KI-gesteuerte Produktrecherche und SEO-Inhaltsautomatisierung

• •Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
• •Google Sheets API-Anmeldedaten
• •Google Gemini API Key

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      "name": "Digital Marketing",
      "createdAt": "2025-05-29T11:14:57.099Z",
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              "name": "key",
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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"
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        "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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