{
  "workflow": {
    "id": 5195,
    "name": "AI-powered product research & SEO content automation",
    "views": 11715,
    "recentViews": 3,
    "totalViews": 11715,
    "createdAt": "2025-06-24T09:43:17.079Z",
    "description": "## AI-Powered Product Research & SEO Content Automation\n\nSkip the guesswork and manual effort — this n8n flow automates the entire process of researching your product's online competition and generating high-quality SEO content. Whether you're launching a new product or optimizing existing listings, this workflow leverages **real-time web data** and **AI-driven copywriting** to deliver:\n\n- 📈 Search-optimized metadata (Title, Description, Keywords)  \n- 🛍️ Engaging product descriptions tailored for marketing  \n- 📊 Auto-organized output ready for use in your content or e-commerce platform\n\nAll of this happens with just one product title input!\n\n---\n\n### 🧠 How It Works\n• User submits a product title via a form.  \n• The workflow uses Google Custom Search to gather real-time competitor content based on that title.  \n• Titles, snippets, and keywords are extracted from the search results.  \n• This information is sent to a language model (Google Gemini via LangChain) to generate:  \n   - SEO-optimized metadata (Title, Description, Keywords)  \n   - A compelling product description tailored for marketing  \n• The AI-generated content is then parsed and organized into two categories: SEO data and product content.  \n• The structured output is saved automatically into a connected Google Sheet for easy access or further automation.\n\n---\n\n### 🛠️ What Problems Does This Solve?\nManual competitor research and writing SEO content from scratch can be:\n- **Time-consuming**\n- **Inconsistent in quality**\n- **Not optimized for search engines**\n- **Hard to scale for multiple products**\n\nThis workflow **automates** the entire research + writing + structuring process.\n\n---\n\n### ✅ Key Benefits\n- **Instant Content Creation**: Generate polished SEO content in seconds.  \n- **Competitor-Aware**: Pulls in real-time data from the web for relevant, market-aligned content.  \n- **Scalable**: Easily repeat the process for multiple product titles with minimal effort.  \n- **Data Centralization**: Stores everything in Google Sheets—great for collaboration or syncing with other tools.  \n- **Customizable**: Easily extend or modify the workflow to include translations, publishing, or social media automation.\n\n---\n\n### ⚙️ Set-Up Steps\n• Connect Google Custom Search API with a valid API key and search engine ID (CX).  \n• Connect and configure Google Gemini or LangChain with access credentials.  \n• Provide access to a Google Sheet with columns for storing SEO and product data.  \n• Estimated setup time: ~15–25 minutes depending on API access and sheet setup.  \n\n---\n\n## 🚀 Let’s Get You Started with Automating Your LinkedIn Posts!\n\nCreate your **free n8n account** and set up the workflow in just a few minutes using the link below:\n\n👉 [Start Automating with n8n](https://n8n.partnerlinks.io/7fuarh1e6dz5)\n\nSave time, stay consistent, and grow your LinkedIn presence effortlessly!\n",
    "workflow": {
      "id": "icW2uoM7g7pFZhsR",
      "meta": {
        "instanceId": "60c025075753afcab9f803964b4caaca9402f435deb4efafbb8e3b93b54d8752",
        "templateCredsSetupCompleted": true
      },
      "name": "AI-Powered Product Research & SEO Content Automation",
      "tags": [
        {
          "id": "QXtLNWbsCSABOTNm",
          "name": "Digital Marketing",
          "createdAt": "2025-05-29T11:14:57.099Z",
          "updatedAt": "2025-05-29T11:14:57.099Z"
        }
      ],
      "nodes": [
        {
          "id": "f3824049-9114-447c-8c3f-e3a08af34d12",
          "name": "Google Search",
          "type": "n8n-nodes-base.httpRequest",
          "position": [
            400,
            -120
          ],
          "parameters": {
            "url": "https://www.googleapis.com/customsearch/v1",
            "options": {},
            "queryParametersUi": {
              "parameter": [
                {
                  "name": "key",
                  "value": "your key"
                },
                {
                  "name": "cx",
                  "value": "your cx"
                },
                {
                  "name": "q",
                  "value": "=intitle:\"{{ $json.title }}\" (pricing OR features OR buy OR software) -medium.com -quora.com -youtube.com -linkedin.com "
                }
              ]
            }
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          "name": "Extract Competitor Data",
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          "position": [
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            -100
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            "functionCode": "let allTitles = [];\nlet allDescriptions = [];\nlet allKeywords = [];\n\nfor (const item of $json.items) {\n  allTitles.push(item.title);\n  allDescriptions.push(item.snippet);\n\n  const keywords = item.title\n    .toLowerCase()\n    .replace(/[^a-zA-Z0-9 ]/g, '')\n    .split(' ')\n    .filter(w => w.length > 3);\n\n  allKeywords.push(...keywords);\n}\n\n// Create unique keywords\nconst uniqueKeywords = [...new Set(allKeywords)];\n\nreturn [\n  {\n    json: {\n      chatInput: `\nTitle List:\n${allTitles.join('\\n')}\n\nDescription List:\n${allDescriptions.join('\\n')}\n\nKeywords:\n${uniqueKeywords.join(', ')}\n      `.trim()\n    }\n  }\n];\n"
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          "typeVersion": 1
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        {
          "id": "0a2929a1-d6fc-4a37-b142-54b0e2135652",
          "name": "Basic LLM Chain",
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          "position": [
            920,
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          "parameters": {
            "messages": {
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                {
                  "message": "You are an expert SEO content writer and product copywriter.  generate the following in one output:  1. SEO Meta Data: - Title: (exact product title, must be the same as product title below) - Description: A concise, persuasive meta description optimized for Google SEO best practices. Make sure it is between 120-160 characters, includes main keywords naturally, and encourages clicks. - Keywords: A list of relevant, highly ranked keywords related to the product.  2. Product Content: - Product Title: (exact same title as SEO Meta Data Title) - Product Description: A detailed, engaging product description of minimum 150 words that highlights the product’s key features, benefits, and usage. Use natural language with relevant keywords but avoid keyword stuffing.  Format the output exactly like this:  --- SEO Meta Data: Title: ... Description: ... Keywords: ...  Product Content: Product Title: ... Product Description: ...  ---  Ensure that the SEO Meta Data Title and Product Title are exactly the same string. Follow SEO best practices for titles, descriptions, and keyword usage to maximize Google ranking potential."
                }
              ]
            }
          },
          "typeVersion": 1.5
        },
        {
          "id": "797456cf-d4a2-49b7-8134-d5ebbf062cc7",
          "name": "Google Gemini Chat Model",
          "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
          "position": [
            940,
            360
          ],
          "parameters": {
            "options": {},
            "modelName": "models/gemini-2.0-flash"
          },
          "credentials": {
            "googlePalmApi": {
              "id": "credential-id",
              "name": "googlePalmApi Credential"
            }
          },
          "typeVersion": 1
        },
        {
          "id": "44d6ebd9-ad12-4838-aee0-9b8a4a847a6b",
          "name": "Google Sheets",
          "type": "n8n-nodes-base.googleSheets",
          "position": [
            1660,
            -140
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          "parameters": {
            "columns": {
              "value": {},
              "schema": [
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                  "id": "type",
                  "type": "string",
                  "display": true,
                  "removed": false,
                  "required": false,
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                  "canBeUsedToMatch": true
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                  "type": "string",
                  "display": true,
                  "removed": false,
                  "required": false,
                  "displayName": "title",
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                  "canBeUsedToMatch": true
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                  "display": true,
                  "removed": false,
                  "required": false,
                  "displayName": "description",
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                  "canBeUsedToMatch": true
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                  "display": true,
                  "removed": false,
                  "required": false,
                  "displayName": "keywords",
                  "defaultMatch": false,
                  "canBeUsedToMatch": true
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                  "type": "string",
                  "display": true,
                  "removed": false,
                  "required": false,
                  "displayName": "product_title",
                  "defaultMatch": false,
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                  "required": false,
                  "displayName": "product_description",
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                  "canBeUsedToMatch": true
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              "matchingColumns": [
                "text"
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              "attemptToConvertTypes": false,
              "convertFieldsToString": false
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            "options": {},
            "operation": "appendOrUpdate",
            "sheetName": {
              "__rl": true,
              "mode": "url",
              "value": ""
            },
            "documentId": {
              "__rl": true,
              "mode": "url",
              "value": ""
            },
            "authentication": "serviceAccount"
          },
          "credentials": {
            "googleApi": {
              "id": "credential-id",
              "name": "googleApi Credential"
            }
          },
          "typeVersion": 4.5
        },
        {
          "id": "571bb379-f061-42ae-b633-3e80467a0a3d",
          "name": "On form submission",
          "type": "n8n-nodes-base.formTrigger",
          "position": [
            -180,
            -140
          ],
          "webhookId": "f7e2c20d-4cd1-45f1-b6f7-54eb48c2ad91",
          "parameters": {
            "options": {},
            "formTitle": "Product Research ",
            "formFields": {
              "values": [
                {
                  "fieldLabel": "title",
                  "placeholder": "Enter product title",
                  "requiredField": true
                }
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            }
          },
          "typeVersion": 2.2
        },
        {
          "id": "0a4b670a-50b3-4a60-ae51-e3bb958f573a",
          "name": "Edit Fields",
          "type": "n8n-nodes-base.set",
          "position": [
            120,
            -140
          ],
          "parameters": {
            "options": {},
            "assignments": {
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                  "id": "39f794ce-8c11-4f72-b8d9-4ad0894d1e05",
                  "name": "title",
                  "type": "string",
                  "value": "={{ $json.title }}"
                }
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        },
        {
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          "name": "Sticky Note",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -1160,
            -500
          ],
          "parameters": {
            "width": 640,
            "height": 1340,
            "content": "# 🚀 AI-Powered Product Research & SEO Content Automation\n\nAn **AI-powered automation** that performs product research, extracts competitor insights, and generates SEO-optimized product content using Google Search and a large language model (LLM) like Google Gemini or OpenAI. The output is cleanly structured and saved into Google Sheets—ready for publishing.\n### Workflow Steps:\n1. **On form submission**  \n   *The user provides the product title via a form.*\n\n2. **Edit Fields**  \n   *The product title is prepared for the Google search query.*\n\n3. **Google Search**  \n   *A search is made on Google for competitor products and relevant information.*\n\n4. **Extract Competitor Data**  \n   *Competitor data, such as titles, descriptions, and keywords, is extracted from the search results.*\n\n5. **Basic LLM Chain**  \n   *SEO metadata and product content are generated using LangChain’s language model.*\n\n6. **Google Gemini Chat Model**  \n   *Google Gemini (PaLM) refines the generated content for quality and engagement.*\n\n7. **Code**  \n   *The content is split into SEO Meta Data and Product Content sections.*\n\n8. **Google Sheets**  \n   *All the generated content is stored in Google Sheets for easy access.*\n\n---\n\n## How This Flow Resolves Challenges:\n\n- **Automates Time-Consuming Tasks:**  \n  This workflow eliminates manual research and content writing by automating the gathering of competitor data and SEO content generation.\n  \n- **Improves SEO Outcomes:**  \n  By leveraging AI models like LangChain and Google Gemini, the workflow ensures that SEO metadata and product content are optimized for search engines.\n\n- **Efficient Organization:**  \n  The workflow splits content into clear sections and stores everything in Google Sheets, making it easy to access and manage data.\n\n- **Reduces Human Error:**  \n  Automation reduces the chances of missing important steps in content generation, ensuring consistency and accuracy.\n\n- **Centralized Data Management:**  \n  Storing everything in Google Sheets makes tracking, updating, and managing generated content straightforward and efficient.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "7f656ef7-50ce-40bd-a38b-74f3b4556311",
          "name": "Sticky Note1",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            -240,
            -300
          ],
          "parameters": {
            "height": 340,
            "content": "### 1. **On form submission**\n- *Trigger*: Collects the product title entered by the user via the form. This is the starting point of the workflow, where the process is initiated.\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "e6567de3-ed0d-4bcd-9f10-1e8abc374539",
          "name": "Sticky Note2",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            60,
            -300
          ],
          "parameters": {
            "height": 340,
            "content": "### 2. **Edit Fields**\n- *Action*: Formats the product title to fit the required query parameters for the Google search. This ensures the title is ready for the next step.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "2d75a14d-8d4b-4ea0-aad9-a3626e0caa1c",
          "name": "Sticky Note3",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            340,
            -300
          ],
          "parameters": {
            "height": 340,
            "content": "### 3. **Google Search**\n- *Action*: Executes a Google Custom Search API query to retrieve competitor data based on the product title. This helps in gathering insights from similar products or competitors.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "e3f73de9-6b55-45ee-aa31-b9ee4268d6fe",
          "name": "Code Formatting",
          "type": "n8n-nodes-base.code",
          "position": [
            1340,
            -100
          ],
          "parameters": {
            "jsCode": "const inputText = $json.text; // Your combined text input\n\nfunction getFieldValue(text, field) {\n  const regex = new RegExp(field + ':\\\\s*([\\\\s\\\\S]*?)(?=\\\\n\\\\S|$)', 'i');\n  const match = text.match(regex);\n  return match ? match[1].trim() : '';\n}\n\nfunction splitSections(text) {\n  // Extract sections by titles\n  const seoMetaMatch = text.match(/SEO Meta Data:\\n([\\s\\S]*?)\\n\\nProduct Content:/i);\n  const productContentMatch = text.match(/Product Content:\\n([\\s\\S]*)/i);\n\n  const seoMeta = seoMetaMatch ? seoMetaMatch[1].trim() : '';\n  const productContent = productContentMatch ? productContentMatch[1].trim() : '';\n\n  return [\n    {\n      json: {\n        type: 'seo_meta_data',\n        title: getFieldValue(seoMeta, 'Title'),\n        description: getFieldValue(seoMeta, 'Description'),\n        keywords: getFieldValue(seoMeta, 'Keywords'),\n        product_title: '',          // empty for SEO row\n        product_description: ''     // empty for SEO row\n      }\n    },\n    {\n      json: {\n        type: 'product_content',\n        title: '',                  // empty for Product row\n        description: '',\n        keywords: '',\n        product_title: getFieldValue(productContent, 'Product Title'),\n        product_description: getFieldValue(productContent, 'Product Description')\n      }\n    }\n  ];\n}\n\nreturn splitSections($input.first().json.text);\n"
          },
          "typeVersion": 2
        },
        {
          "id": "4811155c-a560-430c-b284-0730fc10b0c7",
          "name": "Sticky Note4",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            620,
            -300
          ],
          "parameters": {
            "height": 340,
            "content": "### 4. **Extract Competitor Data**\n- *Action*: Extracts key information (titles, descriptions, and keywords) from the search results. This data provides valuable insights into competitor strategies and product offerings.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "1f0f8a48-2d72-4695-85c0-9e4d260da954",
          "name": "Sticky Note5",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            900,
            -300
          ],
          "parameters": {
            "width": 320,
            "height": 340,
            "content": "### 5. **Basic LLM Chain**\n- *Action*: Uses LangChain’s language model to generate SEO metadata (title, description, keywords) and product content (description, title). The content is optimized for search engines.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "74c7341e-281e-4ec2-a24e-f4ea9d0df3a6",
          "name": "Sticky Note6",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            900,
            160
          ],
          "parameters": {
            "width": 260,
            "height": 320,
            "content": "### 6. **Google Gemini Chat Model**\n- *Action*: Refines and improves the content generated in the previous step by using Google Gemini (PaLM) to enhance its quality and engagement.\n"
          },
          "typeVersion": 1
        },
        {
          "id": "1dd0fee3-9c48-4748-b707-00abf0cd6475",
          "name": "Sticky Note7",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1280,
            -300
          ],
          "parameters": {
            "height": 340,
            "content": "### 7. **Code Formating **\n- *Action*: Splits the generated content into two sections: SEO Meta Data and Product Content, organizing the output into clearly defined sections for easy use.\n\n"
          },
          "typeVersion": 1
        },
        {
          "id": "7360db3c-7c8a-4a00-9bd3-a462df36df05",
          "name": "Sticky Note8",
          "type": "n8n-nodes-base.stickyNote",
          "position": [
            1600,
            -300
          ],
          "parameters": {
            "height": 340,
            "content": "### 8. **Google Sheets**\n- *Action*: Appends the final SEO metadata and product content into a Google Sheets document, making it easy to store, access, and track the generated information."
          },
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        "Code Formatting": {
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                "node": "Google Sheets",
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        "Google Gemini Chat Model": {
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                "node": "Basic LLM Chain",
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      "name": "Evoort Solutions",
      "username": "evoortsolutions",
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      "verified": true,
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              "Javascript",
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            "details": "The Function node allows you to execute JavaScript in your workflow. Unlike the Function Item node, this node does not operate on incoming node data per-item. Instead, you must iterate over multiple items of incoming data yourself. This can be useful if you're performing data transformation where you want to manipulate the number of items being outputted by the node (i.e. 1 item is inputted in with nested object, 10 items are outputted without any nested objects)",
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                  "icon": "🏭",
                  "label": "Learn to Automate Your Factory's Incident Reporting: A Step by Step Guide"
                },
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                  "label": "2021: The Year to Automate the New You with n8n"
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                "Root Nodes"
              ],
              "Language Models": [
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            }
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            "id": 26,
            "name": "Langchain"
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        ]
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    "categories": [
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        "id": 31,
        "name": "Content Creation"
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    "image": []
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}