intent Signals|Semantic Topics|Unknown\",\n \"reasoning\": \"brief explanation of categorization\",\n \"msv\": number or null,\n \"kw_difficulty\": number or null,\n \"search_intent\": \"original intent or null\",\n \"competition\": \"original competition or null\",\n \"cpc\": number or null\n}\n\n\nImportant: Return ONLY the JSON object with NO line breaks (\\n), NO extra spaces, and NO additional text.\n\nImportant:\n- Process EVERY keyword in the input\n- Preserve all original data\n- Ensure total_processed matches input count\n- Provide brief reasoning for each categorization\n- please be accurate with the language, if the researches are made in Dutch, write in Dutch"
},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "61240f06-f973-49de-9327-08130f0a3b39",
"name": "Ideas de Contenido del Agente de IA de Categorías",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1584,
640
],
"parameters": {
"text": "=For each keyword, analyze its category and reasoning to create:\n\n1. A title that:\n - Captures search intent\n - Is engaging and clickable\n - Includes the main keyword naturally\n - Is optimized for both search and social sharing\n - Is under 60 characters\n - Aligns with the category context: {{ $json.category }}\n \n2. A description that:\n - Clearly outlines the main topics and key points the article should cover\n - Indicates specific value readers will gain\n - Provides enough context to guide content creation\n - Naturally incorporates the keyword\n - Is concise but comprehensive (aim for 2-3 sentences)\n - Considers the categorization reasoning: {{ $json.reasoning }}\n\nInput:\n\n{{ $json.keyword }}\n\nReturn a single-line JSON object with this structure (no line breaks):\n{\"keyword\":\"input keyword\",\"title\":\"created title\",\"description\":\"article description\"}",
"options": {
"systemMessage": "You are an AI content strategist specialized in creating engaging, SEO-optimized titles and article descriptions."
},
"promptType": "define"
},
"typeVersion": 1.7
},
{
"id": "ccf02d2e-596b-47fa-bea5-9f5ba666c054",
"name": "Establecer Campos del Flujo de Trabajo",
"type": "n8n-nodes-base.set",
"position": [
-208,
864
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "acee4494-86dc-4f48-b5d8-e18e7db9eaaa",
"name": "keyword",
"type": "string",
"value": "={{ $json.Keyword }}"
},
{
"id": "575ec827-4dd3-4d4c-8aca-14c80f4a9015",
"name": "record_id",
"type": "string",
"value": "={{ $json.id }}"
},
{
"id": "b5d76b17-8473-4369-9c50-7c0194bce34e",
"name": "primary_keyword",
"type": "string",
"value": "={{ $json['Primary Keyword'] }}"
},
{
"id": "8e4e71d4-662f-4c59-9f01-5b0f14ffb54f",
"name": "competition",
"type": "string",
"value": "={{ $json.Competition }}"
},
{
"id": "5925b3bb-8581-4dfa-9aec-b3578cabef35",
"name": "msv",
"type": "number",
"value": "={{ $json.MSV }}"
},
{
"id": "4de58314-1701-4a95-9826-f28233c1a87d",
"name": "search_intent",
"type": "string",
"value": "={{ $json['Search Intent'] }}"
},
{
"id": "dfb906d8-3c2e-446e-bee3-d24ba4610927",
"name": "kw_difficulty",
"type": "number",
"value": "={{ $json['KW Difficulty'] }}"
},
{
"id": "2fdf1cd1-742b-418b-8966-33823c5aa90b",
"name": "type",
"type": "string",
"value": "={{ $json.Type }}"
},
{
"id": "89472023-1df7-4d64-b874-9106dee97866",
"name": "cpc",
"type": "number",
"value": "={{ $json.CPC }}"
},
{
"id": "9fdccded-22de-4daf-86bb-67ae1db5bfec",
"name": "Date Pulled from D4SEO",
"type": "string",
"value": "={{ $json['Date Pulled from D4SEO'] }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "9eb70197-dc70-4696-8c0f-3175200d2bc3",
"name": "Establecer Campo de Tabla de Ideas de Contenido",
"type": "n8n-nodes-base.set",
"position": [
1952,
640
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "3b11eddb-dfa2-4e28-a4e5-8cf3996e3e56",
"name": "keyword",
"type": "string",
"value": "={{ JSON.parse($json.output).keyword }}"
},
{
"id": "eaa730fd-678f-42fb-95d7-fb0210fefcd7",
"name": "title",
"type": "string",
"value": "={{ JSON.parse($json.output).title }}"
},
{
"id": "eb7f4d7d-c669-4f13-acfc-109e6af78f96",
"name": "description",
"type": "string",
"value": "={{ JSON.parse($json.output).description }}"
},
{
"id": "76254565-f080-41d6-b8ed-e71d22c315da",
"name": "primary_keyword",
"type": "string",
"value": "={{ $('Set WF Fields').item.json.primary_keyword }}"
},
{
"id": "619a217e-8526-499d-826a-8874364f0b3b",
"name": "reasoning",
"type": "string",
"value": "={{ $('Filter Out Unknown').item.json.fields.Reasoning }}"
},
{
"id": "74a4cb6e-8ca6-4ebe-b821-1b26d018d1b8",
"name": "category",
"type": "string",
"value": "={{ $('Filter Out Unknown').item.json.fields.Category }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "27cbaea3-5b5d-4c2c-b687-3f0784aec8a7",
"name": "Tabla de Ideas de Contenido de Categorías",
"type": "n8n-nodes-base.airtable",
"position": [
2160,
640
],
"parameters": {
"base": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set Airtable Fields').item.json.airtable_base_id }}"
},
"table": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set Airtable Fields').item.json.content_ideas_from_kws_table_id }}"
},
"columns": {
"value": {
"Title": "={{ $json.title }}",
"Status": "Not Started",
"Keyword": "={{ $json.keyword }}",
"Category": "={{ $json.category }}",
"Reasoning": "={{ $json.reasoning }}",
"Description": "={{ $json.description }}",
"Primary Keyword": "={{ $json.primary_keyword }}"
},
"schema": [
{
"id": "Title",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Status",
"type": "options",
"display": true,
"options": [
{
"name": "Not Started",
"value": "Not Started"
},
{
"name": "Send to Article Writer",
"value": "Send to Article Writer"
},
{
"name": "Discard",
"value": "Discard"
},
{
"name": "In Article Writer",
"value": "In Article Writer"
}
],
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Status",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Description",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Description",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Keyword",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Keyword",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Primary Keyword",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Primary Keyword",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Category",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
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{
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"text": "=Analyze ALL keywords as a complete dataset and identify natural semantic clusters. Let the number and size of clusters emerge from the relationships in the data. Each keyword should be assigned to its most relevant cluster based on semantic meaning and user intent.\n\nGuidelines for clustering:\n- Identify genuine thematic relationships across keywords\n- Group keywords based on semantic similarity and shared user intents\n- Consider how different keyword types complement each other in revealing topic patterns\n- Let cluster count and size be determined by the natural groupings in the data\n- Each keyword should belong to exactly one cluster\n\nReturn a single-line JSON object with this structure (no line breaks):\n{\n \"total_keywords_processed\": number,\n \"number_of_clusters\": number,\n \"clusters\": [\n {\n \"cluster_name\": \"descriptive name\",\n \"core_topic\": \"main theme or focus\",\n \"intent_pattern\": \"primary user intent pattern\",\n \"keywords\": [\"array of all keywords in this cluster\"],\n \"reasoning\": \"explanation of why these keywords form a coherent cluster\",\n \"primary_keyword\": \"the primary keyword\"\n }\n ]\n}\n\nIMPORTANT: Do not include extra spaces, backticks ```, or any comments about what you did. Do not include \\n in any part of the output.\n\nInput data:\n{{ $json.keyword_dataset }}\n\n",
"options": {
"systemMessage": "=You are an AI expert in semantic analysis and content clustering. Your task is to analyze a collection of keywords holistically and identify natural semantic clusters based on:\n- Thematic relationships\n- User intent patterns\n- Topic hierarchies\n- Search behavior signals across different keyword types (direct searches, questions, suggestions)\n\nConsider both keywords with metrics (search_intent) and those without (people also ask, subtopics, autocomplete) as they represent different aspects of user intent."
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"assignments": [
{
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},
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"content": "# Setup \n\n## 1. Copy this Airtable base: [KW Research Content Ideation](https://airtable.com/apphzhR0wI16xjJJs/shrsojqqzGpgMJq9y)\n## Important: Copy the base. Please do not ask for access. \n## 2. Set Airtable Base Id\nWith your (copied) Airtable base open (to any table), copy the base id from the url.\n\nThe base id begins with app. For example: https://airtable.com/apphzhR0wI16xjJJs/tblewTSMwBdGQKUuZ/\napphzhR0wI16xjJJs is the base id. Enter this into the Set Airtable Fields node.\n\n## 3. Enter the table id of the following tables into the Set Airtable Fields node.\n- Master All KW Variations\n- Keyword Categories\n- Content Ideas for Keywords\n- Clusters\n- Content Ideas from Clusters\n\nThe table id is after the base id. For example.\nhttps://airtable.com/apphzhR0wI16xjJJs/tblD8sMi6W4EikkN4/viw8DZMvccWGY7YuO?blocks=hide\n\ntblD8sMi6W4EikkN4 is the table id.\n\n## 4. Test your automation\nSelect Test Workflow."
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{
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{
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"Title": "={{ $json.title }}",
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"Reasoning": "={{ $json.reasoning }}",
"Description": "={{ $json.description }}",
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{
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{
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{
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{
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{
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],
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"mode": "id",
"value": "={{ $('Set Airtable Fields').item.json.airtable_base_id }}"
},
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"mode": "id",
"value": "={{ $('Set Airtable Fields').item.json.clusters_table_id }}"
},
"columns": {
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"Core Topic": "={{ $('Set Fields for Airtable').item.json.core_topic }}",
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{
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],
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},
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}
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},
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}¿Cómo usar este flujo de trabajo?
Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.
¿En qué escenarios es adecuado este flujo de trabajo?
Avanzado
¿Es de pago?
Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.
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Gloria
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