Stripe Customer Duplicate Detection & Management with Airtable & Slack…

The workflow JSON

Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →

{
  "id": "Rr0vbFBRhTCMYSuP",
  "meta": {
    "templateCredsSetupCompleted": true
  },
  "name": "Stripe Customer Duplicate Detection & Management",
  "tags": [],
  "nodes": [
    {
      "id": "38d831a3-05c2-4de0-94db-a1669fa98ec7",
      "name": "Workflow Description",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -928,
        352
      ],
      "parameters": {
        "width": 389,
        "height": 672,
        "content": "## \ud83c\udfaf Stripe Customer Duplicate Detection & Management\n\nThis workflow automatically scans your Stripe customers daily to identify potential duplicates and helps you maintain a clean customer database.\n\n### What this workflow does:\n\u2022 Fetches all customers from Stripe daily at 2 AM\n\u2022 Uses advanced fuzzy matching to detect duplicates by email and name\n\u2022 Logs findings to Airtable for review and approval\n\u2022 Sends detailed Slack notifications with actionable insights\n\n### Key Features:\n\u2022 Email-based duplicate detection (99% confidence)\n\u2022 Name similarity matching using Levenshtein distance\n\u2022 Automated logging with status tracking\n\u2022 Smart grouping and prioritization\n\u2022 Detailed Slack reports with statistics\n\n### Setup Requirements:\n1. Stripe API credentials\n2. Airtable base with duplicate tracking table\n3. Slack workspace integration\n"
      },
      "typeVersion": 1
    },
    {
      "id": "3a339de6-55b4-45ae-82e5-77455a181e74",
      "name": "Schedule Setup",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -512,
        48
      ],
      "parameters": {
        "width": 236,
        "height": 408,
        "content": "## \u23f0 Daily Trigger Setup\n\nScheduled to run every day at 2 AM to avoid peak business hours.\n\n**Cron Expression:** `0 2 * * *`\n- 0: minute (0)\n- 2: hour (2 AM)\n- *: any day of month\n- *: any month\n- *: any day of week\n\n\ud83d\udca1 **Tip:** You can modify the schedule based on your timezone and business needs."
      },
      "typeVersion": 1
    },
    {
      "id": "6994f890-98d7-47fc-9e77-2b25d636ae13",
      "name": "Daily Schedule Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        -432,
        480
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "cronExpression",
              "expression": "0 2 * * *"
            }
          ]
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "8cf9c8a7-38fc-47c9-a83c-68537ae947c3",
      "name": "Stripe Setup",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -336,
        656
      ],
      "parameters": {
        "width": 300,
        "height": 444,
        "content": "## \ud83d\udcb3 Stripe Customer Fetch\n\nRetrieves all customers from your Stripe account for duplicate analysis.\n\n**Setup Steps:**\n1. Create Stripe API credentials in n8n\n2. Use your Stripe Secret Key (starts with sk_)\n3. Ensure the key has read permissions for customers\n\n**Security Note:** Never hardcode API keys - always use n8n credentials manager.\n\n\u26a0\ufe0f **Important:** This fetches ALL customers. For large datasets (10k+ customers), consider adding pagination or filters."
      },
      "typeVersion": 1
    },
    {
      "id": "8e276971-d826-4307-bd90-547ec767a7bd",
      "name": "Fetch All Stripe Customers",
      "type": "n8n-nodes-base.stripe",
      "position": [
        -208,
        480
      ],
      "parameters": {
        "filters": {},
        "resource": "customer",
        "operation": "getAll",
        "returnAll": true
      },
      "credentials": {
        "stripeApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "5f0f09fd-3d34-4839-8a51-d865eed0bc88",
      "name": "Detection Algorithm",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -80,
        -64
      ],
      "parameters": {
        "width": 300,
        "height": 532,
        "content": "## \ud83d\udd0d Duplicate Detection Logic\n\nAdvanced algorithm that identifies potential duplicates using:\n\n**Email Matching (99% confidence):**\n- Exact email matches across customers\n- Case-insensitive comparison\n- Highest priority for merging\n\n**Name Similarity (80%+ threshold):**\n- Uses Levenshtein distance algorithm\n- Handles typos and variations\n- Configurable similarity threshold\n\n**Smart Grouping:**\n- Oldest customer becomes primary\n- All others suggested for merge\n- Prevents duplicate processing\n\nThe algorithm processes customers efficiently and avoids false positives."
      },
      "typeVersion": 1
    },
    {
      "id": "3f53c9e4-9a5a-4519-ae46-8e27b60f3890",
      "name": "Analyze Customer Duplicates",
      "type": "n8n-nodes-base.function",
      "position": [
        32,
        480
      ],
      "parameters": {
        "functionCode": "// Function to calculate Levenshtein distance\nfunction levenshteinDistance(str1, str2) {\n  const matrix = [];\n  \n  for (let i = 0; i <= str2.length; i++) {\n    matrix[i] = [i];\n  }\n  \n  for (let j = 0; j <= str1.length; j++) {\n    matrix[0][j] = j;\n  }\n  \n  for (let i = 1; i <= str2.length; i++) {\n    for (let j = 1; j <= str1.length; j++) {\n      if (str2.charAt(i - 1) === str1.charAt(j - 1)) {\n        matrix[i][j] = matrix[i - 1][j - 1];\n      } else {\n        matrix[i][j] = Math.min(\n          matrix[i - 1][j - 1] + 1,\n          matrix[i][j - 1] + 1,\n          matrix[i - 1][j] + 1\n        );\n      }\n    }\n  }\n  \n  return matrix[str2.length][str1.length];\n}\n\n// Function to calculate similarity percentage\nfunction calculateSimilarity(str1, str2) {\n  if (!str1 || !str2) return 0;\n  \n  const maxLength = Math.max(str1.length, str2.length);\n  if (maxLength === 0) return 100;\n  \n  const distance = levenshteinDistance(str1.toLowerCase(), str2.toLowerCase());\n  return Math.round(((maxLength - distance) / maxLength) * 100);\n}\n\n// Extract customers array from items - each item contains one customer\nconst customers = items.map(item => item.json);\nconst suggestions = [];\nconst processedCustomers = new Set();\n\nconsole.log(`Processing ${customers.length} customers for duplicates`);\n\n// Group customers by email and name for efficient duplicate detection\nconst emailGroups = new Map();\nconst nameGroups = new Map();\n\ncustomers.forEach(customer => {\n  // Group by email\n  if (customer.email) {\n    const emailKey = customer.email.toLowerCase();\n    if (!emailGroups.has(emailKey)) {\n      emailGroups.set(emailKey, []);\n    }\n    emailGroups.get(emailKey).push(customer);\n  }\n  \n  // Group by name (for name similarity matching)\n  if (customer.name) {\n    const nameKey = customer.name.toLowerCase();\n    if (!nameGroups.has(nameKey)) {\n      nameGroups.set(nameKey, []);\n    }\n    nameGroups.get(nameKey).push(customer);\n  }\n});\n\n// Process email-based duplicates\nemailGroups.forEach((group, email) => {\n  if (group.length > 1) {\n    // Sort by creation date to make the oldest one primary\n    group.sort((a, b) => a.created - b.created);\n    const primary = group[0];\n    \n    // Create suggestions for all others against the primary\n    for (let i = 1; i < group.length; i++) {\n      const secondary = group[i];\n      if (!processedCustomers.has(secondary.id)) {\n        let confidenceScore = 95;\n        let matchReason = 'Email match';\n        \n        // Higher confidence if names also match\n        if (primary.name && secondary.name && primary.name.toLowerCase() === secondary.name.toLowerCase()) {\n          confidenceScore = 99;\n          matchReason = 'Email + Name exact match';\n        }\n        \n        suggestions.push({\n          primary_customer_id: primary.id,\n          secondary_customer_id: secondary.id,\n          email: primary.email || secondary.email || '',\n          name_similarity_score: confidenceScore,\n          primary_name: primary.name || '',\n          secondary_name: secondary.name || '',\n          match_reason: matchReason,\n          status: 'Pending Review'\n        });\n        \n        processedCustomers.add(secondary.id);\n      }\n    }\n    processedCustomers.add(primary.id);\n  }\n});\n\n// Process name-based duplicates (only for customers not already processed by email)\nnameGroups.forEach((group, name) => {\n  if (group.length > 1) {\n    // Filter out customers already processed by email matching\n    const unprocessedGroup = group.filter(customer => !processedCustomers.has(customer.id));\n    \n    if (unprocessedGroup.length > 1) {\n      // Sort by creation date to make the oldest one primary\n      unprocessedGroup.sort((a, b) => a.created - b.created);\n      const primary = unprocessedGroup[0];\n      \n      // Create suggestions for all others against the primary\n      for (let i = 1; i < unprocessedGroup.length; i++) {\n        const secondary = unprocessedGroup[i];\n        const nameSimilarity = calculateSimilarity(primary.name, secondary.name);\n        \n        if (nameSimilarity >= 80) {\n          suggestions.push({\n            primary_customer_id: primary.id,\n            secondary_customer_id: secondary.id,\n            email: primary.email || secondary.email || '',\n            name_similarity_score: nameSimilarity,\n            primary_name: primary.name || '',\n            secondary_name: secondary.name || '',\n            match_reason: 'Name similarity',\n            status: 'Pending Review'\n          });\n        }\n      }\n    }\n  }\n});\n\nconsole.log(`Found ${suggestions.length} duplicate suggestions`);\n\n// Return suggestions as n8n items format\nreturn suggestions.map(suggestion => ({ json: suggestion }));"
      },
      "typeVersion": 1
    },
    {
      "id": "31ac8a3a-a2ac-4468-96d3-43eefb377823",
      "name": "Airtable Configuration",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        144,
        624
      ],
      "parameters": {
        "width": 320,
        "height": 524,
        "content": "## \ud83d\udcca Airtable Logging Setup\n\nLogs all duplicate suggestions to Airtable for review and approval workflow.\n\n**Required Table Fields:**\n- Primary Customer ID (Text)\n- Secondary Customer ID (Text)\n- Email (Email)\n- Name Similarity Score (Number)\n- Primary Name (Text)\n- Secondary Name (Text)\n- Match Reason (Single Select)\n- Status (Single Select: Pending Review, Approved, Rejected)\n\n**Setup Steps:**\n1. Create Airtable Personal Access Token\n2. Replace the hardcoded base and table IDs with your own\n3. Set up the table structure as described above\n\n"
      },
      "typeVersion": 1
    },
    {
      "id": "2a1648e3-4276-45b6-8dd1-37e9cd9f6b70",
      "name": "Log to Airtable Database",
      "type": "n8n-nodes-base.airtable",
      "position": [
        256,
        480
      ],
      "parameters": {
        "table": {
          "__rl": true,
          "mode": "id",
          "value": "{{ $env.AIRTABLE_TABLE_ID }}"
        },
        "options": {},
        "operation": "append",
        "application": {
          "__rl": true,
          "mode": "id",
          "value": "{{ $env.AIRTABLE_BASE_ID }}"
        },
        "authentication": "airtableTokenApi"
      },
      "credentials": {
        "airtableTokenApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "c8a3224a-1da5-4230-9edd-909afa20757a",
      "name": "Message Format",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        368,
        -48
      ],
      "parameters": {
        "width": 300,
        "height": 520,
        "content": "## \ud83d\udcdd Message Formatting\n\nCreates a detailed Slack message with:\n\n**Summary Statistics:**\n- Total duplicate suggestions found\n- Number of customer groups affected\n- Total customers involved\n\n**Match Type Breakdown:**\n- Email matches (highest confidence)\n- Name similarity matches\n- Combined email + name matches\n\n**Top Duplicate Groups:**\n- Shows the most problematic duplicates\n- Includes customer count per group\n- Limited to top 3 for readability\n\n**Action Items:**\n- Direct link to Airtable for review\n- Clear next steps for the team"
      },
      "typeVersion": 1
    },
    {
      "id": "dfbf1b63-22a0-4d4c-a4e9-07565b5cab82",
      "name": "Format Notification Message",
      "type": "n8n-nodes-base.function",
      "position": [
        464,
        480
      ],
      "parameters": {
        "functionCode": "const suggestions = items;\nconst count = suggestions.length;\nconst airtableLink = `https://airtable.com/${process.env.AIRTABLE_BASE_ID}/${process.env.AIRTABLE_TABLE_ID}`;\n\n// Initialize these variables outside the if/else blocks\nconst emailGroups = new Map();\nconst matchReasons = new Map();\n\nlet message = '';\n\nif (count === 0) {\n  message = '\u2705 No duplicate customers found in today\\'s scan.';\n} else {\n  // Analyze the suggestions for better insights\n  suggestions.forEach(item => {\n    const suggestion = item.json ? item.json : item.fields; // Handle both formats\n    \n    // Group by email\n    const email = suggestion.email;\n    if (email) {\n      if (!emailGroups.has(email)) {\n        emailGroups.set(email, new Set());\n      }\n      emailGroups.get(email).add(suggestion.primary_customer_id);\n      emailGroups.get(email).add(suggestion.secondary_customer_id);\n    }\n    \n    // Count match reasons\n    const reason = suggestion.match_reason || 'Unknown';\n    matchReasons.set(reason, (matchReasons.get(reason) || 0) + 1);\n  });\n  \n  // Create detailed message\n  const uniqueCustomerGroups = emailGroups.size;\n  const totalDuplicateCustomers = Array.from(emailGroups.values()).reduce((sum, customerSet) => sum + customerSet.size, 0);\n  \n  message = `\u26a0\ufe0f *Duplicate Customer Alert*\\n\\n`;\n  message += `\ud83d\udcca *Summary:*\\n`;\n  message += `\u2022 ${count} duplicate suggestion${count > 1 ? 's' : ''} found\\n`;\n  message += `\u2022 ${uniqueCustomerGroups} customer group${uniqueCustomerGroups > 1 ? 's' : ''} affected\\n`;\n  message += `\u2022 ${totalDuplicateCustomers} total customers involved\\n\\n`;\n  \n  // Add breakdown by match reason\n  if (matchReasons.size > 0) {\n    message += `\ud83d\udd0d *Match Types:*\\n`;\n    for (const [reason, reasonCount] of matchReasons) {\n      let emoji = '\ud83d\udce7';\n      if (reason && reason.includes && reason.includes('Name')) emoji = '\ud83d\udc64';\n      if (reason && reason.includes && reason.includes('Email + Name')) emoji = '\ud83d\udcaf';\n      \n      message += `${emoji} ${reason}: ${reasonCount}\\n`;\n    }\n    message += `\\n`;\n  }\n  \n  // Add top duplicate groups (limit to 3 for brevity)\n  const sortedGroups = Array.from(emailGroups.entries())\n    .sort((a, b) => b[1].size - a[1].size)\n    .slice(0, 3);\n  \n  if (sortedGroups.length > 0) {\n    message += `\ud83c\udfaf *Top Duplicate Groups:*\\n`;\n    sortedGroups.forEach(([email, customerIds], index) => {\n      message += `${index + 1}. ${email} (${customerIds.size} customers)\\n`;\n    });\n    message += `\\n`;\n  }\n  \n  message += `\ud83d\udc40 *Action Required:* Please review and approve merges in Airtable\\n`;\n  message += `\ud83d\udd17 *Review Link:* ${airtableLink}`;\n}\n\nreturn [{\n  json: {\n    message: message,\n    count: count,\n    unique_groups: emailGroups.size || 0,\n    total_customers_affected: Array.from(emailGroups.values()).reduce((sum, customerSet) => sum + customerSet.size, 0) || 0,\n    match_reasons: Object.fromEntries(matchReasons),\n    airtable_link: airtableLink\n  }\n}];"
      },
      "typeVersion": 1
    },
    {
      "id": "b3d6a5cd-e852-4694-a27e-3d5f53b4a81d",
      "name": "Slack Setup",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        640,
        640
      ],
      "parameters": {
        "width": 300,
        "height": 600,
        "content": "## \ud83d\udcac Slack Notification Setup\n\nSends detailed duplicate reports to your team Slack channel.\n\n**Setup Steps:**\n1. Create Slack App with Bot Token\n2. Add bot to your target channel\n3. Replace hardcoded channel ID with your channel\n4. Grant necessary permissions (chat:write)\n\n**Message Features:**\n- Markdown formatting for better readability\n- Emoji indicators for different match types\n- Direct links to Airtable for action\n- Summary statistics for quick overview\n\n**Security:** Use environment variables for sensitive channel IDs and tokens.\n\n\ud83d\udca1 **Tip:** Consider using different channels for different alert levels."
      },
      "typeVersion": 1
    },
    {
      "id": "228175d2-da58-4ccc-afda-b7f358f6a3d1",
      "name": "Send Slack Notification",
      "type": "n8n-nodes-base.slack",
      "position": [
        672,
        480
      ],
      "parameters": {
        "text": "={{ $json.message }}",
        "select": "channel",
        "channelId": {
          "__rl": true,
          "mode": "list",
          "value": "{{ $env.SLACK_CHANNEL_ID }}",
          "cachedResultName": "duplicate-alerts"
        },
        "otherOptions": {
          "mrkdwn": true
        }
      },
      "credentials": {
        "slackApi": {
          "name": "<your credential>"
        }
      },
      "typeVersion": 2.3
    }
  ],
  "active": false,
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "15516be5-62fa-4865-a572-48dd92f7294b",
  "connections": {
    "Daily Schedule Trigger": {
      "main": [
        [
          {
            "node": "Fetch All Stripe Customers",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Log to Airtable Database": {
      "main": [
        [
          {
            "node": "Format Notification Message",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Fetch All Stripe Customers": {
      "main": [
        [
          {
            "node": "Analyze Customer Duplicates",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Analyze Customer Duplicates": {
      "main": [
        [
          {
            "node": "Log to Airtable Database",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Format Notification Message": {
      "main": [
        [
          {
            "node": "Send Slack Notification",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Credentials you'll need

Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.

• airtableTokenApi
• slackApi
• stripeApi

About this workflow

Automatically scan your Stripe customers daily to detect duplicates and keep your customer database clean. This workflow uses advanced fuzzy matching for emails and names, logs results to Airtable for review, and notifies your team in Slack with actionable insights. 💳🧹💬 Runs…

Source: https://n8n.io/workflows/8947/ — original creator credit. Request a take-down →

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