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Workflow n8n

Automatisation SEO avec n8n : recherche de mots-clés optimisée

  • Ce workflow n8n est conçu pour automatiser la recherche de mots-clés SEO en utilisant des outils d'intelligence artificielle et des analyses concurrentielles. Dans un contexte où le référencement est crucial pour la visibilité en ligne, cette automatisation permet aux spécialistes du marketing et aux agences d'optimiser leur stratégie de contenu en identifiant les mots-clés les plus pertinents et en évaluant leur difficulté. Grâce à ce workflow, vous pouvez générer des recommandations de mots-clés basées sur des données réelles, ce qui vous permet de rester compétitif sur le marché.
  • Le processus commence par un déclencheur Webhook qui récupère les données d'entrée depuis NocoDB. Ensuite, plusieurs modèles d'OpenAI sont utilisés pour analyser les mots-clés, effectuer une expansion de sujets et réaliser une analyse concurrentielle. Les nœuds de DataForSEO sont intégrés pour évaluer la difficulté des mots-clés et obtenir des informations sur le volume de recherche et le coût par clic. Les résultats sont ensuite agrégés et formatés, permettant de créer une stratégie de mots-clés finale. Ce workflow inclut également des notifications via Slack pour tenir les équipes informées des mises à jour.
  • En mettant en place cette automatisation n8n, les entreprises peuvent réduire le temps consacré à la recherche de mots-clés, minimiser les erreurs humaines et obtenir des résultats plus précis. Cela se traduit par une meilleure stratégie de contenu, une augmentation du trafic organique et une amélioration de la visibilité en ligne. En somme, ce workflow représente une valeur ajoutée significative pour toute équipe marketing cherchant à optimiser son SEO.
Tags clés :SEOautomatisationn8nmarketing digitalrecherche de mots-clés
🎯Pour qui ?🧩Problème résolu📋Étapes du flux🛠Guide de personnalisation
Catégorie: Webhook · Tags: SEO, automatisation, n8n, marketing digital, recherche de mots-clés❤ 0

Workflow n8n SEO, marketing digital, recherche de mots-clés : vue d'ensemble

Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.

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Workflow n8n SEO, marketing digital, recherche de mots-clés : détail des nœuds

  • OpenAI Chat Model

    Ce noeud utilise le modèle de chat OpenAI pour générer des réponses basées sur les paramètres fournis.

  • Structured Output Parser

    Ce noeud analyse la sortie de données structurées en utilisant un schéma JSON exemple.

  • Topic Expansion

    Ce noeud développe des sujets à partir d'un texte donné en utilisant des options et un type de prompt.

  • Competitor Analysis

    Ce noeud effectue une analyse des concurrents en générant des réponses basées sur le texte et les options fournies.

  • Keyword Difficulty

    Ce noeud évalue la difficulté des mots-clés en fonction des paramètres spécifiés.

  • Search Volume & CPC

    Ce noeud récupère les données de volume de recherche et de coût par clic (CPC) pour des mots-clés donnés sur une période spécifiée.

  • split primary keywords

    Ce noeud divise les mots-clés principaux en fonction des options et du champ spécifié.

  • OpenAI Chat Model2

    Ce noeud utilise un modèle de chat OpenAI pour générer des réponses supplémentaires basées sur des paramètres similaires.

  • Keyword Ranking per URL

    Ce noeud récupère le classement des mots-clés par URL en fonction des paramètres fournis.

  • Final Keyword Strategy

    Ce noeud génère une stratégie de mots-clés finale en utilisant un texte donné et des options.

  • Get Input from NocoDB

    Ce noeud reçoit des entrées via un webhook depuis NocoDB selon les paramètres spécifiés.

  • Split the Competitor URLs

    Ce noeud divise les URL des concurrents en fonction des options et du champ spécifié.

  • Set relevant fields

    Ce noeud définit des champs pertinents en fonction des options et des affectations fournies.

  • OpenAI Chat Model1

    Ce noeud utilise un modèle de chat OpenAI pour générer des réponses basées sur des paramètres similaires à un autre noeud.

  • Format Json and add Competitor URLs

    Ce noeud formate les données JSON et ajoute les URL des concurrents en utilisant du code JavaScript.

  • Aggregate SV & CPC

    Ce noeud agrège les données de volume de recherche et de CPC selon les options spécifiées.

  • Aggregate KWD

    Ce noeud agrège les données de difficulté des mots-clés selon les options spécifiées.

  • Merge SV, CPC & KWD

    Ce noeud fusionne les données de volume de recherche, de CPC et de difficulté des mots-clés selon les options fournies.

  • Merge Topic Expansion, SV, CPC & KWD

    Ce noeud fusionne les résultats de l'expansion de sujet, du volume de recherche, du CPC et de la difficulté des mots-clés.

  • Aggregate Competitor Analysis

    Ce noeud agrège les résultats de l'analyse des concurrents selon les options spécifiées.

  • Merge Everything

    Ce noeud fusionne toutes les données collectées selon les options et le nombre d'entrées spécifiés.

  • Write Content Brief

    Ce noeud écrit un brief de contenu dans NocoDB selon les champs et l'opération spécifiés.

  • Update Status - Done

    Ce noeud met à jour le statut d'une tâche à 'Fait' dans NocoDB selon les paramètres fournis.

  • Send Notification

    Ce noeud envoie une notification via Slack avec le texte et les options spécifiés.

  • Start Notification

    Ce noeud envoie une notification de démarrage via Slack avec le texte et les options spécifiés.

  • Update Status - Started

    Ce noeud met à jour le statut d'une tâche à 'Démarré' dans NocoDB selon les paramètres fournis.

  • Sticky Note

    Ce noeud crée une note autocollante avec les paramètres de couleur, largeur, hauteur et contenu spécifiés.

  • Sticky Note1

    Ce noeud crée une note autocollante avec les dimensions et le contenu spécifiés.

  • Sticky Note2

    Ce noeud crée une note autocollante avec les paramètres de couleur, largeur, hauteur et contenu spécifiés.

  • Sticky Note3

    Ce noeud crée une note autocollante avec les paramètres de couleur, largeur, hauteur et contenu spécifiés.

  • Sticky Note4

    Ce noeud crée une note autocollante avec les paramètres de couleur, largeur, hauteur et contenu spécifiés.

  • Sticky Note5

    Ce noeud crée une note autocollante avec les paramètres de couleur, hauteur et contenu spécifiés.

  • Sticky Note6

    Ce noeud crée une note autocollante avec les dimensions et le contenu spécifiés.

  • Sticky Note7

    Ce noeud crée une note autocollante avec les paramètres de couleur, largeur, hauteur et contenu spécifiés.

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{
  "id": "nGpVbW7RTylKujyT",
  "meta": {
    "instanceId": "dcb7e9805ce8fe33e4ef843b02947aacc9de2ca8e3594435f3a36d9f33df54fc",
    "templateCredsSetupCompleted": true
  },
  "name": "AI powered SEO Keyword Research Automation - The vibe Marketer",
  "tags": [
    {
      "id": "SRzFKUr6fVtmWq2d",
      "name": "works",
      "createdAt": "2025-04-14T11:05:17.062Z",
      "updatedAt": "2025-04-14T11:05:17.062Z"
    }
  ],
  "nodes": [
    {
      "id": "65aacfa5-4891-49f9-a614-2866c96142ee",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        88,
        455
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "o1",
          "cachedResultName": "o1"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "AZynAxNG099jyj7B",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "5a0445ad-20c9-4e62-8e04-62451d3e8f7e",
      "name": "Structured Output Parser",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        208,
        455
      ],
      "parameters": {
        "jsonSchemaExample": "{\n  \"primary_keywords\": [\"string\"],\n  \"long_tail_keywords\": [\n    {\n      \"keyword\": \"string\",\n      \"intent\": \"string\"\n    }\n  ],\n  \"question_based_keywords\": [\"string\"],\n  \"related_topics\": [\"string\"]\n}\n"
      },
      "typeVersion": 1.2
    },
    {
      "id": "38cd2c66-d4b7-47a9-a3eb-f58eb32f55ab",
      "name": "Topic Expansion",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        60,
        235
      ],
      "parameters": {
        "text": "=I need to create comprehensive SEO keyword research for content about: \n{{ $json.primary_topic }}\n\nMy target audience is: {{ $json.target_audience }}\nThis will be used for a: {{ $json.content_type }}\nLocation: {{ $json.location }}\nLanguage: {{ $json.language }}\n\nPlease generate:\n1. A list of 20 primary keywords directly related to {{ $json.primary_topic }}\n2. 30 long-tail keyword variations with search intent (informational, commercial, transactional)\n3. 15 question-based keywords people might ask about this topic\n4. 10 related topics that could be used for supporting content\n\nFormat the output as a structured JSON with these categories. ",
        "options": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.8
    },
    {
      "id": "14811f51-5992-4e35-af8d-f05f5b488bc1",
      "name": "Competitor Analysis",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        1100,
        660
      ],
      "parameters": {
        "text": "=Analyze the following competitor content for the Primary Topic \"{{ $('Format Json and add Competitor URLs').item.json.primary_topic }}\":\n\nCompetitor: {{ $('Split the Competitor URLs').item.json.competitorUrls }}\nDATA: ```\n{{ $json.tasks[0].result.toJsonString() }}\n```\n\nPlease identify:\n1. Primary keywords they appear to be targeting\n2. Content gaps or missing topics they aren't covering\n3. Unique angles or approaches they're taking\n4. Questions they're answering (or not answering)\n\nFormat the output as a structured analysis. ",
        "options": {},
        "promptType": "define"
      },
      "typeVersion": 1.8
    },
    {
      "id": "564866ac-c287-48a3-816c-78207dfce133",
      "name": "Keyword Difficulty",
      "type": "n8n-nodes-dataforseo.dataForSeo",
      "position": [
        656,
        260
      ],
      "parameters": {
        "keywords": {
          "values": [
            {
              "value": "={{ $json['output.primary_keywords'] }}"
            }
          ]
        },
        "resource": "labs",
        "operation": "get-keyword-difficulty",
        "language_name_required": "={{ $('Set relevant fields').item.json.language }}",
        "location_name_required": "={{ $('Set relevant fields').item.json.location }}"
      },
      "credentials": {
        "dataForSeoApi": {
          "id": "owHrK02rkWLlYrl3",
          "name": "DataForSEO account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "d39e392c-c547-4edd-8fe9-014c26152915",
      "name": "Search Volume & CPC",
      "type": "n8n-nodes-dataforseo.dataForSeo",
      "position": [
        656,
        60
      ],
      "parameters": {
        "date_to": {},
        "keywords": {
          "values": [
            {
              "value": "={{ $json['output.primary_keywords'] }}"
            }
          ]
        },
        "resource": "keywords_data",
        "date_from": {},
        "language_name": "={{ $('Set relevant fields').item.json.language }}",
        "location_name": "={{ $('Set relevant fields').item.json.location }}"
      },
      "credentials": {
        "dataForSeoApi": {
          "id": "owHrK02rkWLlYrl3",
          "name": "DataForSEO account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "2985d85c-4373-4f18-9c27-188f19c920a6",
      "name": "split primary keywords",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        440,
        160
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "output.primary_keywords"
      },
      "typeVersion": 1
    },
    {
      "id": "49819332-744d-45a5-b0ed-b74a1a57aad8",
      "name": "OpenAI Chat Model2",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1920,
        640
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "o1",
          "cachedResultName": "o1"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "AZynAxNG099jyj7B",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "07576442-14b1-402a-a084-50fd775d6523",
      "name": "Keyword Ranking per URL",
      "type": "n8n-nodes-dataforseo.dataForSeo",
      "position": [
        880,
        660
      ],
      "parameters": {
        "limit": 10,
        "target": "={{ $json.competitorUrls }}",
        "resource": "labs",
        "operation": "get-ranked-keywords",
        "language_name_required": "={{ $('Format Json and add Competitor URLs').item.json.language }}",
        "location_name_required": "={{ $('Format Json and add Competitor URLs').item.json.location }}"
      },
      "credentials": {
        "dataForSeoApi": {
          "id": "owHrK02rkWLlYrl3",
          "name": "DataForSEO account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "1e1f4a81-31b9-450d-85ba-65dbe2b6e8c2",
      "name": "Final Keyword Strategy",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        1940,
        440
      ],
      "parameters": {
        "text": "=# Role: Act as an expert SEO Strategist and Content Planner.\n\n# Context:\n# You are creating an actionable SEO Keyword Strategy & Content Brief based on prior AI-driven keyword generation and competitor analysis.\n# The goal is content creation for the 'Primary Topic', targeting the specified 'Target Audience' and 'Content Type' in the given 'Location' and 'Language'.\n# Data provided includes initial keyword ideas (primary, long-tail, questions), keyword metrics (volume, difficulty), related topics, and competitor analysis insights (their likely keywords, content gaps, unique angles).\n\n# Input Parameters for this Task:\nPrimary Topic: {{ $json.primary_topic }}\nTarget Audience: {{ $json.target_audience }}\nContent Type: {{ $json.content_type }}\nLocation: {{ $json.location }}\nLanguage: {{ $json.language }}\nAnalyzed Compeitors: {{ $json.competitor_urls }}\n\n# Your Task:\n# Analyze the provided input parameters and the detailed 'DATA' section below.\n# Synthesize this information into a clear, concise, and actionable SEO Keyword Strategy & Content Brief.\n# Structure the output logically using Markdown. Focus on providing insights and actionable recommendations, not just listing data. Explain the 'why' behind key recommendations. Keep the language easy to understand, assuming the reader (e.g., a content writer or marketing manager) understands basic SEO concepts but isn't necessarily a deep expert.\n\n# Required Output Sections (Use Markdown Headers):\n\n## 1. Executive Summary\n   - **Objective:** Briefly state the primary goal of creating content on this topic for this audience (e.g., \"Attract [Target Audience] seeking information on [Primary Topic]...\" or \"Position our brand as a thought leader for [Target Audience] regarding [Primary Topic]\").\n   - **Key Opportunity:** Summarize the most significant keyword opportunity identified (e.g., \"Target the high-volume term '[Example Keyword]' while capturing related informational queries via long-tail variations.\")\n   - **Competitor Angle:** Briefly mention the main strategic takeaway from the competitor analysis (e.g., \"Competitors focus heavily on [X], leaving an opportunity to address [Y] or provide a unique angle on [Z].\")\n\n## 2. Target Keyword Strategy & Rationale\n   - **Primary Target Keywords:**\n      - List the top 5-10 recommended primary keywords.\n      - For each, include Search Volume (SV) and Keyword Difficulty (KD).\n      - **Add brief commentary/rationale for each group or key term:** Why were these chosen? (e.g., \"High relevance and strong search volume despite moderate difficulty,\" or \"Balances primary topic focus with user search behavior.\")\n   - **Secondary & Long-Tail Opportunities:**\n      - List the top 10-15 recommended long-tail and secondary keywords.\n      - Group them by likely Search Intent (e.g., Informational, Commercial, Transactional) if discernible from the input data.\n      - **Add brief commentary on the overall opportunity:** What specific user needs or funnel stages do these address? Note any clusters with particularly low competition.\n   - **Key Question Keywords:**\n      - List the top 5 question-based keywords the content *must* answer.\n      - **Add brief commentary:** Why are these questions crucial for the target audience or content goals?\n\n## 3. Competitive Landscape & Content Gaps\n   - **Competitor Focus:** Briefly summarize the main keyword themes or angles competitors seem to be targeting, based on the provided analysis.\n   - **Identified Gaps/Opportunities:** Highlight 1-3 specific content gaps, under-served intents, or unique angles identified from the competitor analysis that this content piece should leverage. Be specific (e.g., \"Competitors explain 'what', but not 'how to implement',\" or \"Lack of practical examples for [Target Audience]\").\n\n## 4. Content Outline & Actionable Recommendations\n   - **Recommended Structure:** Propose a logical H2/H3 structure or outline for the content piece, designed to cover the target keywords and address user intent effectively.\n   - **Keyword Integration:** Briefly suggest how to naturally incorporate the different keyword types (primary, long-tail, questions) within the proposed structure.\n   - **Content Enhancement:** Provide 2-3 specific, actionable recommendations to make the content stand out for the target audience and potentially outperform competitors (e.g., \"Include step-by-step instructions,\" \"Add original data/charts,\" \"Feature quotes from [Target Audience Role],\" \"Create a downloadable checklist\").\n\n## 5. Proposed SEO Titles\n   - List 3-5 compelling, SEO-optimized title options for the content piece. Ensure they are relevant, incorporate keywords naturally, and entice clicks.\n\n# DATA for Analysis:\n# (Analyze the following JSON data containing keyword suggestions, metrics, and competitor analysis results)\n```json\n{{ $json.data.toJsonString() }}\n\n{{ $json.output.toJsonString() }}\n```\n\nFinal Output Format: Ensure the entire response is well-structured, clean Markdown, ready to be used as a content brief.",
        "options": {},
        "promptType": "define"
      },
      "typeVersion": 1.8
    },
    {
      "id": "613e1d25-3e9d-4a7f-8657-392854eb00de",
      "name": "Get Input from NocoDB",
      "type": "n8n-nodes-base.webhook",
      "position": [
        -680,
        340
      ],
      "webhookId": "ac7e989d-6e32-4850-83c4-f10421467fb8",
      "parameters": {
        "path": "ac7e989d-6e32-4850-83c4-f10421467fb8",
        "options": {},
        "httpMethod": "POST"
      },
      "typeVersion": 2
    },
    {
      "id": "88076d36-fe04-4a7a-a176-9ba93388b089",
      "name": "Split the Competitor URLs",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        580,
        660
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "competitorUrls"
      },
      "typeVersion": 1
    },
    {
      "id": "88d8ad2f-4b66-48e3-aaf7-d6f8210f264b",
      "name": "Set relevant fields",
      "type": "n8n-nodes-base.set",
      "position": [
        -500,
        340
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "e729ab88-95f8-44c0-948c-d2476262fd17",
              "name": "primary_topic",
              "type": "string",
              "value": "={{ $json.body.data.rows[0]['Primary Topic'] }}"
            },
            {
              "id": "1c6fbf22-fb3f-4577-b6cc-4d0672ff2046",
              "name": "competitor_urls",
              "type": "string",
              "value": "={{ $json.body.data.rows[0]['Competitor URLs'] }}"
            },
            {
              "id": "ea8518c8-8f89-4aa5-9546-44be77deeebb",
              "name": "target_audience",
              "type": "string",
              "value": "={{ $json.body.data.rows[0]['Target Audience'] }}"
            },
            {
              "id": "4b27d628-6cc1-4161-bb49-d39a4b1d320e",
              "name": "content_type",
              "type": "string",
              "value": "={{ $json.body.data.rows[0]['Content Type'] }}"
            },
            {
              "id": "bb3fefe7-7eea-4a6d-b2de-307b791ff1b6",
              "name": "id",
              "type": "string",
              "value": "={{ $json.body.data.rows[0].Id }}"
            },
            {
              "id": "09e64ce6-39de-4550-9078-fe4f233edd9a",
              "name": "status",
              "type": "string",
              "value": "={{ $json.body.data.rows[0].Status }}"
            },
            {
              "id": "c10736b0-dece-40a7-9fb0-86b23b44e517",
              "name": "location",
              "type": "string",
              "value": "={{ $json.body.data.rows[0].Location }}"
            },
            {
              "id": "6508a1e9-963d-4a79-bd35-f537c892e8d4",
              "name": "language",
              "type": "string",
              "value": "={{ $json.body.data.rows[0].Language }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "1f083fb0-8b55-43f0-85de-58a81f30a9f2",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1100,
        860
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "o1",
          "cachedResultName": "o1"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "AZynAxNG099jyj7B",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "ffcc38ac-0f0a-4fc7-8e65-86950ea6a01d",
      "name": "Format Json and add Competitor URLs",
      "type": "n8n-nodes-base.code",
      "position": [
        300,
        660
      ],
      "parameters": {
        "jsCode": "const inputJson = $input.first().json;\nconst rawUrls = inputJson.competitor_urls;\n\nconst competitorUrls = rawUrls\n  .split(\",\")\n  .map(url => url.trim())\n  .filter(url => url.length > 0);\n\nconst outputJson = {\n  ...inputJson,\n  competitorUrls: competitorUrls\n};\n\nreturn [{ json: outputJson }];\n"
      },
      "typeVersion": 2
    },
    {
      "id": "cf522a25-6e62-4a34-b5dd-6684ea67e938",
      "name": "Aggregate SV & CPC",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        880,
        60
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData"
      },
      "typeVersion": 1
    },
    {
      "id": "781614a6-7afd-4465-86cb-05ef781b70fe",
      "name": "Aggregate KWD",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        880,
        260
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData"
      },
      "typeVersion": 1
    },
    {
      "id": "15ab5e60-1f8d-4fd5-bfd8-983a8e0861bb",
      "name": "Merge SV, CPC & KWD",
      "type": "n8n-nodes-base.merge",
      "position": [
        1174,
        160
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineByPosition"
      },
      "typeVersion": 3.1
    },
    {
      "id": "19b056e8-8fb3-436a-b8be-356eeedbb57e",
      "name": "Merge Topic Expansion, SV, CPC & KWD",
      "type": "n8n-nodes-base.merge",
      "position": [
        1472,
        235
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineByPosition"
      },
      "typeVersion": 3.1
    },
    {
      "id": "460a5cf3-691e-44c8-a1d3-8dcd43728851",
      "name": "Aggregate Competitor Analysis",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        1472,
        660
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData"
      },
      "typeVersion": 1
    },
    {
      "id": "b28fe5bb-2ca1-4c02-b45f-033af494d706",
      "name": "Merge Everything",
      "type": "n8n-nodes-base.merge",
      "position": [
        1720,
        440
      ],
      "parameters": {
        "mode": "combine",
        "options": {
          "includeUnpaired": false
        },
        "combineBy": "combineByPosition",
        "numberInputs": 3
      },
      "typeVersion": 3.1
    },
    {
      "id": "a4851979-f231-458b-be3f-13eb3c14b0ee",
      "name": "Write Content Brief ",
      "type": "n8n-nodes-base.nocoDb",
      "position": [
        2320,
        440
      ],
      "parameters": {
        "table": "mfsjucjn304v1hc",
        "fieldsUi": {
          "fieldValues": [
            {
              "fieldName": "primary_topic_used",
              "fieldValue": "={{ $('Merge Everything').item.json.primary_topic }}"
            },
            {
              "fieldName": "report_content",
              "fieldValue": "={{ $json.output }}"
            }
          ]
        },
        "operation": "create",
        "projectId": "pl6znsxtne8x3yh",
        "authentication": "nocoDbApiToken"
      },
      "credentials": {
        "nocoDbApiToken": {
          "id": "Nqxw0TptKnROWv9i",
          "name": "NocoDB (hosted) Token account"
        }
      },
      "typeVersion": 3
    },
    {
      "id": "e13ecdf4-0696-4bd7-bbf5-49cb508072c6",
      "name": "Update Status - Done",
      "type": "n8n-nodes-base.nocoDb",
      "position": [
        2320,
        600
      ],
      "parameters": {
        "table": "mp3qmbuye3pyihc",
        "fieldsUi": {
          "fieldValues": [
            {
              "fieldName": "Id",
              "fieldValue": "={{ $('Merge Everything').item.json.id }}"
            },
            {
              "fieldName": "=Status",
              "fieldValue": "Done"
            }
          ]
        },
        "operation": "update",
        "projectId": "pl6znsxtne8x3yh",
        "authentication": "nocoDbApiToken"
      },
      "credentials": {
        "nocoDbApiToken": {
          "id": "Nqxw0TptKnROWv9i",
          "name": "NocoDB (hosted) Token account"
        }
      },
      "typeVersion": 3
    },
    {
      "id": "c23e1c12-41d3-4c91-8175-f035024c6339",
      "name": "Send Notification",
      "type": "n8n-nodes-base.slack",
      "position": [
        2320,
        800
      ],
      "webhookId": "d4615307-81b9-45a3-9d03-4fe5875811c1",
      "parameters": {
        "text": "=>> DONE << \n\nSEO Keyword Research \nPrimary Topic: {{ $('Merge Everything').item.json.primary_topic }}\nTarget Audience: {{ $('Merge Everything').item.json.target_audience }}\nContent Type: {{ $('Merge Everything').item.json.content_type }}\nLocation: {{ $('Merge Everything').item.json.location }}\nLanguage: {{ $('Merge Everything').item.json.language }}\nCompetitor URLs: {{ $('Merge Everything').item.json.competitor_urls }}",
        "select": "channel",
        "channelId": {
          "__rl": true,
          "mode": "list",
          "value": "C08Q7EQ8JNS",
          "cachedResultName": "seo-keyword-research"
        },
        "otherOptions": {
          "mrkdwn": false,
          "includeLinkToWorkflow": false
        }
      },
      "credentials": {
        "slackApi": {
          "id": "WSpsCFfmEwBZkHv1",
          "name": "Slack account"
        }
      },
      "typeVersion": 2.3
    },
    {
      "id": "acfee96e-7d37-4a36-b652-3b0798688538",
      "name": "Start Notification",
      "type": "n8n-nodes-base.slack",
      "position": [
        -340,
        20
      ],
      "webhookId": "d4615307-81b9-45a3-9d03-4fe5875811c1",
      "parameters": {
        "text": "=>> START << \n\nSEO Keyword Research \nPrimary Topic: {{ $json.primary_topic }}\nTarget Audience: {{ $json.target_audience }}\nContent Type: {{ $json.content_type }}\nLocation: {{ $json.location }}\nLanguage: {{ $json.language }}\nCompetitor URLs: {{ $json.competitor_urls }}",
        "select": "channel",
        "channelId": {
          "__rl": true,
          "mode": "list",
          "value": "C08Q7EQ8JNS",
          "cachedResultName": "seo-keyword-research"
        },
        "otherOptions": {
          "mrkdwn": false,
          "includeLinkToWorkflow": false
        }
      },
      "credentials": {
        "slackApi": {
          "id": "WSpsCFfmEwBZkHv1",
          "name": "Slack account"
        }
      },
      "typeVersion": 2.3
    },
    {
      "id": "5af5855d-b858-4b9f-91bc-1cbb14c08258",
      "name": "Update Status - Started",
      "type": "n8n-nodes-base.nocoDb",
      "position": [
        -140,
        40
      ],
      "parameters": {
        "table": "mp3qmbuye3pyihc",
        "fieldsUi": {
          "fieldValues": [
            {
              "fieldName": "Id",
              "fieldValue": "={{ $json.id }}"
            },
            {
              "fieldName": "=Status",
              "fieldValue": "Started"
            }
          ]
        },
        "operation": "update",
        "projectId": "pl6znsxtne8x3yh",
        "authentication": "nocoDbApiToken"
      },
      "credentials": {
        "nocoDbApiToken": {
          "id": "Nqxw0TptKnROWv9i",
          "name": "NocoDB (hosted) Token account"
        }
      },
      "typeVersion": 3
    },
    {
      "id": "a9db9a15-acc1-411c-b596-810a2ce6b8f6",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -440,
        -140
      ],
      "parameters": {
        "color": 7,
        "width": 480,
        "height": 360,
        "content": "## Notification and Update Status\n"
      },
      "typeVersion": 1
    },
    {
      "id": "bd0e0d35-dce3-47c4-bb85-de02ded10691",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        60,
        40
      ],
      "parameters": {
        "width": 280,
        "height": 540,
        "content": "## Topic Expansion"
      },
      "typeVersion": 1
    },
    {
      "id": "9bb138db-cf51-4614-aeb4-abe7b298aab7",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        400,
        -80
      ],
      "parameters": {
        "color": 5,
        "width": 1220,
        "height": 540,
        "content": "## Search Volume, Cost Per Click, Keyword Difficulty"
      },
      "typeVersion": 1
    },
    {
      "id": "757c15fc-5b5f-44d6-ae06-43dac9c32b2c",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        260,
        600
      ],
      "parameters": {
        "color": 4,
        "width": 1360,
        "height": 460,
        "content": "## Competitor Research"
      },
      "typeVersion": 1
    },
    {
      "id": "5459b4ee-f8dd-426b-b0f2-52b8ad6e1222",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1700,
        260
      ],
      "parameters": {
        "color": 6,
        "width": 500,
        "height": 540,
        "content": "## Merge and write Final Keyword Strategy"
      },
      "typeVersion": 1
    },
    {
      "id": "398ff4dd-d143-4944-96f3-3284cb391d84",
      "name": "Sticky Note5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2260,
        260
      ],
      "parameters": {
        "color": 7,
        "height": 720,
        "content": "## Save, Update Status and Notify"
      },
      "typeVersion": 1
    },
    {
      "id": "7d0ee538-62c7-4bdc-bd4a-be5f600c78b4",
      "name": "Sticky Note6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -740,
        240
      ],
      "parameters": {
        "width": 400,
        "height": 320,
        "content": "## Input"
      },
      "typeVersion": 1
    },
    {
      "id": "42f81576-ac7c-4ab2-a93b-3c95410bd801",
      "name": "Sticky Note7",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        460,
        -280
      ],
      "parameters": {
        "color": 3,
        "width": 820,
        "height": 80,
        "content": "# AI-Powered SEO Keyword Research Automation"
      },
      "typeVersion": 1
    }
  ],
  "active": true,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "9abcff0c-1aff-4594-8796-8828963a3f75",
  "connections": {
    "Aggregate KWD": {
      "main": [
        [
          {
            "node": "Merge SV, CPC & KWD",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "Topic Expansion": {
      "main": [
        [
          {
            "node": "split primary keywords",
            "type": "main",
            "index": 0
          },
          {
            "node": "Merge Topic Expansion, SV, CPC & KWD",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "Merge Everything": {
      "main": [
        [
          {
            "node": "Final Keyword Strategy",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Topic Expansion",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Aggregate SV & CPC": {
      "main": [
        [
          {
            "node": "Merge SV, CPC & KWD",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Keyword Difficulty": {
      "main": [
        [
          {
            "node": "Aggregate KWD",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model1": {
      "ai_languageModel": [
        [
          {
            "node": "Competitor Analysis",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model2": {
      "ai_languageModel": [
        [
          {
            "node": "Final Keyword Strategy",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Competitor Analysis": {
      "main": [
        [
          {
            "node": "Aggregate Competitor Analysis",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Merge SV, CPC & KWD": {
      "main": [
        [
          {
            "node": "Merge Topic Expansion, SV, CPC & KWD",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Search Volume & CPC": {
      "main": [
        [
          {
            "node": "Aggregate SV & CPC",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Set relevant fields": {
      "main": [
        [
          {
            "node": "Topic Expansion",
            "type": "main",
            "index": 0
          },
          {
            "node": "Format Json and add Competitor URLs",
            "type": "main",
            "index": 0
          },
          {
            "node": "Merge Everything",
            "type": "main",
            "index": 2
          },
          {
            "node": "Update Status - Started",
            "type": "main",
            "index": 0
          },
          {
            "node": "Start Notification",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Write Content Brief ": {
      "main": [
        []
      ]
    },
    "Get Input from NocoDB": {
      "main": [
        [
          {
            "node": "Set relevant fields",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Final Keyword Strategy": {
      "main": [
        [
          {
            "node": "Write Content Brief ",
            "type": "main",
            "index": 0
          },
          {
            "node": "Update Status - Done",
            "type": "main",
            "index": 0
          },
          {
            "node": "Send Notification",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "split primary keywords": {
      "main": [
        [
          {
            "node": "Search Volume & CPC",
            "type": "main",
            "index": 0
          },
          {
            "node": "Keyword Difficulty",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Keyword Ranking per URL": {
      "main": [
        [
          {
            "node": "Competitor Analysis",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Structured Output Parser": {
      "ai_outputParser": [
        [
          {
            "node": "Topic Expansion",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Split the Competitor URLs": {
      "main": [
        [
          {
            "node": "Keyword Ranking per URL",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Aggregate Competitor Analysis": {
      "main": [
        [
          {
            "node": "Merge Everything",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "Format Json and add Competitor URLs": {
      "main": [
        [
          {
            "node": "Split the Competitor URLs",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Merge Topic Expansion, SV, CPC & KWD": {
      "main": [
        [
          {
            "node": "Merge Everything",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Workflow n8n SEO, marketing digital, recherche de mots-clés : pour qui est ce workflow ?

Ce workflow s'adresse aux agences de marketing digital, aux spécialistes SEO et aux entreprises cherchant à améliorer leur visibilité en ligne. Il est conçu pour des utilisateurs ayant une connaissance intermédiaire des outils d'automatisation et des pratiques SEO, idéal pour les équipes de taille moyenne à grande.

Workflow n8n SEO, marketing digital, recherche de mots-clés : problème résolu

Ce workflow résout le problème de la recherche manuelle de mots-clés, souvent chronophage et sujette à des erreurs. En automatisant ce processus, il permet d'éliminer les frustrations liées à la collecte de données et à l'analyse concurrentielle. Les utilisateurs bénéficient d'une stratégie de mots-clés optimisée, ce qui peut conduire à une augmentation significative du trafic organique et à une meilleure performance SEO.

Workflow n8n SEO, marketing digital, recherche de mots-clés : étapes du workflow

Étape 1 : Le workflow est déclenché par un Webhook qui récupère les données d'entrée.

  • Étape 1 : Les mots-clés sont analysés à l'aide de modèles d'OpenAI pour l'expansion de sujets et l'analyse concurrentielle.
  • Étape 2 : Les nœuds DataForSEO évaluent la difficulté des mots-clés et fournissent des données sur le volume de recherche et le coût par clic.
  • Étape 3 : Les résultats sont agrégés et formatés, et une stratégie de mots-clés finale est générée.
  • Étape 4 : Des notifications sont envoyées via Slack pour informer les équipes des mises à jour.

Workflow n8n SEO, marketing digital, recherche de mots-clés : guide de personnalisation

Pour personnaliser ce workflow, commencez par modifier le chemin du Webhook pour l'adapter à votre configuration NocoDB. Vous pouvez également ajuster les paramètres des modèles OpenAI en fonction de vos besoins spécifiques. Si vous souhaitez intégrer d'autres outils, examinez les nœuds existants et ajoutez des connexions selon vos préférences. Assurez-vous de sécuriser le flux en vérifiant les autorisations d'accès aux données et en surveillant les performances via les notifications Slack.