Comentarios de conversaciones de Intercom

Avanzado

Este es unTicket Management, AI Summarizationflujo de automatización del dominio deautomatización que contiene 22 nodos.Utiliza principalmente nodos como If, Code, Merge, Webhook, SplitOut. Automatización de la evaluación de la calidad de soporte con Intercom, GPT y Google Sheets

Requisitos previos
  • Punto final de HTTP Webhook (n8n generará automáticamente)
  • Pueden requerirse credenciales de autenticación para la API de destino
  • Credenciales de API de Google Sheets
  • Clave de API de OpenAI
Vista previa del flujo de trabajo
Visualización de las conexiones entre nodos, con soporte para zoom y panorámica
Exportar flujo de trabajo
Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo
{
  "id": "U8L7ojJGYnPXUZZm",
  "meta": {
    "instanceId": "5f48daf3a0baf541941ac99dac87a58469ec38ada0698ec3f47e71ef7e50b0ff",
    "templateCredsSetupCompleted": true
  },
  "name": "Intercom Conversation Reviews",
  "tags": [],
  "nodes": [
    {
      "id": "3a663159-b082-440d-b15f-81a4f246e8c2",
      "name": "Webhook",
      "type": "n8n-nodes-base.webhook",
      "position": [
        720,
        420
      ],
      "webhookId": "a716761a-b062-4f93-9734-04fdc83e9a9a",
      "parameters": {
        "path": "a716761a-b062-4f93-9734-04fdc83e9a9a",
        "options": {},
        "httpMethod": "POST"
      },
      "typeVersion": 2
    },
    {
      "id": "82fb7f3c-137f-4d28-8764-4b71ecca18d4",
      "name": "HTTP Request",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        940,
        420
      ],
      "parameters": {
        "url": "=https://api.intercom.io/conversations/{{ $json.body.data.item.id }}?display_as=plaintext' ",
        "options": {},
        "authentication": "predefinedCredentialType",
        "nodeCredentialType": "intercomApi"
      },
      "credentials": {
        "intercomApi": {
          "id": "Tx85thcOrnYamj7m",
          "name": "Intercom account"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "42d3660f-ef89-4b05-92b7-8efbe1d5a9d4",
      "name": "Agente de IA",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        2480,
        120
      ],
      "parameters": {
        "text": "={{ $json }}",
        "options": {
          "systemMessage": "I manage a customer support team based in India. I want to evaluate how our agents handle live chat conversations. \n\nThe goal is to improve response speed, clarity, urgency handling, tone, ownership, and problem resolution.\n\nYou are to act like a human QA reviewer — not an AI. \n\nProvide straight, coaching-style feedback in simple, easy-to-understand language that agents can learn and act on.\n\nConversation mostly have involvement of AI replies in the name of \"Alisha ( AI Bot ) from Saleshandy\" initially and then if not solved real human team member participate. \n\n🧠 Tone Reminder\nUse a friendly, coaching tone — never sound like a complaint. The goal is to help the agent grow, not to shame them.\n\n🔧 GPT Feedback Instructions\n\n✅ Be factual, crisp, and direct\n\n✅ Avoid technical or fancy words\n\n✅ Use exact sentences from the chat to highlight mistakes\n\n✅ Suggest a clear and improved reply\n\n✅ Explain the impact and what the agent should do instead\n\n✅ Use the agent’s first name (from the transcript) — never say “agent” or mention AI\n\n✅ Adjust tone and expectations if the customer was angry, confused, or seemed in a hurry\n\n✅ Our support hours are from 10:00 AM to 2:30 AM IST\n\n✅ If team member has not participated in the conversation, mention the rating is for AI bot i.e Alisa. \n\n✅ Ensure the feedback is easy to read:\n- Use proper line breaks and spacing\n- Keep sentences short and clear (ideally under 20 words)\n- Use bullets or emojis where helpful\n- Avoid large blocks of text\n\n\nFedback formate\n\nResponse Time: (Fast / Okay / Slow)\n\nWas the reply quick or delayed? Include the customer's wait time if available.\n\nClarity of Answers: (Clear / Confusing / Incomplete)\n\nWas the explanation simple and understandable?\n\nTone & Behavior: (Polite / Robotic / Rude)\n\nDid the agent sound human, helpful, and respectful?\n\nUrgency Handling: (Handled Well / Ignored / Unaware)\n\nDid the agent notice urgency and respond accordingly?\n\nOwnership & Accountability: (Strong / Weak / Avoiding)\n\nDid the agent take responsibility or deflect the issue?\n\nDid They Solve the Problem? (Yes / Partially / No)\n\nWas the issue resolved or clearly guided?\n\nGive conversation start date & end date in seperate lines (follow yyyy-mm-dd formate)\n\nOverall Score: (1 to 5)\n\nScoring Guide\n5 – Excellent (All aspects handled well with ownership)\n4 – Good (Minor gaps, customer likely satisfied)\n3 – Average (Some confusion, but no major damage)\n2 – Poor (Multiple issues, customer likely frustrated)\n1 – Unacceptable (Neglected, robotic, or disrespectful)\n\n\nOutput Format Requirements:\n\n⚠️ Return output as a pure JSON array, no extra keys, no string wrapping, no markdown, no triple backticks.\n\nDo NOT wrap the JSON in any extra string or code block.\n\n🔁 Only return the array.\n✅ No markdown formatting\n✅ No output: key\n✅ No escaping of quotes\n✅ No explanation\n✅ No wrapping in a string\n\nSample below:\n\n[\n    {\n        \"Response Time\": \"Fast\",\n        \"Clarity of Answers\": \"Confusing\",\n        \"Tone & Behavior\": \"Polite\",\n        \"Urgency Handling\": \"Ignored\",\n        \"Ownership & Accountability\": \"Weak\",\n        \"Did They Solve the Problem?\": \"No\",\n        \"Start Date\": \"2025-07-07\",\n        \"End Date\": \"2025-07-07\",\n        \"Overall Score\": 2\n    }\n]"
        },
        "promptType": "define"
      },
      "typeVersion": 1.8
    },
    {
      "id": "b71a3cfd-e33a-4bbe-8e14-d6b25aed76aa",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        2568,
        340
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o",
          "cachedResultName": "gpt-4o"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "CAQP7fWZtZcilByu",
          "name": "Dhruv's OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "0dec2602-4e2d-43d4-b494-094f9a3c5e29",
      "name": "Dividir",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        1380,
        570
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "conversation_parts"
      },
      "typeVersion": 1
    },
    {
      "id": "b5a0fd7a-c73c-44b6-bbda-86daf62dc1aa",
      "name": "Código",
      "type": "n8n-nodes-base.code",
      "position": [
        1600,
        570
      ],
      "parameters": {
        "jsCode": "// Start from items[1], since items[0] only has metadata\nconst conversationParts = items[1].json;\n\nconst output = [];\n\nfor (const key in conversationParts) {\n  const part = conversationParts[key];\n\n  if (part && part.part_type === 'comment') {\n    output.push({\n      json: part,\n      pairedItem: {\n        item: 1, // link to items[1], where the data came from\n      },\n    });\n  }\n}\n\nreturn output;\n"
      },
      "typeVersion": 2,
      "alwaysOutputData": true
    },
    {
      "id": "0ba2ff75-4ee6-4db8-8aef-8d7bbfc56ccd",
      "name": "Dividir1",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        1820,
        570
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "body, created_at, author.type, author.name, author.email"
      },
      "typeVersion": 1
    },
    {
      "id": "963b2239-32af-4cb0-a130-e3b067b6fe7e",
      "name": "Código1",
      "type": "n8n-nodes-base.code",
      "position": [
        2040,
        570
      ],
      "parameters": {
        "jsCode": "function formatTimestamp(unixTime) {\n  const date = new Date(unixTime * 1000);\n  return date.toISOString().replace('T', ' ').split('.')[0]; // \"YYYY-MM-DD HH:mm:ss\"\n}\n\nlet combinedText = items.map(item => {\n  const body = item.json.body || '';\n  const author = item.json[\"author.name\"] || 'Unknown';\n  const role = item.json[\"author.type\"] || 'unknown';\n  const timestamp = item.json.created_at ? formatTimestamp(item.json.created_at) : 'Unknown time';\n\n  const cleanBody = body.replace(/<[^>]*>/g, '').trim();\n\n  let speaker = 'Unknown';\n  if (role === 'user') {\n    speaker = 'User';\n  } else if (role === 'bot') {\n    speaker = 'Bot';\n  } else if (role === 'admin') {\n    speaker = 'Admin';\n  }\n\n  return `[${timestamp}] ${speaker} (${author}): ${cleanBody}`;\n}).join('\\n\\n');\n\nreturn [\n  {\n    json: {\n      conversation: combinedText\n    }\n  }\n];\n"
      },
      "typeVersion": 2
    },
    {
      "id": "e51d2ee7-fd29-4535-88be-94bbaf5083dd",
      "name": "Código2",
      "type": "n8n-nodes-base.code",
      "position": [
        2856,
        220
      ],
      "parameters": {
        "jsCode": "const raw = $json[\"output\"];\nreturn JSON.parse(raw);\n"
      },
      "typeVersion": 2
    },
    {
      "id": "d15b437b-e2a3-4fcc-a167-7bcc1c1ac8ff",
      "name": "Dividir2",
      "type": "n8n-nodes-base.splitOut",
      "position": [
        1820,
        170
      ],
      "parameters": {
        "options": {},
        "fieldToSplitOut": "source.body, source.delivered_as, source.author.name, source.author.email, "
      },
      "typeVersion": 1
    },
    {
      "id": "a4d0c944-d7d3-4fa2-8549-24e0895f9ecd",
      "name": "Código3",
      "type": "n8n-nodes-base.code",
      "position": [
        2040,
        170
      ],
      "parameters": {
        "jsCode": "return items.map(item => {\n  const data = item.json;\n\n  // Remove HTML tags from body if needed\n  const plainBody = data[\"source.body\"]\n    ? data[\"source.body\"].replace(/<[^>]*>/g, '').trim()\n    : '';\n\n  const name = data[\"source.author.name\"] || 'Unknown';\n  const email = data[\"source.author.email\"] || 'unknown@example.com';\n\n  return {\n    json: {\n      conversationinitiatied: `${name} (${email}): ${plainBody}`\n    }\n  };\n});\n"
      },
      "typeVersion": 2
    },
    {
      "id": "f8e6b7dc-9a3d-4ffa-ace0-dc2da6dd5534",
      "name": "Combinar",
      "type": "n8n-nodes-base.merge",
      "position": [
        2260,
        220
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineByPosition"
      },
      "typeVersion": 3.2
    },
    {
      "id": "9afa1edb-2693-4705-b1af-ac5b56beea2c",
      "name": "Agente de IA1",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        2480,
        620
      ],
      "parameters": {
        "text": "={{ $json.conversation }}",
        "options": {
          "systemMessage": "Analyze the following conversation transcript.\n\nYour tasks:\n\nCount the number of messages sent by each role: Bot, User, and Admin.\n\nIdentify who was the last admin person to send a message (include their name, avoid considering bot or user for the last messsage).\n\n✅ Output the result in the following JSON format:\n\njson\n{\n  {\n    \"Bot\": 10,\n    \"User\": 8,\n    \"Admin\": 5\n  \"last_message_by\":\n    \"name\": \"Kinjal\",\n}\n"
        },
        "promptType": "define"
      },
      "typeVersion": 2
    },
    {
      "id": "e41e5ed9-069b-4a6b-b0d1-e07a628b4be8",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        2568,
        840
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "W1K5DlnXfMcbyFKe",
          "name": "Raj Bheda's OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "7e77f48d-2201-4e87-9426-9e9f0a84460d",
      "name": "Combinar1",
      "type": "n8n-nodes-base.merge",
      "position": [
        3076,
        420
      ],
      "parameters": {
        "mode": "combine",
        "options": {},
        "combineBy": "combineByPosition"
      },
      "typeVersion": 3.2
    },
    {
      "id": "d1390d6c-d5f7-4789-8751-89bfdf2c11d7",
      "name": "Código5",
      "type": "n8n-nodes-base.code",
      "position": [
        2856,
        620
      ],
      "parameters": {
        "jsCode": "let raw = $json[\"output\"];\n\n// Remove Markdown-style code block if present\nraw = raw.replace(/^```json\\n/, '').replace(/\\n```$/, '');\n\nreturn JSON.parse(raw);\n"
      },
      "typeVersion": 2
    },
    {
      "id": "69277b71-7eb0-444d-9b9b-0f4bc3795811",
      "name": "Agregar fila en hoja",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        3296,
        320
      ],
      "parameters": {
        "columns": {
          "value": {
            "Tone": "={{ $json[\"Tone & Behavior\"] }}",
            "Solved": "={{ $json[\"Did They Solve the Problem?\"] }}",
            "Clarity": "={{ $json[\"Clarity of Answers\"] }}",
            "Urgency": "={{ $json[\"Urgency Handling\"] }}",
            "Ownership": "={{ $json[\"Ownership & Accountability\"] }}",
            "#Bot Replies ": "={{ $json.Bot }}",
            "Overall Score": "={{ $json[\"Overall Score\"] }}",
            "Response time": "={{ $json[\"Response Time\"] }}",
            "Conversation ID": "={{ $item(0).$node[\"HTTP Request\"].json[\"id\"] }}",
            "Last Message by": "={{ $json.last_message_by.name }}",
            "Our Replies count": "={{ $json.Admin }}",
            "#User Replies Count": "={{ $json.User }}",
            "Conversation end date": "={{ $json[\"End Date\"] }}",
            "Conversation Start Date": "={{ $json[\"Start Date\"] }}"
          },
          "schema": [
            {
              "id": "Conversation end date",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Conversation end date",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Conversation Start Date",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Conversation Start Date",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Conversation ID",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Conversation ID",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Intercom URL",
              "type": "string",
              "display": true,
              "removed": true,
              "required": false,
              "displayName": "Intercom URL",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Response time",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Response time",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Clarity",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Clarity",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Tone",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Tone",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Urgency",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Urgency",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Ownership",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Ownership",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Solved",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Solved",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Overall Score",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Overall Score",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Time to close (Days)",
              "type": "string",
              "display": true,
              "removed": true,
              "required": false,
              "displayName": "Time to close (Days)",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "#Bot Replies ",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "#Bot Replies ",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "#User Replies Count",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "#User Replies Count",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Our Replies count",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Our Replies count",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Last Message by",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Last Message by",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "Conversation Start Date"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "append",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 1593039064,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1f9VmrRKolmn3PKIyLWy0yVSiTlQ1QbCAz-8E93XzTJM/edit#gid=1593039064",
          "cachedResultName": "AI.Coach"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1f9VmrRKolmn3PKIyLWy0yVSiTlQ1QbCAz-8E93XzTJM",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1f9VmrRKolmn3PKIyLWy0yVSiTlQ1QbCAz-8E93XzTJM/edit?usp=drivesdk",
          "cachedResultName": "Daily Input Update (DIU) - Customer Support"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "WqAbIK1oyEv92RRM",
          "name": "Dhruv's Google Sheets"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "cc12f47b-8421-44da-887d-d096635a8be4",
      "name": "Si",
      "type": "n8n-nodes-base.if",
      "position": [
        1160,
        420
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "or",
          "conditions": [
            {
              "id": "b7f80639-c3cd-49ae-acbb-0f54d399844a",
              "operator": {
                "name": "filter.operator.equals",
                "type": "string",
                "operation": "equals"
              },
              "leftValue": "={{ $json.custom_attributes.Type }}",
              "rightValue": "Spam/Promotional"
            },
            {
              "id": "344ac3eb-6308-4973-882b-274cee353dac",
              "operator": {
                "name": "filter.operator.equals",
                "type": "string",
                "operation": "equals"
              },
              "leftValue": "={{ $json.custom_attributes.Type }}",
              "rightValue": "Other"
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "a86ada21-36c9-46cd-81d4-b3c038311f34",
      "name": "Si1",
      "type": "n8n-nodes-base.if",
      "position": [
        3296,
        520
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "ef9a24d9-2cc2-4199-b9e4-2d8d85771b4f",
              "operator": {
                "type": "number",
                "operation": "lte"
              },
              "leftValue": "={{ $json['Overall Score'] }}",
              "rightValue": 3
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "86e0be5c-4328-4468-a567-7ba66039ae5a",
      "name": "Agente de IA2",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        3516,
        520
      ],
      "parameters": {
        "text": "={{ $('Merge').item.json.conversationinitiatied }}{{ $('Merge').item.json.conversation }}",
        "options": {
          "systemMessage": "I manage a customer support team based in India. I want to evaluate how our agents handle live chat conversations. \n\nThe goal is to improve response speed, clarity, urgency handling, tone, ownership, and problem resolution.\n\nYou are to act like a human QA reviewer — not an AI. \n\nProvide straight, coaching-style feedback in simple, easy-to-understand language that agents can learn and act on.\n\nConversation mostly have involvement of AI replies in the name of \"Alisha ( AI Bot ) from Saleshandy\" initially and then if not solved real human team member participate. \n\n🧠 Tone Reminder\nUse a friendly, coaching tone — never sound like a complaint. The goal is to help the agent grow, not to shame them.\n\n🔧 GPT Feedback Instructions\n\n✅ Be factual, crisp, and direct\n\n✅ Avoid technical or fancy words\n\n✅ Use exact sentences from the chat to highlight mistakes\n\n✅ Suggest a clear and improved reply\n\n✅ Explain the impact and what the agent should do instead\n\n✅ Use the agent’s first name (from the transcript) — never say “agent” or mention AI\n\n✅ Adjust tone and expectations if the customer was angry, confused, or seemed in a hurry\n\n✅ Our support hours are from 10:00 AM to 2:30 AM IST\n\n✅ If team member has not participated in the conversation, mention the rating is for AI bot i.e Alisa. \n\n✅ Ensure the feedback is easy to read:\n- Use proper line breaks and spacing\n- Keep sentences short and clear (ideally under 20 words)\n- Use bullets or emojis where helpful\n- Avoid large blocks of text\n\n\n📣 Feedback for Team member \n\nWhat you did well\n\nMention 1–2 positive points (e.g., polite tone, clear guidance, fast reply)\n\nWhere you messed up\n❌ Quote the exact problematic sentence\n✅ Show a better version\n➕ Explain the impact and the expected behavior\n\nWhat the customer likely felt\n\nExplain in simple, emotional terms (e.g., “The customer probably felt ignored…”)\n\nHow to fix it next time\n\nGive practical advice the agent can follow in future chats\n\n🔄 Example Feedback\n❌ You said: “We will check and revert in 1 hour” — but the customer had already waited 12 hours.\n\nThis reply added no value and made the customer feel ignored.\n\n✅ Instead: “Apologies for the delay. I’ve checked internally — we need another hour and will update you by 4 PM IST today.”\n→ This shows urgency, ownership, and clear commitment.\n\n❌ You wrote: “We regret the inconvenience caused” without offering a solution.\n✅ Don’t paste sympathy lines. Understand the issue and respond with a real fix.\n"
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    },
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      "name": "OpenAI Chat Model2",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
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          "mode": "list",
          "value": "chatgpt-4o-latest",
          "cachedResultName": "chatgpt-4o-latest"
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      "credentials": {
        "openAiApi": {
          "id": "W1K5DlnXfMcbyFKe",
          "name": "Raj Bheda's OpenAi account"
        }
      },
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      "name": "Nota adhesiva",
      "type": "n8n-nodes-base.stickyNote",
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        "content": "\n# 🧠 Intercom Conversation QA Review Automation – n8n Workflow\n\n## ✅ Objective\n\nAutomate the QA review of Intercom support conversations using AI to:\n\n* Evaluate agent performance\n* Log structured feedback\n* Provide coaching where needed\n* Track trends in customer interactions\n\n---\n\n## 🧩 Workflow Overview\n\n### 1. **Webhook Trigger**\n\n* Listens for `conversation.admin.closed` events from Intercom.\n* Initiates the workflow whenever a conversation is closed.\n\n### 2. **Fetch Conversation Details**\n\n* Uses Intercom API to retrieve the full conversation using `conversation ID`.\n\n### 3. **Filter Irrelevant Conversations**\n\n* Skips conversations marked as “Spam/Promotional” or “Other” via `custom_attributes`.\n\n### 4. **Structure the Conversation**\n\n* Extracts:\n\n  * Message body\n  * Role (User, Bot, Admin)\n  * Author name\n  * Timestamps\n* Formats messages into a readable transcript.\n\n### 5. **AI-Powered Evaluation (Parallel Branches)**\n\n#### A. 🧪 **Performance Scoring (GPT-4o)**\n\nEvaluates the following attributes:\n\n* **Response Time**\n* **Clarity of Answers**\n* **Tone & Behavior**\n* **Urgency Handling**\n* **Ownership & Accountability**\n* **Problem Solving**\n* Outputs:\n\n  * `Start Date`, `End Date`\n  * `Overall Score` (1 to 5)\n  * Attribute-wise scores\n\n#### B. 🔍 **Message Analytics**\n\n* Counts the number of messages from:\n\n  * Bot\n  * User\n  * Admin\n* Identifies the **last admin responder's name**\n\n### 6. **Merge & Log**\n\n* Combines scoring and metadata\n* Appends the data to a Google Sheet:\n\n  * **Sheet:** `Daily Input Update`\n  * **Tab:** `AI.Coach`\n\n### 7. **Optional: Coaching Feedback Generator (Score ≤ 3)**\n\n* Triggered if the score is 3 or below\n* Generates coaching feedback in this format:\n\n  * ✅ What went well\n  * ❌ What needs fixing (with quote + suggestion)\n  * 😕 How the customer likely felt\n  * 🔄 What to do differently next time\n\n---\n\n## 📈 Example Output\n\n| Conversation ID | Response Time | Clarity | Tone   | Ownership | Overall Score | Last Message By |\n| --------------- | ------------- | ------- | ------ | --------- | ------------- | --------------- |\n| 215469787223351 | Fast          | Clear   | Polite | Strong    | 5             | Kinjal          |\n\n---\n\n## 💡 Why It Matters\n\n* Automates repetitive QA work at scale\n* Transforms unstructured conversations into actionable insights\n* Boosts support quality, ownership, and customer satisfaction\n* Offers personalized, high-signal feedback for team coaching\n\n---"
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                        "title": "Sender Rotation: What, Why, and How to Set it Up?",
                        "locale": "en",
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                        "locale": "en",
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                },
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                "custom_attributes": {
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                  "Copilot used": false,
                  "Auto-translated": false,
                  "Has attachments": false,
                  "AI Answer Length": "Concise",
                  "AI Tone of Voice": "Friendly",
                  "AI Pronoun Formality": "Let Fin decide",
                  "Conversation Priority": "Highest",
                  "Fin AI Agent: Preview": false,
                  "Fin AI Agent resolution state": "Confirmed Resolution"
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                "conversation_parts": {
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                "ai_agent_participated": true
              },
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            },
            "self": null,
            "type": "notification_event",
            "links": {},
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            "app_id": "g27xawt4",
            "created_at": 1752070590,
            "delivered_at": 0,
            "first_sent_at": 1752070591,
            "delivery_status": "pending",
            "delivery_attempts": 1
          },
          "query": {},
          "params": {},
          "headers": {
            "date": "Wed, 09 Jul 2025 14:16:31 GMT",
            "host": "cygnus.saleshandy.com",
            "accept": "application/json",
            "cf-ray": "95c8708ccf1a2d15-IAD",
            "cdn-loop": "cloudflare; loops=1",
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            "cf-ipcountry": "US",
            "content-type": "application/json",
            "content-length": "4350",
            "accept-encoding": "gzip, br",
            "x-amzn-trace-id": "Root=1-686e79bf-58c9924b30bd58ee44441bbc",
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            "x-hub-signature": "sha1=de547f642efa133f34b1b44aba1a045a440e71fe",
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            "x-forwarded-port": "443",
            "x-forwarded-proto": "https",
            "x-datadog-trace-id": "246277491046908309",
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            "x-datadog-sampling-priority": "1",
            "intercom-webhook-subscription-id": "nsub_wd_44657dbe-c0a4-4f1d-a4f1-92b9c1a7bf93_g27xawt4"
          },
          "webhookUrl": "https://cygnus.saleshandy.com/webhook/a716761a-b062-4f93-9734-04fdc83e9a9a",
          "executionMode": "production"
        }
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Preguntas frecuentes

¿Cómo usar este flujo de trabajo?

Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.

¿En qué escenarios es adecuado este flujo de trabajo?

Avanzado - Gestión de tickets, Resumen de IA

¿Es de pago?

Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.

Información del flujo de trabajo
Nivel de dificultad
Avanzado
Número de nodos22
Categoría2
Tipos de nodos10
Descripción de la dificultad

Adecuado para usuarios avanzados, flujos de trabajo complejos con 16+ nodos

Enlaces externos
Ver en n8n.io

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Categorías

Categorías: 34