Intelligenter Website-Funnel-Analysator

• •Google Sheets API-Anmeldedaten
• •OpenAI API Key

{
  "id": "4A25nv05Jho7qvlD",
  "meta": {
    "instanceId": "60046904b104f0f72b2629a9d88fe9f676be4035769f1f08dad1dd38a76b9480",
    "templateCredsSetupCompleted": true
  },
  "name": "12 Smart Website Funnel Analyzer",
  "tags": [],
  "nodes": [
    {
      "id": "033bde69-15e0-4518-83fb-2fa0c434e3c1",
      "name": "⏰ Trigger: Zeitgesteuert ausführen",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        -60,
        0
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "triggerAtHour": 9
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "f8f66218-4f7d-4fdf-9d43-1217923f8d69",
      "name": "🛠️ Ziel-URL & Kontext definieren",
      "type": "n8n-nodes-base.set",
      "position": [
        160,
        0
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "c0317fd3-7765-4e9d-9d10-a30184a89543",
              "name": "url",
              "type": "string",
              "value": "https://www.shopify.com"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "5aebc5c5-adf8-4bfe-9dcf-4d9dad58620d",
      "name": "🤖 KI-Agent: URL mit MCP scrapen",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        440,
        0
      ],
      "parameters": {
        "text": "=Visit the given URL and extract the following information:\n\n{{ $json.url }}\n\n1. **Page Metadata**\n   - Page Title\n   - Meta Description\n   - Canonical URL\n\n2. **Tracking/Analytics Scripts**\n   - List all script `src` that match known analytics vendors (e.g. `google-analytics.com`, `gtag`, `mixpanel`, `plausible.io`, `segment.io`, `hotjar.com`, etc.)\n\n3. **CTA Buttons and Links**\n   - Extract all visible `<a>` and `<button>` elements with:\n     - Inner text\n     - href or onclick\n     - Position in viewport (if possible)\n   - Filter for CTA indicators: buttons/links with text like \"Start Free Trial\", \"Sign Up\", \"Get Started\", \"Learn More\", \"Try Now\", etc.\n\n4. **Analytics Objects**\n   - Try to extract any JavaScript variables that might contain tracking data:\n     - `window.dataLayer`\n     - `window.analytics`\n     - Any `JSON.parse(...)` content embedded in `<script>` tags\n\n5. **Page Structure Overview**\n   - Count and summarize the number of:\n     - Headings (`h1`, `h2`, `h3`)\n     - Sections (`<section>` tags)\n     - Images and media elements\n\n6. **Funnel Insight Tags (Optional for Later Use)**\n   - Detect if this page likely fits a funnel stage:\n     - Awareness (homepage, product overview)\n     - Consideration (product detail, features)\n     - Conversion (CTA, checkout, pricing)\n\nEnsure that JavaScript is rendered fully and wait for the page to become idle before extracting data. Use a mobile user-agent and viewport to simulate mobile browsing behavior accurately.\n\nReturn all data in structured JSON.\n",
        "options": {},
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 2
    },
    {
      "id": "19c9f2ea-1faf-42c5-aa6b-cc03f200d706",
      "name": "🧠 LLM-Modell (Instruction Brain)",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        400,
        260
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8sEyPDkC5p4w4Jha",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "4458687e-613a-4a41-823d-8f7ec7e374e8",
      "name": "📡 Bright Data MCP Client",
      "type": "n8n-nodes-mcp.mcpClientTool",
      "position": [
        580,
        260
      ],
      "parameters": {
        "toolName": "scrape_as_markdown",
        "operation": "executeTool",
        "toolParameters": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('Tool_Parameters', ``, 'json') }}"
      },
      "credentials": {
        "mcpClientApi": {
          "id": "eqq94k789oJCd6jU",
          "name": "MCP Client (STDIO) account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "92c907a5-9ecd-4299-869e-dbcf8037fb3e",
      "name": "📊 Ergebnisse in Google Sheets speichern",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        980,
        0
      ],
      "parameters": {
        "columns": {
          "value": {
            "images": "={{ $json.output.page_structure_overview.images }}",
            "headings": "={{ $json.output.page_structure_overview.headings }}",
            "sections": "={{ $json.output.page_structure_overview.sections }}",
            "analytics": "={{ $json.output.analytics_objects.analytics }}",
            "data layer": "={{ $json.output.analytics_objects.dataLayer }}",
            "page title": "={{ $json.output.page_metadata.page_title }}",
            "funnel stage": "={{ $json.output.funnel_stage }}",
            "canonical url": "={{ $json.output.page_metadata.canonical_url }}",
            "cta button links": "={{ $json.output.cta_buttons_links }}",
            "meta description": "={{ $json.output.page_metadata.meta_description }}",
            "json parsed content": "={{ $json.output.analytics_objects.json_parsed_content }}"
          },
          "schema": [
            {
              "id": "page title",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "page title",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "meta description",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "meta description",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "canonical url",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "canonical url",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "cta button links",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "cta button links",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "data layer",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "data layer",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "analytics",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "analytics",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "json parsed content",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "json parsed content",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "headings",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "headings",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "sections",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "sections",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "images",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "images",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "funnel stage",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "funnel stage",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "append",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1JbTZgfXxSddks7Sx2YVW_uf-CDC6vBQ9s0nidzzxEKs/edit#gid=0",
          "cachedResultName": "Sheet1"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1JbTZgfXxSddks7Sx2YVW_uf-CDC6vBQ9s0nidzzxEKs",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1JbTZgfXxSddks7Sx2YVW_uf-CDC6vBQ9s0nidzzxEKs/edit?usp=drivesdk",
          "cachedResultName": "Website analytics"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "r2mDaisH6e9VkwHl",
          "name": "Google Sheets account"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "72c17e6e-c2f0-447e-b15c-3d974c75af85",
      "name": "Notizzettel",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -80,
        -900
      ],
      "parameters": {
        "color": 6,
        "width": 380,
        "height": 1080,
        "content": "## 🔶 **SECTION 1: Start & Define Target**\n\n### 🔹 Nodes:\n\n* `⏰ Trigger: Run on Schedule`\n* `🛠️ Define Target URL & Context`\n\n---\n\n### 🧩 What This Section Does:\n\n1. **⏰ Trigger: Run on Schedule**\n\n   * This node automatically **starts the workflow at scheduled intervals** (e.g., hourly, daily).\n   * You don’t need to press a button every time. Just set it once, and it runs like a robot clock.\n\n2. **🛠️ Define Target URL & Context**\n\n   * Here, you **input the Shopify URL** you want to scrape.\n   * You can also define **tags** like `page_type: homepage`, `funnel_stage: awareness`, etc., to help analyze which stage of the sales funnel each page belongs to.\n\n---\n\n### 💡 Beginner Benefit:\n\n> This section allows you to automate the scraping of a specific page (like the Shopify homepage) and clearly tag what you're trying to analyze — all **without coding**!\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "307d8a0d-260d-433d-ae61-097992f35efe",
      "name": "Notizzettel1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        400,
        -1340
      ],
      "parameters": {
        "color": 5,
        "width": 340,
        "height": 1520,
        "content": "## 🤖 **SECTION 2: AI-Powered Scraping via Bright Data MCP**\n\n### 🔹 Nodes:\n\n* `🤖 AI Agent: Scrape Shopify with MCP`\n\n  * 🧠 `LLM Model (Instruction Brain)`\n  * 📡 `Bright Data MCP Client`\n  * 🧾 `Output Parser: Clean Extracted Data`\n\n---\n\n### 🧩 What This Section Does:\n\n1. **🤖 AI Agent: Scrape Shopify with MCP**\n\n   * This is the **smart engine** that handles all scraping tasks.\n\n2. **🧠 LLM Model (Instruction Brain)**\n\n   * It tells the AI agent **what to look for**, like:\n\n     * Page title, CTAs, Google Analytics scripts, section counts, etc.\n   * Think of it as the “brain” of the operation.\n\n3. **📡 Bright Data MCP Client**\n\n   * This node actually **loads the website like a real phone user** (mobile browser), thanks to **Bright Data's Mobile Carrier Proxy**.\n   * It **bypasses blocks**, loads dynamic content, and mimics real behavior.\n\n4. **🧾 Output Parser: Clean Extracted Data**\n\n   * After scraping, this node **cleans and formats the results** into a neat JSON structure.\n   * It ensures that things like headings, links, CTA buttons, and analytics scripts are easy to read and store.\n\n---\n\n### 💡 Beginner Benefit:\n\n> You don't have to know how scraping or proxies work. This AI Agent + Bright Data combo does the heavy lifting: it visits the page, reads everything like a human user, and extracts key insights in a structured format. 💪\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "b4af3b43-0daf-40be-96ab-c8f706414e14",
      "name": "Notizzettel2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        880,
        -600
      ],
      "parameters": {
        "color": 3,
        "width": 300,
        "height": 780,
        "content": "## ✅ **SECTION 3: Save Insights for Reporting**\n\n### 🔹 Node:\n\n* `📊 Save Results to Google Sheets`\n\n---\n\n### 🧩 What This Section Does:\n\n* This node **automatically logs all the structured results** (like title, CTAs, funnel stage, analytics scripts, etc.) into a connected Google Sheet.\n* Over time, this sheet becomes a **powerful conversion funnel tracker**, helping you identify:\n\n  * Drop-off points\n  * CTA effectiveness\n  * Page structure evolution\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "a38a2cb0-f8e3-4892-abae-0b1f0695b328",
      "name": "Notizzettel9",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -2080,
        -900
      ],
      "parameters": {
        "color": 4,
        "width": 1300,
        "height": 320,
        "content": "=======================================\n            WORKFLOW ASSISTANCE\n=======================================\nFor any questions or support, please contact:\n    Yaron@nofluff.online\n\nExplore more tips and tutorials here:\n   - YouTube: https://www.youtube.com/@YaronBeen/videos\n   - LinkedIn: https://www.linkedin.com/in/yaronbeen/\n=======================================\n"
      },
      "typeVersion": 1
    },
    {
      "id": "86a27ad9-d138-489c-a7de-176bd117536e",
      "name": "Notizzettel4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -2080,
        -560
      ],
      "parameters": {
        "color": 4,
        "width": 1289,
        "height": 2778,
        "content": "# 📊 **Workflow Title:**\n\n**Smart Website Funnel Analyzer: Scrape Shopify with Bright Data and Log Insights to Google Sheets**\n\n---\n\n## 🔶 **SECTION 1: Start & Define Target**\n\n### 🔹 Nodes:\n\n* `⏰ Trigger: Run on Schedule`\n* `🛠️ Define Target URL & Context`\n\n---\n\n### 🧩 What This Section Does:\n\n1. **⏰ Trigger: Run on Schedule**\n\n   * This node automatically **starts the workflow at scheduled intervals** (e.g., hourly, daily).\n   * You don’t need to press a button every time. Just set it once, and it runs like a robot clock.\n\n2. **🛠️ Define Target URL & Context**\n\n   * Here, you **input the Shopify URL** you want to scrape.\n   * You can also define **tags** like `page_type: homepage`, `funnel_stage: awareness`, etc., to help analyze which stage of the sales funnel each page belongs to.\n\n---\n\n### 💡 Beginner Benefit:\n\n> This section allows you to automate the scraping of a specific page (like the Shopify homepage) and clearly tag what you're trying to analyze — all **without coding**!\n\n---\n\n## 🤖 **SECTION 2: AI-Powered Scraping via Bright Data MCP**\n\n### 🔹 Nodes:\n\n* `🤖 AI Agent: Scrape Shopify with MCP`\n\n  * 🧠 `LLM Model (Instruction Brain)`\n  * 📡 `Bright Data MCP Client`\n  * 🧾 `Output Parser: Clean Extracted Data`\n\n---\n\n### 🧩 What This Section Does:\n\n1. **🤖 AI Agent: Scrape Shopify with MCP**\n\n   * This is the **smart engine** that handles all scraping tasks.\n\n2. **🧠 LLM Model (Instruction Brain)**\n\n   * It tells the AI agent **what to look for**, like:\n\n     * Page title, CTAs, Google Analytics scripts, section counts, etc.\n   * Think of it as the “brain” of the operation.\n\n3. **📡 Bright Data MCP Client**\n\n   * This node actually **loads the website like a real phone user** (mobile browser), thanks to **Bright Data's Mobile Carrier Proxy**.\n   * It **bypasses blocks**, loads dynamic content, and mimics real behavior.\n\n4. **🧾 Output Parser: Clean Extracted Data**\n\n   * After scraping, this node **cleans and formats the results** into a neat JSON structure.\n   * It ensures that things like headings, links, CTA buttons, and analytics scripts are easy to read and store.\n\n---\n\n### 💡 Beginner Benefit:\n\n> You don't have to know how scraping or proxies work. This AI Agent + Bright Data combo does the heavy lifting: it visits the page, reads everything like a human user, and extracts key insights in a structured format. 💪\n\n---\n\n## ✅ **SECTION 3: Save Insights for Reporting**\n\n### 🔹 Node:\n\n* `📊 Save Results to Google Sheets`\n\n---\n\n### 🧩 What This Section Does:\n\n* This node **automatically logs all the structured results** (like title, CTAs, funnel stage, analytics scripts, etc.) into a connected Google Sheet.\n* Over time, this sheet becomes a **powerful conversion funnel tracker**, helping you identify:\n\n  * Drop-off points\n  * CTA effectiveness\n  * Page structure evolution\n\n---\n\n### 💡 Beginner Benefit:\n\n> No coding. No manual copy-paste. The moment a page is analyzed, the key insights are saved into your Google Sheet — ready for reporting or optimization.\n\n---\n\n## 🎁 **Final Thoughts: Why This Workflow Is Powerful**\n\n* 📱 Uses mobile proxy scraping (MCP) for full access to dynamic web pages\n* 🤖 AI handles complex instructions and parsing\n* 📊 Google Sheets gives you instant reporting and tracking\n\n---\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "0218af59-c980-495f-9546-5992ce8f399b",
      "name": "Notizzettel5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1280,
        -600
      ],
      "parameters": {
        "color": 7,
        "width": 380,
        "height": 240,
        "content": "## I’ll receive a tiny commission if you join Bright Data through this link—thanks for fueling more free content!\n\n### https://get.brightdata.com/1tndi4600b25"
      },
      "typeVersion": 1
    },
    {
      "id": "7c9b3666-f32f-49ab-be38-36b3f31a8ca0",
      "name": "Auto-fixing Output Parser",
      "type": "@n8n/n8n-nodes-langchain.outputParserAutofixing",
      "position": [
        720,
        260
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "dae3494e-25b5-4394-a9ac-d4bfcf0621a2",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        680,
        520
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8sEyPDkC5p4w4Jha",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "1ab9f312-a515-4b02-9e7f-f49e0f4c6515",
      "name": "Structured Output Parser",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        860,
        520
      ],
      "parameters": {
        "jsonSchemaExample": "{\n  \"page_metadata\": {\n    \"page_title\": \"Shopify – Start your free trial today\",\n    \"meta_description\": \"Start selling online today with Shopify. The easiest way to start an online store.\",\n    \"canonical_url\": \"https://www.shopify.com\"\n  },\n  \"tracking_analytics_scripts\": [\n    \"https://www.googletagmanager.com/\",\n    \"https://www.google-analytics.com/\"\n  ],\n  \"cta_buttons_links\": [\n    {\n      \"inner_text\": \"Start for free\",\n      \"href\": \"https://accounts.shopify.com/store-create?locale=en&language=en&signup%5Fpage=https%3A%2F%2Fwww.shopify.com%2F&signup%5Ftypes%5B%5D=paid%5Ftrial%5Fexperience\",\n      \"position_in_viewport\": null\n    },\n    {\n      \"inner_text\": \"Start for free\",\n      \"href\": \"https://accounts.shopify.com/store-create?locale=en&language=en&signup%5Fpage=https%3A%2F%2Fwww.shopify.com%2F&signup%5Ftypes%5B%5D=paid%5Ftrial%5Fexperience\",\n      \"position_in_viewport\": null\n    },\n    {\n      \"inner_text\": \"Get started\",\n      \"href\": \"/online\",\n      \"position_in_viewport\": null\n    }\n  ],\n  \"analytics_objects\": {\n    \"dataLayer\": null,\n    \"analytics\": null,\n    \"json_parsed_content\": null\n  },\n  \"page_structure_overview\": {\n    \"headings\": {\n      \"h1\": 1,\n      \"h2\": 10,\n      \"h3\": 4\n    },\n    \"sections\": 15,\n    \"images\": 20\n  },\n  \"funnel_stage\": \"Awareness\"\n}\n"
      },
      "typeVersion": 1.2
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "fd1b5014-94c4-4a9f-848b-d42272c68d4a",
  "connections": {
    "dae3494e-25b5-4394-a9ac-d4bfcf0621a2": {
      "ai_languageModel": [
        [
          {
            "node": "7c9b3666-f32f-49ab-be38-36b3f31a8ca0",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "1ab9f312-a515-4b02-9e7f-f49e0f4c6515": {
      "ai_outputParser": [
        [
          {
            "node": "7c9b3666-f32f-49ab-be38-36b3f31a8ca0",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "7c9b3666-f32f-49ab-be38-36b3f31a8ca0": {
      "ai_outputParser": [
        [
          {
            "node": "5aebc5c5-adf8-4bfe-9dcf-4d9dad58620d",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "4458687e-613a-4a41-823d-8f7ec7e374e8": {
      "ai_tool": [
        [
          {
            "node": "5aebc5c5-adf8-4bfe-9dcf-4d9dad58620d",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "033bde69-15e0-4518-83fb-2fa0c434e3c1": {
      "main": [
        [
          {
            "node": "f8f66218-4f7d-4fdf-9d43-1217923f8d69",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "5aebc5c5-adf8-4bfe-9dcf-4d9dad58620d": {
      "main": [
        [
          {
            "node": "92c907a5-9ecd-4299-869e-dbcf8037fb3e",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "19c9f2ea-1faf-42c5-aa6b-cc03f200d706": {
      "ai_languageModel": [
        [
          {
            "node": "5aebc5c5-adf8-4bfe-9dcf-4d9dad58620d",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "f8f66218-4f7d-4fdf-9d43-1217923f8d69": {
      "main": [
        [
          {
            "node": "5aebc5c5-adf8-4bfe-9dcf-4d9dad58620d",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}