Tracker Google SERP + tendances et recommandations (avec Bright Data et Google Gemini)

Name: Tracker Google SERP + tendances et recommandations (avec Bright Data et Google Gemini)
Rating: 4.5 (10 reviews)
Author: Ranjan Dailata

Avancé

Ceci est unAI, Marketingworkflow d'automatisation du domainecontenant 23 nœuds.Utilise principalement des nœuds comme Set, Code, HttpRequest, ConvertToFile, ManualTrigger, combinant la technologie d'intelligence artificielle pour une automatisation intelligente. Suivi, analyse de tendance et recommandations pour les pages de résultats de recherche Google avec Bright Data et Gemini

Prérequis

•Peut nécessiter les informations d'identification d'authentification de l'API cible
•Clé API Google Gemini

Nœuds utilisés (23)

OutputParserStructured

Catégorie

Intelligence Artificielle

Marketing

Aperçu du workflow

Visualisation des connexions entre les nœuds, avec support du zoom et du déplacement

Lors du clic sur 'Tester le workflow'

Définir les champs de saisie

Exécuter la requête Web Bright Data

Google Extracteur de données de recherche

Code

Boucler sur les éléments

Extracteur de données de tendances

Google Modèle de chat Gemini pour recherche Google

Analyseur de sortie structurée pour recherche Google

Google Modèle de chat Gemini pour données de tendances

Extracteur de données de recommandation

Google Modèle de chat Gemini pour recommandation

Analyseur de sortie structurée pour recommandation

Analyseur de sortie structurée pour données de tendances

Code pour recommandations

Code pour tendances

Convertir en fichier pour tendances

Convertir en fichier pour recommandations

Écrire le fichier csv des tendances sur le disque

Écrire le fichier csv des recommandations sur le disque

React Flow

Exporter le workflow

Copiez la configuration JSON suivante dans n8n pour importer et utiliser ce workflow

{
  "id": "77EZJT0bcpkDEigw",
  "meta": {
    "instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40",
    "templateCredsSetupCompleted": true
  },
  "name": "Google SERP Tracker + Trends and Recommendations with Bright Data & Google Gemini",
  "tags": [
    {
      "id": "Kujft2FOjmOVQAmJ",
      "name": "Engineering",
      "createdAt": "2025-04-09T01:31:00.558Z",
      "updatedAt": "2025-04-09T01:31:00.558Z"
    },
    {
      "id": "ZOwtAMLepQaGW76t",
      "name": "Building Blocks",
      "createdAt": "2025-04-13T15:23:40.462Z",
      "updatedAt": "2025-04-13T15:23:40.462Z"
    },
    {
      "id": "ddPkw7Hg5dZhQu2w",
      "name": "AI",
      "createdAt": "2025-04-13T05:38:08.053Z",
      "updatedAt": "2025-04-13T05:38:08.053Z"
    }
  ],
  "nodes": [
    {
      "id": "89c87a2f-ee34-47e4-8efd-a4a95d02b052",
      "name": "Lors du clic sur 'Tester le workflow'",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -380,
        -160
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "44ede7e3-f552-4a70-a538-9d124a4df315",
      "name": "Définir les champs de saisie",
      "type": "n8n-nodes-base.set",
      "position": [
        -120,
        -160
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "0ac91db2-9848-40d4-b942-cd7288597ded",
              "name": "url",
              "type": "string",
              "value": "https://www.google.com/search"
            },
            {
              "id": "7142f0df-3c68-4ce0-8e9b-25101db31312",
              "name": "webhook_notification_url",
              "type": "string",
              "value": "https://webhook.site/c9118da2-1c54-460f-a83a-e5131b7098db"
            },
            {
              "id": "f5b7e10d-bcd8-439c-8e84-ba4af11f2cd2",
              "name": "search",
              "type": "string",
              "value": "best crm for the year 2025"
            },
            {
              "id": "3a0bcec2-ec6d-457f-87a5-b73f4d826b2a",
              "name": "zone",
              "type": "string",
              "value": "web_unlocker1"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "adb4eb44-ae8b-4a5e-bab8-afbf5b91e2a2",
      "name": "Exécuter la requête Web Bright Data",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        120,
        -160
      ],
      "parameters": {
        "url": "https://api.brightdata.com/request",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "sendHeaders": true,
        "authentication": "genericCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "zone",
              "value": "={{ $json.zone }}"
            },
            {
              "name": "url",
              "value": "={{ $json.url }}?q={{ encodeURI($json.search) }}"
            },
            {
              "name": "format",
              "value": "raw"
            }
          ]
        },
        "genericAuthType": "httpHeaderAuth",
        "headerParameters": {
          "parameters": [
            {
              "name": "Content-Type",
              "value": "application/json"
            }
          ]
        }
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "kdbqXuxIR8qIxF7y",
          "name": "Header Auth account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "97f0a53c-81cb-4593-afde-d770547b88d0",
      "name": "Note adhésive 4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        60,
        -440
      ],
      "parameters": {
        "color": 5,
        "width": 440,
        "height": 240,
        "content": "## LLM Usages\n\nGoogle Gemini LLM is being utilized for the structured data extraction handling."
      },
      "typeVersion": 1
    },
    {
      "id": "ca10a555-a4ef-4a2b-8ad1-9abf0e02e2d8",
      "name": "Note adhésive 5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -380,
        -800
      ],
      "parameters": {
        "color": 7,
        "width": 400,
        "height": 340,
        "content": "## Logo\n\n\n![logo](https://images.seeklogo.com/logo-png/43/1/brightdata-logo-png_seeklogo-439974.png)\n"
      },
      "typeVersion": 1
    },
    {
      "id": "1ccd35b4-d56a-4c42-88a1-59453a344700",
      "name": "Note adhésive 1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -380,
        -440
      ],
      "parameters": {
        "width": 400,
        "height": 240,
        "content": "## Note\n\nDeals with the Google SERP Tracker by utilizing the Bright Data and Google Gemini LLM for transforming the profile into a structured JSON response.\n\n**Please make sure to set the input fields node with the filtering criteria, Bright Data zone name, Webhook notification URL**\n\nTest Webhook using - https://webhook.site/\n"
      },
      "typeVersion": 1
    },
    {
      "id": "f9b7f382-4a5a-4ddf-a62c-ee83af913a21",
      "name": "Google Extracteur de données de recherche",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        340,
        -160
      ],
      "parameters": {
        "text": "=Extract the following:\n\nRank (position in list)\n\nTitle\n\nURL\n\nSnippet/description\n\nType (organic/ads/map)\n\n{{ $json.data }}\n\nMake sure to return the data in JSON",
        "batching": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "retryOnFail": true,
      "typeVersion": 1.7
    },
    {
      "id": "f10a9a84-3e4c-4ac0-957e-7fc7308c9fda",
      "name": "Code",
      "type": "n8n-nodes-base.code",
      "position": [
        700,
        -160
      ],
      "parameters": {
        "jsCode": "return $input.first().json.output.results"
      },
      "typeVersion": 2
    },
    {
      "id": "d3621752-4837-4e6f-82af-953e98901b24",
      "name": "Boucler sur les éléments",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        920,
        -160
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 3
    },
    {
      "id": "2f607774-34cf-4b0e-9384-f7214e0896e5",
      "name": "Extracteur de données de tendances",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        1180,
        -140
      ],
      "parameters": {
        "text": "=Extract the trends based on the title and spippet:\n\nTitle : {{ $json.title }}\nSnippet : {{ $json.snippet }}\n\nMake sure to return the data in JSON",
        "batching": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "retryOnFail": true,
      "typeVersion": 1.7
    },
    {
      "id": "551b645b-99d7-4824-ad69-290ea8105689",
      "name": "Google Modèle de chat Gemini pour recherche Google",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        340,
        20
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "9bd32bc8-9452-4e6a-ac54-e3a1317d196e",
      "name": "Analyseur de sortie structurée pour recherche Google",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        520,
        20
      ],
      "parameters": {
        "schemaType": "manual",
        "inputSchema": "{\n  \"$schema\": \"http://json-schema.org/schema#\",\n  \"title\": \"Search Results Schema\",\n  \"type\": \"object\",\n  \"properties\": {\n    \"results\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"required\": [\"rank\", \"title\", \"type\"],\n        \"properties\": {\n          \"rank\": {\n            \"type\": \"integer\",\n            \"minimum\": 1\n          },\n          \"title\": {\n            \"type\": \"string\"\n          },\n          \"url\": {\n            \"type\": \"string\",\n            \"format\": \"uri\"\n          },\n          \"snippet\": {\n            \"type\": \"string\"\n          },\n          \"type\": {\n            \"type\": \"string\",\n            \"enum\": [\"organic\", \"paid\", \"featured\"]\n          }\n        },\n        \"additionalProperties\": false\n      }\n    }\n  },\n  \"required\": [\"results\"],\n  \"additionalProperties\": false\n}\n"
      },
      "typeVersion": 1.2
    },
    {
      "id": "06d01c21-4054-4879-a060-70c1a1bac559",
      "name": "Google Modèle de chat Gemini pour données de tendances",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1180,
        40
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "7c89ac87-28b1-47f3-9f04-b2c05b1a483a",
      "name": "Extracteur de données de recommandation",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        1180,
        -560
      ],
      "parameters": {
        "text": "=Provide recommendations based on the title and spippet:\n\nTitle : {{ $json.title }}\nSnippet : {{ $json.snippet }}\n\nMake sure to return the data in JSON",
        "batching": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "retryOnFail": true,
      "typeVersion": 1.7
    },
    {
      "id": "f1f9cfac-28d0-40a9-9287-b11689570b53",
      "name": "Google Modèle de chat Gemini pour recommandation",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1180,
        -380
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-flash-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "YeO7dHZnuGBVQKVZ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "c008d472-0982-4970-a017-73784c6916e7",
      "name": "Analyseur de sortie structurée pour recommandation",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        1360,
        -380
      ],
      "parameters": {
        "schemaType": "manual",
        "inputSchema": "{\n  \"$schema\": \"https://json-schema.org/draft/2020-12/schema\",\n  \"title\": \"CRM Recommendations Schema\",\n  \"type\": \"object\",\n  \"properties\": {\n    \"recommendations\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"properties\": {\n          \"type\": {\n            \"type\": \"string\",\n            \"enum\": [\"Software\", \"Action\", \"Consideration\", \"Research\", \"Focus\"],\n            \"description\": \"The category or nature of the recommendation\"\n          },\n          \"name\": {\n            \"type\": \"string\",\n            \"description\": \"The name\"\n          },\n          \"description\": {\n            \"type\": \"string\",\n            \"description\": \"Explanation or reason behind the recommendation\"\n          },\n          \"reason\": {\n            \"type\": \"string\",\n            \"description\": \"A detailed reason for recommendation (mainly used for Software type)\"\n          }\n        }\n      }\n    }\n  },\n  \"required\": [\"recommendations\"]\n}\n"
      },
      "typeVersion": 1.2
    },
    {
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      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
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      ],
      "parameters": {
        "schemaType": "manual",
        "inputSchema": "{\n  \"$schema\": \"https://json-schema.org/schema\",\n  \"title\": \"Trends Schema\",\n  \"type\": \"object\",\n  \"properties\": {\n    \"trends\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"object\",\n        \"properties\": {\n          \"trend\": {\n            \"type\": \"string\",\n            \"description\": \"The name or label of the CRM trend\"\n          },\n          \"description\": {\n            \"type\": \"string\",\n            \"description\": \"A short explanation of the trend\"\n          }\n        },\n        \"required\": [\"trend\", \"description\"],\n        \"additionalProperties\": false\n      }\n    }\n  },\n  \"required\": [\"trends\"],\n  \"additionalProperties\": false\n}\n"
      },
      "typeVersion": 1.2
    },
    {
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      "type": "n8n-nodes-base.code",
      "position": [
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      ],
      "parameters": {
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      },
      "typeVersion": 2
    },
    {
      "id": "cb71a4e9-55ff-4194-8e5c-be96f3971a4e",
      "name": "Code pour tendances",
      "type": "n8n-nodes-base.code",
      "position": [
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      ],
      "parameters": {
        "jsCode": "return $input.first().json.output.trends"
      },
      "typeVersion": 2
    },
    {
      "id": "bfdac6af-7fa9-42d9-8931-029291202a35",
      "name": "Convertir en fichier pour tendances",
      "type": "n8n-nodes-base.convertToFile",
      "position": [
        1840,
        -140
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "28d26067-622b-4115-ab25-79bf8802acdd",
      "name": "Convertir en fichier pour recommandations",
      "type": "n8n-nodes-base.convertToFile",
      "position": [
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      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "0fb2daca-d998-432e-901a-001f750822db",
      "name": "Écrire le fichier csv des tendances sur le disque",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        2080,
        -140
      ],
      "parameters": {
        "options": {},
        "fileName": "=d:\\Google_SERP_Trends_Response_{{ new Date().toISOString().replace(/[:.]/g, '-')}}.csv",
        "operation": "write"
      },
      "typeVersion": 1
    },
    {
      "id": "b0164de9-50a4-4aba-a680-a392eaba5765",
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      "type": "n8n-nodes-base.readWriteFile",
      "position": [
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      ],
      "parameters": {
        "options": {},
        "fileName": "=d:\\Google_SERP_Recommendations_Response_{{ new Date().toISOString().replace(/[:.]/g, '-')}}.csv",
        "operation": "write"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
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            "node": "f9b7f382-4a5a-4ddf-a62c-ee83af913a21",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "f1f9cfac-28d0-40a9-9287-b11689570b53": {
      "ai_languageModel": [
        [
          {
            "node": "7c89ac87-28b1-47f3-9f04-b2c05b1a483a",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "c008d472-0982-4970-a017-73784c6916e7": {
      "ai_outputParser": [
        [
          {
            "node": "7c89ac87-28b1-47f3-9f04-b2c05b1a483a",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    }
  }
}

Foire aux questions

Comment utiliser ce workflow ?

Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.

Dans quelles scénarios ce workflow est-il adapté ?

Avancé - Intelligence Artificielle, Marketing

Est-ce payant ?

Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.