Workflow n8n

Automatisation WhatsApp avec n8n : réponse automatique aux messages

Ce workflow n8n a pour objectif d'automatiser les réponses aux messages reçus sur WhatsApp, permettant ainsi aux entreprises de gérer efficacement les interactions clients. Dans un contexte où la réactivité est cruciale, ce type d'automatisation n8n est particulièrement utile pour les équipes de support client ou de vente qui souhaitent offrir un service rapide et personnalisé. En intégrant des modèles d'IA, ce workflow permet de fournir des réponses pertinentes en temps réel, améliorant ainsi l'expérience utilisateur. Étape 1 : Le déclencheur 'WhatsApp Trigger' capte les messages entrants sur WhatsApp. Étape 2 : Les messages sont ensuite traités par le noeud 'AI Sales Agent', qui utilise des modèles OpenAI pour générer des réponses adaptées. Étape 3 : Les réponses sont envoyées via le noeud 'Reply To User', garantissant une communication fluide. Ce workflow utilise également des outils de gestion de mémoire et de stockage de vecteurs pour optimiser les interactions. En intégrant ce système, les entreprises peuvent réduire le temps de réponse, minimiser les erreurs humaines et améliorer la satisfaction client, tout en libérant du temps pour leurs équipes. Tags clés : automatisation, WhatsApp, IA.

Catégorie: Webhook · Tags: automatisation, WhatsApp, IA, n8n, service client0

Vue d'ensemble du workflow n8n

Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.

Détail des nœuds du workflow n8n

  • WhatsApp Trigger

    Ce noeud déclenche le workflow lorsqu'un message est reçu via WhatsApp.

  • OpenAI Chat Model

    Ce noeud utilise le modèle de chat OpenAI pour générer des réponses basées sur les entrées fournies.

  • Window Buffer Memory

    Ce noeud gère la mémoire tampon pour stocker les sessions de conversation.

  • Vector Store Tool

    Ce noeud interagit avec un magasin de vecteurs pour stocker et récupérer des données.

  • Embeddings OpenAI

    Ce noeud génère des embeddings à l'aide du modèle OpenAI.

  • OpenAI Chat Model1

    Ce noeud utilise un autre modèle de chat OpenAI pour traiter les requêtes.

  • When clicking ‘Test workflow’

    Ce noeud permet de tester manuellement le workflow.

  • Embeddings OpenAI1

    Ce noeud génère des embeddings à l'aide d'un modèle OpenAI supplémentaire.

  • Default Data Loader

    Ce noeud charge des données par défaut à partir de documents pour les traiter.

  • Recursive Character Text Splitter

    Ce noeud divise le texte en morceaux en utilisant un séparateur de caractères récursif.

  • Extract from File

    Ce noeud extrait des données à partir d'un fichier selon les options spécifiées.

  • get Product Brochure

    Ce noeud effectue une requête HTTP pour obtenir une brochure de produit.

  • Reply To User

    Ce noeud envoie une réponse à l'utilisateur via WhatsApp.

  • Reply To User1

    Ce noeud envoie une réponse à l'utilisateur via WhatsApp, similaire au précédent.

  • Product Catalogue

    Ce noeud crée un catalogue de produits en mémoire.

  • Sticky Note

    Ce noeud crée une note autocollante avec les paramètres spécifiés.

  • Sticky Note1

    Ce noeud crée une autre note autocollante avec des spécifications similaires.

  • Create Product Catalogue

    Ce noeud crée un catalogue de produits en mémoire avec des options de mode.

  • Sticky Note2

    Ce noeud crée une note autocollante supplémentaire.

  • Sticky Note3

    Ce noeud crée une note autocollante avec des dimensions spécifiées.

  • Sticky Note4

    Ce noeud crée une note autocollante avec des paramètres de couleur et de taille.

  • Sticky Note5

    Ce noeud crée une note autocollante avec des spécifications de couleur et de taille.

  • Sticky Note6

    Ce noeud crée une note autocollante avec des paramètres de couleur et de taille.

  • Sticky Note7

    Ce noeud crée une note autocollante avec des dimensions spécifiées.

  • Handle Message Types

    Ce noeud gère les types de messages en fonction des règles définies.

  • Sticky Note8

    Ce noeud crée une note autocollante avec des paramètres de couleur et de taille.

  • Sticky Note9

    Ce noeud crée une note autocollante avec des spécifications de couleur et de taille.

  • AI Sales Agent

    Ce noeud agit comme un agent de vente AI, traitant les entrées et générant des réponses.

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{
  "meta": {
    "instanceId": "408f9fb9940c3cb18ffdef0e0150fe342d6e655c3a9fac21f0f644e8bedabcd9"
  },
  "nodes": [
    {
      "id": "77ee6494-4898-47dc-81d9-35daf6f0beea",
      "name": "WhatsApp Trigger",
      "type": "n8n-nodes-base.whatsAppTrigger",
      "position": [
        1360,
        -280
      ],
      "webhookId": "aaa71f03-f7af-4d18-8d9a-0afb86f1b554",
      "parameters": {
        "updates": [
          "messages"
        ]
      },
      "credentials": {
        "whatsAppTriggerApi": {
          "id": "H3uYNtpeczKMqtYm",
          "name": "WhatsApp OAuth account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "57210e27-1f89-465a-98cc-43f890a4bf58",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1960,
        -200
      ],
      "parameters": {
        "model": "gpt-4o-2024-08-06",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "e1053235-0ade-4e36-9ad2-8b29c78fced8",
      "name": "Window Buffer Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        2080,
        -200
      ],
      "parameters": {
        "sessionKey": "=whatsapp-75-{{ $json.messages[0].from }}",
        "sessionIdType": "customKey"
      },
      "typeVersion": 1.2
    },
    {
      "id": "69f1b78b-7c93-4713-863a-27e04809996f",
      "name": "Vector Store Tool",
      "type": "@n8n/n8n-nodes-langchain.toolVectorStore",
      "position": [
        2200,
        -200
      ],
      "parameters": {
        "name": "query_product_brochure",
        "description": "Call this tool to query the product brochure. Valid for the year 2024."
      },
      "typeVersion": 1
    },
    {
      "id": "170e8f7d-7e14-48dd-9f80-5352cc411fc1",
      "name": "Embeddings OpenAI",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        2200,
        80
      ],
      "parameters": {
        "model": "text-embedding-3-small",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "ee78320b-d407-49e8-b4b8-417582a44709",
      "name": "OpenAI Chat Model1",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        2440,
        -60
      ],
      "parameters": {
        "model": "gpt-4o-2024-08-06",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "9dd89378-5acf-4ca6-8d84-e6e64254ed02",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        0,
        -240
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "e68fc137-1bcb-43f0-b597-3ae07f380c15",
      "name": "Embeddings OpenAI1",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        760,
        -20
      ],
      "parameters": {
        "model": "text-embedding-3-small",
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "8gccIjcuf3gvaoEr",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "2d31e92b-18d4-4f6b-8cdb-bed0056d50d7",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        900,
        -20
      ],
      "parameters": {
        "options": {},
        "jsonData": "={{ $('Extract from File').item.json.text }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "ca0c015e-fba2-4dca-b0fe-bac66681725a",
      "name": "Recursive Character Text Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        900,
        100
      ],
      "parameters": {
        "options": {},
        "chunkSize": 2000,
        "chunkOverlap": {}
      },
      "typeVersion": 1
    },
    {
      "id": "63abb6b2-b955-4e65-9c63-3211dca65613",
      "name": "Extract from File",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        360,
        -240
      ],
      "parameters": {
        "options": {},
        "operation": "pdf"
      },
      "typeVersion": 1
    },
    {
      "id": "be2add9c-3670-4196-8c38-82742bf4f283",
      "name": "get Product Brochure",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        180,
        -240
      ],
      "parameters": {
        "url": "https://usa.yamaha.com/files/download/brochure/1/1474881/Yamaha-Powered-Loudspeakers-brochure-2024-en-web.pdf",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "1ae5a311-36d7-4454-ab14-6788d1331780",
      "name": "Reply To User",
      "type": "n8n-nodes-base.whatsApp",
      "position": [
        2820,
        -280
      ],
      "parameters": {
        "textBody": "={{ $json.output }}",
        "operation": "send",
        "phoneNumberId": "477115632141067",
        "requestOptions": {},
        "additionalFields": {
          "previewUrl": false
        },
        "recipientPhoneNumber": "={{ $('WhatsApp Trigger').item.json.messages[0].from }}"
      },
      "credentials": {
        "whatsAppApi": {
          "id": "9SFJPeqrpChOkAmw",
          "name": "WhatsApp account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "b6efba81-18b0-4378-bb91-51f39ca57f3e",
      "name": "Reply To User1",
      "type": "n8n-nodes-base.whatsApp",
      "position": [
        1760,
        80
      ],
      "parameters": {
        "textBody": "=I'm unable to process non-text messages. Please send only text messages. Thanks!",
        "operation": "send",
        "phoneNumberId": "477115632141067",
        "requestOptions": {},
        "additionalFields": {
          "previewUrl": false
        },
        "recipientPhoneNumber": "={{ $('WhatsApp Trigger').item.json.messages[0].from }}"
      },
      "credentials": {
        "whatsAppApi": {
          "id": "9SFJPeqrpChOkAmw",
          "name": "WhatsApp account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "52decd86-ac6c-4d91-a938-86f93ec5f822",
      "name": "Product Catalogue",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
      "position": [
        2200,
        -60
      ],
      "parameters": {
        "memoryKey": "whatsapp-75"
      },
      "typeVersion": 1
    },
    {
      "id": "6dd5a652-2464-4ab8-8e5f-568529299523",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -88.75,
        -473.4375
      ],
      "parameters": {
        "color": 7,
        "width": 640.4375,
        "height": 434.6875,
        "content": "## 1. Download Product Brochure PDF\n[Read more about the HTTP Request Tool](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.httprequest)\n\nImport your marketing PDF document to build your vector store. This will be used as the knowledgebase by the Sales AI Agent.\n\nFor this demonstration, we'll use the HTTP request node to import the YAMAHA POWERED LOUDSPEAKERS 2024 brochure ([Source](https://usa.yamaha.com/files/download/brochure/1/1474881/Yamaha-Powered-Loudspeakers-brochure-2024-en-web.pdf)) and an Extract from File node to extract the text contents. "
      },
      "typeVersion": 1
    },
    {
      "id": "116663bc-d8d6-41a5-93dc-b219adbb2235",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        580,
        -476
      ],
      "parameters": {
        "color": 7,
        "width": 614.6875,
        "height": 731.1875,
        "content": "## 2. Create Product Brochure Vector Store\n[Read more about the In-Memory Vector Store](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.vectorstoreinmemory/)\n\nVector stores are powerful databases which serve the purpose of matching a user's questions to relevant parts of a document. By creating a vector store of our product catalog, we'll allow users to query using natural language.\n\nTo keep things simple, we'll use the **In-memory Vector Store** which comes built-in to n8n and doesn't require a separate service. For production deployments, I'd recommend replacing the in-memory vector store with either [Qdrant](https://qdrant.tech) or [Pinecone](https://pinecone.io)."
      },
      "typeVersion": 1
    },
    {
      "id": "86bd5334-d735-4650-aeff-06230119d705",
      "name": "Create Product Catalogue",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
      "position": [
        760,
        -200
      ],
      "parameters": {
        "mode": "insert",
        "memoryKey": "whatsapp-75",
        "clearStore": true
      },
      "typeVersion": 1
    },
    {
      "id": "b8078b0d-cbd7-423f-bb30-13902988be38",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1254,
        -552
      ],
      "parameters": {
        "color": 7,
        "width": 546.6875,
        "height": 484.1875,
        "content": "## 3. Use the WhatsApp Trigger\n[Learn more about the WhatsApp Trigger](https://docs.n8n.io/integrations/builtin/trigger-nodes/n8n-nodes-base.whatsapptrigger/)\n\nThe WhatsApp Trigger allows you to receive incoming WhatsApp messages from customers. It requires a bit of setup so remember to follow the documentation carefully! Once ready however, it's quite easy to build powerful workflows which are easily accessible to users.\n\nNote that WhatsApp can send many message types such as audio and video so in this demonstration, we'll filter them out and just accept the text messages."
      },
      "typeVersion": 1
    },
    {
      "id": "5bf7ed07-282b-4198-aa90-3e5ae5180404",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1640,
        280
      ],
      "parameters": {
        "width": 338,
        "height": 92,
        "content": "### Want to handle all message types?\nCheck out my other WhatsApp template in my creator page! https://n8n.io/creators/jimleuk/"
      },
      "typeVersion": 1
    },
    {
      "id": "a3661b59-25d2-446e-8462-32b4d692b69d",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1640,
        -40
      ],
      "parameters": {
        "color": 7,
        "width": 337.6875,
        "height": 311.1875,
        "content": "### 3a. Handle Unsupported Message Types\nFor non-text messages, we'll just reply with a simple message to inform the sender."
      },
      "typeVersion": 1
    },
    {
      "id": "ea3c9ee1-505a-40e7-82fe-9169bdbb80af",
      "name": "Sticky Note5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1840,
        -682.5
      ],
      "parameters": {
        "color": 7,
        "width": 746.6875,
        "height": 929.1875,
        "content": "## 4. Sales AI Agent Responds To Customers\n[Learn more about using AI Agents](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/)\n\nn8n's AI agents are powerful nodes which make it incredibly easy to use state-of-the-art AI in your workflows. Not only do they have the ability to remember conversations per individual customer but also tap into resources such as our product catalogue vector store to pull factual information and data for every question.\n\nIn this demonstration, we use an AI agent which is directed to help the user navigate the product brochure. A Chat memory subnode is attached to identify and keep track of the customer session. A Vector store tool is added to allow the Agent to tap into the product catalogue knowledgebase we built earlier."
      },
      "typeVersion": 1
    },
    {
      "id": "5c72df8d-bca1-4634-b1ed-61ffec8bd103",
      "name": "Sticky Note6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2620,
        -560
      ],
      "parameters": {
        "color": 7,
        "width": 495.4375,
        "height": 484.1875,
        "content": "## 5. Repond to WhatsApp User\n[Learn more about the WhatsApp Node](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.whatsapp/)\n\nThe WhatsApp node is the go-to if you want to interact with WhatsApp users. With this node, you can send text, images, audio and video messages as well as use your WhatsApp message templates.\n\nHere, we'll keep it simple by replying with a text message which is the output of the AI agent."
      },
      "typeVersion": 1
    },
    {
      "id": "48ec809f-ca0e-4052-b403-9ad7077b3fff",
      "name": "Sticky Note7",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -520,
        -620
      ],
      "parameters": {
        "width": 401.25,
        "height": 582.6283033962263,
        "content": "## Try It Out!\n\n### This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's questions.\n\n* This template is in 2 parts: creating the product catalog vector store and building the WhatsApp AI chatbot.\n* A product brochure is imported via HTTP request node and its text contents extracted.\n* The text contents are then uploaded to the in-memory vector store to build a knowledgebase for the chatbot.\n* A WhatsApp trigger is used to capture messages from customers where non-text messages are filtered out.\n* The customer's message is sent to the AI Agent which queries the product catalogue using the vector store tool.\n* The Agent's response is sent back to the user via the WhatsApp node.\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!"
      },
      "typeVersion": 1
    },
    {
      "id": "87cf9b41-66de-49a7-aeb0-c8809191b5a0",
      "name": "Handle Message Types",
      "type": "n8n-nodes-base.switch",
      "position": [
        1560,
        -280
      ],
      "parameters": {
        "rules": {
          "values": [
            {
              "outputKey": "Supported",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "operator": {
                      "type": "string",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $json.messages[0].type }}",
                    "rightValue": "text"
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "Not Supported",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "89971d8c-a386-4e77-8f6c-f491a8e84cb6",
                    "operator": {
                      "type": "string",
                      "operation": "notEquals"
                    },
                    "leftValue": "={{ $json.messages[0].type }}",
                    "rightValue": "text"
                  }
                ]
              },
              "renameOutput": true
            }
          ]
        },
        "options": {}
      },
      "typeVersion": 3.2
    },
    {
      "id": "e52f0a50-0c34-4c4a-b493-4c42ba112277",
      "name": "Sticky Note8",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -80,
        -20
      ],
      "parameters": {
        "color": 5,
        "width": 345.10906976744184,
        "height": 114.53583720930231,
        "content": "### You only have to run this part once!\nRun this step to populate our product catalogue vector. Run again if you want to update the vector store with a new version."
      },
      "typeVersion": 1
    },
    {
      "id": "c1a7d6d1-191e-4343-af9f-f2c9eb4ecf49",
      "name": "Sticky Note9",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1260,
        -40
      ],
      "parameters": {
        "color": 5,
        "width": 364.6293255813954,
        "height": 107.02804651162779,
        "content": "### Activate your workflow to use!\nTo start using the WhatsApp chatbot, you'll need to activate the workflow. If you are self-hosting ensure WhatsApp is able to connect to your server."
      },
      "typeVersion": 1
    },
    {
      "id": "a36524d0-22a6-48cc-93fe-b4571cec428a",
      "name": "AI Sales Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        1960,
        -400
      ],
      "parameters": {
        "text": "={{ $json.messages[0].text.body }}",
        "options": {
          "systemMessage": "You are an assistant working for a company who sells Yamaha Powered Loudspeakers and helping the user navigate the product catalog for the year 2024. Your goal is not to facilitate a sale but if the user enquires, direct them to the appropriate website, url or contact information.\n\nDo your best to answer any questions factually. If you don't know the answer or unable to obtain the information from the datastore, then tell the user so."
        },
        "promptType": "define"
      },
      "typeVersion": 1.6
    }
  ],
  "pinData": {},
  "connections": {
    "AI Sales Agent": {
      "main": [
        [
          {
            "node": "Reply To User",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "WhatsApp Trigger": {
      "main": [
        [
          {
            "node": "Handle Message Types",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings OpenAI": {
      "ai_embedding": [
        [
          {
            "node": "Product Catalogue",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Extract from File": {
      "main": [
        [
          {
            "node": "Create Product Catalogue",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Sales Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Product Catalogue": {
      "ai_vectorStore": [
        [
          {
            "node": "Vector Store Tool",
            "type": "ai_vectorStore",
            "index": 0
          }
        ]
      ]
    },
    "Vector Store Tool": {
      "ai_tool": [
        [
          {
            "node": "AI Sales Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings OpenAI1": {
      "ai_embedding": [
        [
          {
            "node": "Create Product Catalogue",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model1": {
      "ai_languageModel": [
        [
          {
            "node": "Vector Store Tool",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Default Data Loader": {
      "ai_document": [
        [
          {
            "node": "Create Product Catalogue",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Handle Message Types": {
      "main": [
        [
          {
            "node": "AI Sales Agent",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Reply To User1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Window Buffer Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Sales Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "get Product Brochure": {
      "main": [
        [
          {
            "node": "Extract from File",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Recursive Character Text Splitter": {
      "ai_textSplitter": [
        [
          {
            "node": "Default Data Loader",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "When clicking ‘Test workflow’": {
      "main": [
        [
          {
            "node": "get Product Brochure",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Pour qui est ce workflow ?

Ce workflow s'adresse aux entreprises de toutes tailles souhaitant améliorer leur service client via WhatsApp. Il est particulièrement adapté aux équipes de support et de vente, ainsi qu'aux utilisateurs ayant une connaissance technique intermédiaire de l'automatisation.

Problème résolu

Ce workflow résout le problème de la lenteur dans les réponses aux messages clients sur WhatsApp, une frustration courante pour les entreprises. En automatisant le processus de réponse, il permet de réduire les délais de réponse et d'augmenter la satisfaction client. Les utilisateurs bénéficient d'une gestion plus efficace de leurs interactions, ce qui se traduit par une meilleure rétention des clients et une augmentation des ventes.

Étapes du workflow

Étape 1 : Le workflow commence par le déclencheur 'WhatsApp Trigger', qui détecte les nouveaux messages. Étape 2 : Les messages sont ensuite envoyés au noeud 'AI Sales Agent' pour générer des réponses intelligentes. Étape 3 : Les réponses sont traitées par le noeud 'Reply To User', qui les renvoie à l'expéditeur sur WhatsApp. Étape 4 : Des noeuds supplémentaires comme 'Window Buffer Memory' et 'Vector Store Tool' sont utilisés pour optimiser la gestion des données et la mémoire, assurant ainsi une réponse contextuelle et pertinente.

Guide de personnalisation du workflow n8n

Pour personnaliser ce workflow, vous pouvez modifier les paramètres du noeud 'WhatsApp Trigger' pour spécifier le numéro de téléphone associé. Dans le noeud 'AI Sales Agent', vous pouvez ajuster les modèles OpenAI utilisés pour mieux répondre à vos besoins spécifiques. Pensez également à adapter les messages dans les noeuds 'Reply To User' pour qu'ils reflètent le ton et le style de votre marque. Enfin, vous pouvez intégrer d'autres outils ou services via des noeuds HTTP pour enrichir les réponses ou ajouter des fonctionnalités supplémentaires.