Matomo Analytics Report

工作流概述

这是一个包含10个节点的复杂工作流,主要用于自动化处理各种任务。

工作流源代码

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{
  "id": "PRQhetYFkuhxntVH",
  "meta": {
    "instanceId": "558d88703fb65b2d0e44613bc35916258b0f0bf983c5d4730c00c424b77ca36a",
    "templateCredsSetupCompleted": true
  },
  "name": "Matomo Analytics Report",
  "tags": [],
  "nodes": [
    {
      "id": "fd35d612-09a6-4dd3-836b-53d03b75f344",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        120,
        360
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "c8169606-3abd-4dd3-bd35-fdc0296fc0e1",
      "name": "Schedule Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        120,
        160
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "weeks"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "760a87e3-ed8f-4b1e-a46b-4ceb635020d4",
      "name": "Get data from Matomo",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        380,
        260
      ],
      "parameters": {
        "url": "https://shrewd-lyrebird.pikapod.net/index.php",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "contentType": "multipart-form-data",
        "bodyParameters": {
          "parameters": [
            {
              "name": "module",
              "value": "API"
            },
            {
              "name": "method",
              "value": "Live.getLastVisitsDetails"
            },
            {
              "name": "idSite",
              "value": "3"
            },
            {
              "name": "period",
              "value": "range"
            },
            {
              "name": "date",
              "value": "last30"
            },
            {
              "name": "format",
              "value": "JSON"
            },
            {
              "name": "segment",
              "value": "visitCount>3"
            },
            {
              "name": "filter_limit",
              "value": "100"
            },
            {
              "name": "showColumns",
              "value": "actionDetails,visitIp,visitorId,visitCount"
            },
            {
              "name": "token_auth",
              "value": "{insert your auth token}"
            }
          ]
        }
      },
      "typeVersion": 4.1
    },
    {
      "id": "f9e9a099-3131-4320-8a86-b9add4e43096",
      "name": "Parse data from Matomo",
      "type": "n8n-nodes-base.code",
      "position": [
        580,
        260
      ],
      "parameters": {
        "jsCode": "// Get input data
const items = $input.all();

// Format the visitor data into a clear prompt
const visitorData = items.map(item => {
  const visit = item.json;
  
  const visitorActions = visit.actionDetails.map(action => 
    `  - Page ${action.pageviewPosition}: ${action.pageTitle}\n    URL: ${action.url}\n    Time Spent: ${action.timeSpentPretty}`
  ).join('\n');

  return `- Visitor (ID: ${visit.visitorId}):\n  Visit Count: ${visit.visitCount}\n${visitorActions}`;
}).join('\n\n');

// Create the prompt
const prompt = `Please analyze this visitor data:\n\n${visitorData}\n\nPlease provide insights on:\n1. Common visitor paths\n2. Popular pages\n3. User engagement patterns\n4. Recommendations for improvement`;

// Return formatted for LLaMA
return [{
  json: {
    messages: [
      {
        role: \"user\",
        content: prompt
      }
    ]
  }
}];"
      },
      "typeVersion": 2
    },
    {
      "id": "387832ee-8397-43f8-bf62-846e4a7a20d0",
      "name": "Send data to A.I. for analysis",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        760,
        260
      ],
      "parameters": {
        "url": "https://openrouter.ai/api/v1/chat/completions",
        "method": "POST",
        "options": {},
        "jsonBody": "={
  \"model\": \"meta-llama/llama-3.1-70b-instruct:free\",
  \"messages\": [
    {
      \"role\": \"user\",
      \"content\": \"You are an SEO expert. This is data of visitors who have visited my site more then 3 times and the pages they have visited. Can you give me insights into this data:{{ encodeURIComponent($json.messages[0].content)}}\" 
    }
  ]
}",
        "sendBody": true,
        "specifyBody": "json",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "WY7UkF14ksPKq3S8",
          "name": "Header Auth account 2"
        }
      },
      "typeVersion": 4.2,
      "alwaysOutputData": false
    },
    {
      "id": "7ee29949-550e-4f3a-8420-49ca2608bbeb",
      "name": "Store results in Baserow",
      "type": "n8n-nodes-base.baserow",
      "position": [
        1060,
        260
      ],
      "parameters": {
        "tableId": 643,
        "fieldsUi": {
          "fieldValues": [
            {
              "fieldId": 6261,
              "fieldValue": "={{ DateTime.now().toFormat('yyyy-MM-dd') }}"
            },
            {
              "fieldId": 6262,
              "fieldValue": "={{ $json.choices[0].message.content }}"
            },
            {
              "fieldId": 6263,
              "fieldValue": "Your blog name"
            }
          ]
        },
        "operation": "create",
        "databaseId": 121
      },
      "credentials": {
        "baserowApi": {
          "id": "8w0zXhycIfCAgja3",
          "name": "Baserow account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "684ca1c9-97c3-4464-8ce6-aa6019db0c04",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        80,
        -360
      ],
      "parameters": {
        "color": 5,
        "width": 615,
        "height": 289,
        "content": "## Send Matomo analytics to A.I. and save results to baserow

This workflow will check for visitors who have visited more than 3 times. It will take this week's data and compare it to last week's data and give SEO suggestions.

[Watch youtube tutorial here](https://www.youtube.com/watch?v=hGzdhXyU-o8)

[Get my SEO A.I. agent system here](https://2828633406999.gumroad.com/l/rumjahn)

[💡 You can read more about this workflow here](https://rumjahn.com/how-to-create-an-a-i-agent-to-analyze-matomo-analytics-using-n8n-for-free/)
"
      },
      "typeVersion": 1
    },
    {
      "id": "29723224-416e-46b4-a498-90888eb9a41b",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        320,
        -20
      ],
      "parameters": {
        "width": 224.51612903225822,
        "height": 461.4193548387107,
        "content": "## Get Matomo Data
 
1. Enter your Matomo API key at the bottom
2. Navigate to Administration > Personal > Security > Auth tokens within your Matomo dashboard. Click on Create new token and provide a purpose for reference."
      },
      "typeVersion": 1
    },
    {
      "id": "c694c855-c37a-4717-befd-d7a216f99e2d",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        700,
        -20
      ],
      "parameters": {
        "color": 3,
        "width": 225.99936321742769,
        "height": 508.95792207792226,
        "content": "## Send data to A.I.

Fill in your Openrouter A.I. credentials. Use Header Auth.
- Username: Authorization
- Password: Bearer {insert your API key}

Remember to add a space after bearer. Also, feel free to modify the prompt to A.1."
      },
      "typeVersion": 1
    },
    {
      "id": "fdd12783-0456-4fc7-8030-555f058f2fd2",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        960,
        -20
      ],
      "parameters": {
        "color": 6,
        "width": 331.32883116883124,
        "height": 474.88,
        "content": "## Send data to Baserow

Create a table first with the following columns:
- Date
- Note
- Blog

Enter the name of your website under \"Blog\" field."
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "21a1d486-5bb8-40b9-9032-6ab22d8baebc",
  "connections": {
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "Get data from Matomo",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get data from Matomo": {
      "main": [
        [
          {
            "node": "Parse data from Matomo",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Parse data from Matomo": {
      "main": [
        [
          {
            "node": "Send data to A.I. for analysis",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Send data to A.I. for analysis": {
      "main": [
        [
          {
            "node": "Store results in Baserow",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking ‘Test workflow’": {
      "main": [
        [
          {
            "node": "Get data from Matomo",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

功能特点

  • 自动检测新邮件
  • AI智能内容分析
  • 自定义分类规则
  • 批量处理能力
  • 详细的处理日志

技术分析

节点类型及作用

  • Manualtrigger
  • Scheduletrigger
  • Httprequest
  • Code
  • Baserow

复杂度评估

配置难度:
★★★★☆
维护难度:
★★☆☆☆
扩展性:
★★★★☆

实施指南

前置条件

  • 有效的Gmail账户
  • n8n平台访问权限
  • Google API凭证
  • AI分类服务订阅

配置步骤

  1. 在n8n中导入工作流JSON文件
  2. 配置Gmail节点的认证信息
  3. 设置AI分类器的API密钥
  4. 自定义分类规则和标签映射
  5. 测试工作流执行
  6. 配置定时触发器(可选)

关键参数

参数名称 默认值 说明
maxEmails 50 单次处理的最大邮件数量
confidenceThreshold 0.8 分类置信度阈值
autoLabel true 是否自动添加标签

最佳实践

优化建议

  • 定期更新AI分类模型以提高准确性
  • 根据邮件量调整处理批次大小
  • 设置合理的分类置信度阈值
  • 定期清理过期的分类规则

安全注意事项

  • 妥善保管API密钥和认证信息
  • 限制工作流的访问权限
  • 定期审查处理日志
  • 启用双因素认证保护Gmail账户

性能优化

  • 使用增量处理减少重复工作
  • 缓存频繁访问的数据
  • 并行处理多个邮件分类任务
  • 监控系统资源使用情况

故障排除

常见问题

邮件未被正确分类

检查AI分类器的置信度阈值设置,适当降低阈值或更新训练数据。

Gmail认证失败

确认Google API凭证有效且具有正确的权限范围,重新进行OAuth授权。

调试技巧

  • 启用详细日志记录查看每个步骤的执行情况
  • 使用测试邮件验证分类逻辑
  • 检查网络连接和API服务状态
  • 逐步执行工作流定位问题节点

错误处理

工作流包含以下错误处理机制:

  • 网络超时自动重试(最多3次)
  • API错误记录和告警
  • 处理失败邮件的隔离机制
  • 异常情况下的回滚操作