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Anrufzentrum-Transkription-Sentimentanalyse n8n

Fortgeschritten

Dies ist ein AI Summarization, Multimodal AI-Bereich Automatisierungsworkflow mit 9 Nodes. Hauptsächlich werden Set, GoogleSheets, SplitInBatches, Agent, ScheduleTrigger und andere Nodes verwendet. Anrufzentrum-Sentimentanalyse mit GPT-4o-mini und Google Sheets automatisieren

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

Verwendete Nodes (9)

Set
StickyNote
GoogleSheets
SplitInBatches
Agent
ScheduleTrigger
LmChatOpenAi
OutputParserStructured

Kategorie

KI-Zusammenfassung
Multimodales KI
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
React Flow
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "id": "6kTlui6CDAIL3vNV",
  "meta": {
    "instanceId": "9272721148ea09184b6bbb7ce6219dab088562dd450e2df8280d57c2e34c7d84",
    "templateCredsSetupCompleted": true
  },
  "name": "call-center-transcription-sentiment-analysis-n8n",
  "tags": [],
  "nodes": [
    {
      "id": "eee89774-3c9b-4e26-8bf2-9f14ee1ced97",
      "name": "OpenAI-Chat-Modell",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        192,
        128
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "id",
          "value": "=gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "zHTJ5AI7kBmTnuvv",
          "name": "InfyOm"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "77912e60-0f2a-4434-b8c7-00bc53c474a9",
      "name": "Über Elemente schleifen",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        -256,
        32
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 3
    },
    {
      "id": "d44b524d-3b67-4c48-8d52-34bba6ad16b9",
      "name": "Zeitplan-Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        -704,
        32
      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "triggerAtHour": 19
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "3173c049-13c7-483c-a6ea-65340bf585f9",
      "name": "Get All Transcript",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        -480,
        32
      ],
      "parameters": {
        "options": {},
        "filtersUI": {
          "values": [
            {
              "lookupColumn": "Status"
            }
          ]
        },
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit#gid=0",
          "cachedResultName": "Sheet1"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit?usp=drivesdk",
          "cachedResultName": "Transcript_analysis_system"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "WdaCQmtoNquNSoAA",
          "name": "Google Sheets"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "856d4c88-f8a6-41ab-b52c-639e58df2b0c",
      "name": "Send only Transcript Field",
      "type": "n8n-nodes-base.set",
      "position": [
        -32,
        -96
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "697b9e87-2767-43a8-9dfe-72c50903a5d5",
              "name": "Full Transcript",
              "type": "string",
              "value": "={{ $json[\"Full Transcript\"] }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "0aa10ec0-c836-44df-ad85-9a503e1d10e3",
      "name": "Analysis Transcript",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        192,
        -96
      ],
      "parameters": {
        "text": "={{ $json[\"Full Transcript\"] }}",
        "options": {
          "systemMessage": "=You are an advanced AI assistant specialized in sentiment analysis for customer service conversations.\n\nYour task is to extract structured data from a customer service chat transcript. Return values for each field listed below.\n\nRespond in JSON format using structured output tool with the following fields:\n\n\n- Topic (Topic name for discussion like 'Medical Report','shipping delay')\n- Customer Name\n- Agent Name\n- Greeting Sentiment (1 to 5, where 5 is very polite/friendly/Greeting and 1 is rude)\n- Closing Sentiment (1 to 5, where 5 is very Closing polite/friendly and 1 is rude)\n- Problem Solving (1 to 5, where 5 is excellent and 1 is poor)\n- Agent Friendliness (1 to 5, where 5 is very polite/friendly and 1 is rude)\n- Customer Sentiment (Before → After, e.g. \"Angry → Satisfied\")\n- Issue Resolved (Yes / No / Partially)"
        },
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 2
    },
    {
      "id": "1c427949-04d9-4ed8-9d17-d62bf34c18e8",
      "name": "Structured Output",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        368,
        128
      ],
      "parameters": {
        "jsonSchemaExample": "{\n  \"Topic\": \"XYZ\",\n  \"Customer Name\": \"John D\",\n  \"Agent Name\": \"Priya M\",\n  \"Greeting Sentiment\": 5,\n  \"Closing Sentiment\": 5,\n  \"Problem Solving\": 5,\n  \"Agent Friendliness\": 5,\n  \"Customer Sentiment\": \"Frustrated → Satisfied\",\n  \"Issue Resolved\": \"Yes\"\n}"
      },
      "typeVersion": 1.3
    },
    {
      "id": "79c31b02-f5bc-4185-b83a-6ca7caa25f6c",
      "name": "Store Analysis Transcript",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        608,
        32
      ],
      "parameters": {
        "columns": {
          "value": {
            "Status": "Done",
            "Agent Name": "={{ $json.output[\"Agent Name\"] }}",
            "Total Rating": "={{( Number($json.output[\"Greeting Sentiment\"]) + Number($json.output[\"Closing Sentiment\"]) + Number($json.output[\"Problem Solving\"]) + Number($json.output[\"Agent Friendliness\"]))/4}}\n",
            "Customer Name": "={{ $json.output[\"Customer Name\"] }}",
            "Issue Resolved": "={{ $json.output[\"Issue Resolved\"] }}",
            "Full Transcript": "={{ $('Loop Over Items').item.json['Full Transcript'] }}",
            "Problem Solving": "={{ $json.output[\"Problem Solving\"] }}",
            "Closing Sentiment": "={{ $json.output[\"Closing Sentiment\"] }}",
            "Agent Friendliness": "={{ $json.output[\"Agent Friendliness\"] }}",
            "Customer Sentiment": "={{ $json.output[\"Customer Sentiment\"] }}",
            "Greeting Sentiment": "={{ $json.output[\"Greeting Sentiment\"] }}",
            "Conversations Topics": "={{ $json.output.Topic }}"
          },
          "schema": [
            {
              "id": "Full Transcript",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Full Transcript",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Conversations Topics",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Conversations Topics",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Customer Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Customer Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Agent Name",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Agent Name",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Greeting Sentiment",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Greeting Sentiment",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Closing Sentiment",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Closing Sentiment",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Problem Solving",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Problem Solving",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Agent Friendliness",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Agent Friendliness",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Customer Sentiment",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Customer Sentiment",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Issue Resolved",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Issue Resolved",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Total Rating",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "Total Rating",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "Status",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "Status",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "row_number",
              "type": "number",
              "display": true,
              "removed": true,
              "readOnly": true,
              "required": false,
              "displayName": "row_number",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "Full Transcript"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "update",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": "gid=0",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit#gid=0",
          "cachedResultName": "Sheet1"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit?usp=drivesdk",
          "cachedResultName": "Transcript_analysis_system"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "WdaCQmtoNquNSoAA",
          "name": "Google Sheets"
        }
      },
      "typeVersion": 4.6
    },
    {
      "id": "735bad42-0258-4076-a4d2-939a4a2677f6",
      "name": "Haftnotiz",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -720,
        -176
      ],
      "parameters": {
        "width": 512,
        "height": 128,
        "content": "### Sample Google Sheet\n\nhttps://docs.google.com/spreadsheets/d/1aWU28D_73nvkDMPfTkPkaV53kHgX7cg0W4NwLzGFEGU/edit?gid=0#gid=0"
      },
      "typeVersion": 1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "a54e879a-6738-4edb-b195-8b47945d70a7",
  "connections": {
    "Loop Over Items": {
      "main": [
        [],
        [
          {
            "node": "856d4c88-f8a6-41ab-b52c-639e58df2b0c",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "3173c049-13c7-483c-a6ea-65340bf585f9",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "0aa10ec0-c836-44df-ad85-9a503e1d10e3",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "1c427949-04d9-4ed8-9d17-d62bf34c18e8": {
      "ai_outputParser": [
        [
          {
            "node": "0aa10ec0-c836-44df-ad85-9a503e1d10e3",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "3173c049-13c7-483c-a6ea-65340bf585f9": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "0aa10ec0-c836-44df-ad85-9a503e1d10e3": {
      "main": [
        [
          {
            "node": "79c31b02-f5bc-4185-b83a-6ca7caa25f6c",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "79c31b02-f5bc-4185-b83a-6ca7caa25f6c": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "856d4c88-f8a6-41ab-b52c-639e58df2b0c": {
      "main": [
        [
          {
            "node": "0aa10ec0-c836-44df-ad85-9a503e1d10e3",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Fortgeschritten - KI-Zusammenfassung, Multimodales KI

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

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Workflow-Informationen
Schwierigkeitsgrad
Fortgeschritten
Anzahl der Nodes9
Kategorie2
Node-Typen8
Schwierigkeitsbeschreibung

Für erfahrene Benutzer, mittelkomplexe Workflows mit 6-15 Nodes

Autor
InfyOm Technologies

InfyOm Technologies

@infyom

We are an AI Automation Agency focusing on various AI Automation Services like, workflow automation, shopify automation, chatbot developerment, custom ai agent development and more.

Externe Links
Auf n8n.io ansehen →

Diesen Workflow teilen

Kategorien

Multimodales KI
1540
Künstliche Intelligenz
1108
Content-Erstellung
695
KI-Zusammenfassung
516
Marketing
419
KI-Chatbot
251
Engineering
241
Marktforschung
203
Verschiedenes
193
Sonstiges
176
Vertrieb
162
IT-Betrieb
156
Dokumentenextraktion
147
KI RAG
146
Bausteine
144
Soziale Medien
137
Lead-Generierung
125
Persönliche Produktivität
117
DevOps
111
Personalwesen
101
Support
97
Lead-Pflege
87
Kundenbeziehungsmanagement
82
Finanzen
81
Produkt
77
Support-Chatbot
76
Design
70
Ticketverwaltung
67
Sicherheitsbetrieb
57
Rechnungsverarbeitung
53
Krypto-Handel
49
Dateiverwaltung
39
Projektmanagement
35
Internes Wiki
32

Kategorien: 34