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Workflow n8n

Automatisation Google Sheets avec n8n : gestion des risques de désabonnement

  • Ce workflow n8n a pour objectif de gérer le risque de désabonnement des clients en automatisant l'envoi d'offres de reconquête. Dans un contexte où la fidélisation des clients est cruciale, ce processus permet aux entreprises de cibler efficacement les clients à risque en se basant sur des données stockées dans Google Sheets. Grâce à ce workflow, les équipes marketing peuvent identifier les clients qui n'ont pas été contactés par une campagne et qui présentent un risque élevé de désabonnement, leur permettant ainsi de réagir rapidement et de proposer des offres personnalisées pour les inciter à rester.
  • Le workflow commence par un déclencheur programmé qui vérifie quotidiennement les données des clients. Ensuite, il récupère les informations des clients à partir d'une feuille Google Sheets. Un filtre est appliqué pour identifier les clients à haut risque de désabonnement qui n'ont pas encore reçu d'offre. Si des clients éligibles sont trouvés, le workflow les traite un par un pour générer une offre de reconquête à l'aide d'un modèle de langage. L'offre est ensuite envoyée par email et enregistrée dans un journal pour un suivi ultérieur. En cas d'absence de clients éligibles, le système enregistre cette information pour éviter des actions inutiles.
  • Les bénéfices de cette automatisation n8n sont multiples : elle permet de réduire le temps consacré à la gestion manuelle des désabonnements, d'améliorer la réactivité des équipes marketing et d'augmenter le taux de fidélisation des clients. En intégrant ce type de workflow, les entreprises peuvent optimiser leur stratégie de rétention et ainsi améliorer leur rentabilité.
Tags clés :automatisationGoogle Sheetsfidélisation clientn8nreconquête
🎯Pour qui ?🧩Problème résolu📋Étapes du flux🛠Guide de personnalisation
Catégorie: Scheduled · Tags: automatisation, Google Sheets, fidélisation client, n8n, reconquête❤ 0

Workflow n8n Google Sheets, fidélisation client, reconquête : vue d'ensemble

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

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Workflow n8n Google Sheets, fidélisation client, reconquête : détail des nœuds

  • Scheduled Start: Daily Churn Check

    Déclenche le workflow quotidien pour vérifier le taux de désabonnement.

  • Fetch Customer Data from Sheet

    Récupère les données des clients à partir d'une feuille Google Sheets.

  • Filter High Churn Risk & No Campaign Customers

    Filtre les clients à haut risque de désabonnement et ceux sans campagne.

  • Check if Eligible Customers Found

    Vérifie si des clients éligibles ont été trouvés.

  • Process Each Eligible Customer

    Traite chaque client éligible en les divisant en lots.

  • Generate Win-Back Offer

    Génère une offre de reconquête pour les clients.

  • (LLM Model for Offer Generation)

    Utilise un modèle LLM pour générer l'offre.

  • (Parse Offer JSON)

    Analyse le JSON de l'offre générée.

  • Log Sent Offer in System Log

    Enregistre l'offre envoyée dans le journal du système sur Google Sheets.

  • Send Win-Back Offer via Email

    Envoie l'offre de reconquête par email au client.

  • Set 'Not Found' Status

    Définit le statut 'Non trouvé' pour les clients non éligibles.

  • Log 'Not Found' in System Log

    Enregistre le statut 'Non trouvé' dans le journal du système sur Google Sheets.

  • Sticky Note

    Crée une note autocollante avec un contenu spécifique.

  • Sticky Note1

    Crée une note autocollante avec une couleur et un contenu spécifiques.

  • Sticky Note2

    Crée une note autocollante avec une couleur et un contenu spécifiques.

  • Sticky Note3

    Crée une note autocollante avec une couleur et un contenu spécifiques.

  • Sticky Note4

    Crée une note autocollante avec un contenu spécifique.

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{
  "meta": {
    "instanceId": "02e782574ebb30fbddb2c3fd832c946466d718819d25f6fe4b920124ff3fc2c1",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "13f8de57-7247-4be1-8fc4-dddc1a7d677e",
      "name": "Scheduled Start: Daily Churn Check",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        160,
        0
      ],
      "parameters": {
        "rule": {
          "interval": [
            {}
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "8f52666a-7247-4058-a775-2be80e3b4c0e",
      "name": "Fetch Customer Data from Sheet",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        440,
        0
      ],
      "parameters": {
        "options": {
          "returnFirstMatch": false
        },
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 1698897552,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k/edit#gid=1698897552",
          "cachedResultName": "Customer Data"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k/edit?usp=drivesdk",
          "cachedResultName": "Medium Post Automation"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "VV5AyFvgYkc4TfC7",
          "name": "Onur Drive "
        }
      },
      "typeVersion": 4.5
    },
    {
      "id": "37951981-3c3d-4434-8782-51e9129f0bbc",
      "name": "Filter High Churn Risk & No Campaign Customers",
      "type": "n8n-nodes-base.filter",
      "position": [
        760,
        0
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "9b78accc-0926-4537-8ce9-70206dd45525",
              "operator": {
                "type": "number",
                "operation": "gt"
              },
              "leftValue": "={{ $json.predicted_churn_score.toNumber() }}",
              "rightValue": 0.7
            }
          ]
        }
      },
      "typeVersion": 2.2,
      "alwaysOutputData": true
    },
    {
      "id": "4152752b-3ba3-4af0-aec8-aba9fc0424d9",
      "name": "Check if Eligible Customers Found",
      "type": "n8n-nodes-base.if",
      "position": [
        1140,
        0
      ],
      "parameters": {
        "options": {},
        "conditions": {
          "options": {
            "version": 2,
            "leftValue": "",
            "caseSensitive": true,
            "typeValidation": "strict"
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "2b03f228-f10c-43c1-90f8-a2ef397d2e0b",
              "operator": {
                "type": "boolean",
                "operation": "false",
                "singleValue": true
              },
              "leftValue": "={{ $json.isEmpty() }}",
              "rightValue": ""
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "c1164b8f-4497-4763-bb42-7187e9f2f4d2",
      "name": "Process Each Eligible Customer",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        1640,
        -320
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 3
    },
    {
      "id": "8896a776-ed5b-431a-908b-663fa8475c77",
      "name": "Generate Win-Back Offer",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
        2100,
        -300
      ],
      "parameters": {
        "text": "=",
        "messages": {
          "messageValues": [
            {
              "message": "=\n**You are an AI assistant designed to analyze customer data and determine a win-back offer based on specific churn prediction scores and preferences.**\n\n**Input:** You will receive customer data as a JSON object.\n\n**Task:** Analyze the fields `'predicted_churn_score': {{ $json.predicted_churn_score }}` and `'preferred_categories': \"{{ $json.preferred_categories }}\"` in the input JSON. Apply the following rules to determine the appropriate offer details:\n\n**Rules:**\n\n1. If `predicted_churn_score` is greater than or equal to 0.7 and less than or equal to 0.8:\n\n   * Offer Type: `INFORMATIONAL`\n   * Offer Value: `0`\n   * Offer Title: `Special Advantage on Books Just for You`\n   * Offer Details: Create a message encouraging the customer to explore new products in their preferred categories. To make it more specific, select *one* of the preferred categories and include a *typical product type* from that category.\n     Example: `\"Exciting new [product type, e.g., novels] just arrived in your favorite [Preferred Category Name] category! Check out what's new in your other favorite categories too: [List of Other Preferred Categories]!\"`\n\n2. If `predicted_churn_score` is greater than 0.8 and less than or equal to 0.9:\n\n   * Offer Type: `BONUS_POINTS`\n   * Offer Value: `200`\n   * Offer Title: `Special Advantage on Books Just for You`\n   * Offer Details: Create a message offering 200 bonus points for purchases made specifically in the \"Books\" category.\n     Example: `\"Earn 200 bonus points on your next purchase in the Books category!\"`\n\n3. If `predicted_churn_score` is greater than 0.9 and less than or equal to 1.0:\n\n   * Offer Type: `DISCOUNT_PERCENTAGE`\n   * Offer Value: `20`\n   * Offer Title: `Special Advantage on Books Just for You`\n   * Offer Details: Create a message offering a 20% discount on a future purchase specifically in the \"Books\" category.\n     Example: `\"Enjoy a 20% discount on your next purchase in the Books category!\"`\n\n**Output:** Generate a JSON object that includes the determined offer details. The OUTPUT MUST STRICTLY FOLLOW THE STRUCTURE BELOW and INCLUDE ONLY THE JSON OBJECT. Do not add any other text or explanation.\n\n**Output Structure:**\n\n{\n  \"customer_id\": string, // Customer ID from the input data\n  \"action_taken\": \"SENT_WINBACK_OFFER\", // Action taken: win-back offer sent (constant in this example)\n  \"offer_type\": string, // Offer type: INFORMATIONAL, BONUS_POINTS, or DISCOUNT_PERCENTAGE\n  \"offer_value\": number, // Offer value: 0 (informational), 200 (points), or 20 (discount)\n  \"offer_title\": string, // Message title\n  \"offer_details\": string, // Message in Turkish, created based on rules and preferred categories\n  \"communication_channel\": \"email\", // Communication channel (constant in this example)\n  \"timestamp\": string // Current timestamp in ISO 8601 format (e.g., \"YYYY-MM-DDTHH:mm:ssZ\"). Note: In an actual n8n workflow, you may prefer to add the real timestamp using a separate node or expression after the LLM node.\n}\n\n"
            }
          ]
        },
        "promptType": "define",
        "hasOutputParser": true
      },
      "typeVersion": 1.5
    },
    {
      "id": "b89954e9-7689-47e6-bf15-3089f3863ca9",
      "name": "(LLM Model for Offer Generation)",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        2060,
        -120
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.0-pro-exp"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "BhQsoi2WTmDm0fQ4",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "ee485123-32be-447b-80f3-303e3a046207",
      "name": "(Parse Offer JSON)",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        2260,
        -100
      ],
      "parameters": {
        "jsonSchemaExample": "{\n  \"customer_id\": \"CUST_001\",\n  \"action_taken\": \"SENT_WINBACK_OFFER\",\n  \"offer_type\": \"BONUS_POINTS\",\n  \"offer_value\": 200,\n  \"offer_title\": \"Huge Offer!\",\n  \"offer_details\": \"Get 200 bonus points when you shop in the Kitap category!\",\n  \"communication_channel\": \"email\",\n  \"timestamp\": \"2024-06-08T09:05:00Z\"\n}"
      },
      "typeVersion": 1.2
    },
    {
      "id": "005890c2-f77d-4d0d-add2-496642464a9f",
      "name": "Log Sent Offer in System Log",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        2640,
        -220
      ],
      "parameters": {
        "columns": {
          "value": {
            "date": "={{ $json.output.timestamp }}",
            "system_log": "={{ $json.output.action_taken }}",
            "customer_id": "={{ $json.output.customer_id }}"
          },
          "schema": [
            {
              "id": "system_log",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "system_log",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "date",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "date",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "customer_id",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "customer_id",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "system_log"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "appendOrUpdate",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 157558698,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k/edit#gid=157558698",
          "cachedResultName": "SYSTEM_LOG"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k/edit?usp=drivesdk",
          "cachedResultName": "OnurPolat05 N8N  Db"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "VV5AyFvgYkc4TfC7",
          "name": "Onur Drive "
        }
      },
      "typeVersion": 4.5
    },
    {
      "id": "98295978-21f1-420f-8e9c-4014d53ffb16",
      "name": "Send Win-Back Offer via Email",
      "type": "n8n-nodes-base.gmail",
      "position": [
        2880,
        -120
      ],
      "webhookId": "3067948c-c6f7-4c77-a91f-fcdb2e0c8095",
      "parameters": {
        "sendTo": "={{ $('Process Each Eligible Customer').item.json.user_mail }}",
        "message": "={{ $json.output.offer_details }}",
        "options": {},
        "subject": "={{ $json.output.offer_title }}",
        "emailType": "text"
      },
      "credentials": {
        "gmailOAuth2": {
          "id": "epBpgOmwmYErJ4pe",
          "name": "Onur Account"
        }
      },
      "typeVersion": 2.1
    },
    {
      "id": "13095156-a54f-432f-8d10-209ddc30680a",
      "name": "Set 'Not Found' Status",
      "type": "n8n-nodes-base.set",
      "position": [
        1620,
        300
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "e42f6e99-487d-4942-a133-879d62b28fe5",
              "name": "system_log",
              "type": "string",
              "value": "NOT_FOUND"
            },
            {
              "id": "4fe0abc3-e685-4ece-bee2-1ae4f6d3ca92",
              "name": "date",
              "type": "string",
              "value": "={{ $now }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "1f823726-6483-40c1-b184-eac87886ded5",
      "name": "Log 'Not Found' in System Log",
      "type": "n8n-nodes-base.googleSheets",
      "position": [
        1940,
        300
      ],
      "parameters": {
        "columns": {
          "value": {
            "date": "={{ $json.date }}",
            "system_log": "={{ $json.system_log }}"
          },
          "schema": [
            {
              "id": "system_log",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "system_log",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "date",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "date",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "system_log"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "appendOrUpdate",
        "sheetName": {
          "__rl": true,
          "mode": "list",
          "value": 157558698,
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k/edit#gid=157558698",
          "cachedResultName": "SYSTEM_LOG"
        },
        "documentId": {
          "__rl": true,
          "mode": "list",
          "value": "1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k",
          "cachedResultUrl": "https://docs.google.com/spreadsheets/d/1hG2NMi-4fMa7D5qGonCN8bsYVya4L2TOB_8mI4XK-9k/edit?usp=drivesdk",
          "cachedResultName": "OnurPolat05 N8N  Db"
        }
      },
      "credentials": {
        "googleSheetsOAuth2Api": {
          "id": "VV5AyFvgYkc4TfC7",
          "name": "Onur Drive "
        }
      },
      "typeVersion": 4.5
    },
    {
      "id": "c6828c9c-c39f-40b5-9197-1435915d3682",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        160,
        -340
      ],
      "parameters": {
        "width": 380,
        "height": 300,
        "content": "# 00. Daily Start & Fetch Customer Data\n\n**Purpose:** Automatically triggers the workflow **once daily** based on the schedule set in the first node. It then fetches all customer data from the specified Google Sheet ('Customer Data' sheet) to identify potential churn risks for the day."
      },
      "typeVersion": 1
    },
    {
      "id": "71d3f596-1413-4e97-81eb-ec701f15938d",
      "name": "Sticky Note1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1560,
        540
      ],
      "parameters": {
        "color": 3,
        "width": 540,
        "height": 300,
        "content": "# 03. Handle No Eligible Customers\n\n**Purpose:** This path executes if the initial filter finds *no* customers meeting the win-back criteria during the daily check.\n1.  **Set Status:** Sets a variable indicating no eligible customers were found (`system_log = NOT_FOUND`).\n2.  **Log Status:** Records this 'NOT_FOUND' status along with the current timestamp in the 'SYSTEM_LOG' Google Sheet. This helps track when the daily workflow ran but had no one to process."
      },
      "typeVersion": 1
    },
    {
      "id": "0f076e97-7cf0-48b6-8808-db0f1863409e",
      "name": "Sticky Note2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        760,
        -360
      ],
      "parameters": {
        "color": 2,
        "width": 460,
        "height": 280,
        "content": "# 01. Filter & Branch\n\n**Purpose:** Filters the fetched customer data to identify those meeting specific win-back criteria:\n1.  `predicted_churn_score` is greater than 0.7.\n2.  No previous campaign date exists (`created_campaign_date` is empty - *Note: Verify this field's purpose or adjust logic if needed*).\nThen, it checks if any customers passed the filter. The workflow branches based on whether eligible customers were found."
      },
      "typeVersion": 1
    },
    {
      "id": "d3493f09-7eba-4625-98db-83cf649dbbcf",
      "name": "Sticky Note3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1700,
        -760
      ],
      "parameters": {
        "color": 4,
        "width": 600,
        "height": 360,
        "content": "# 02. Generate & Send Win-Back Offer (Loop)\n\n**Purpose:** Processes each eligible customer found in the previous step individually within a loop.\n1.  **Generate Offer (Gemini):** Uses Google Gemini to create a personalized win-back offer (Informational, Bonus Points, or Discount) based on the customer's `predicted_churn_score` and `preferred_categories`. Outputs offer details in JSON format.\n2.  **Log Sent Offer:** Records the successful generation and intent to send the offer (action_taken, timestamp, customer_id) in the 'SYSTEM_LOG' Google Sheet.\n3.  **Send Email (Gmail):** Sends the generated offer details (`offer_title` and `offer_details`) via email to the customer's `user_mail`.\nThe loop continues until all eligible customers are processed."
      },
      "typeVersion": 1
    },
    {
      "id": "2fc53a15-2bdd-48f5-9a74-44a2e028e7e0",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -360,
        -120
      ],
      "parameters": {
        "width": 400,
        "height": 380,
        "content": "# Example Customer Data\n\n\n{\n    \"customer_id\": \"CUST_001\",\n    \"last_purchase_date\": \"2024-01-10T10:00:00Z\",\n    \"purchase_frequency_days\": 90,\n    \"user_mail\":\"example@mail.com\",\n    \"days_since_last_purchase\": 110,\n    \"total_spent_usd\": 55.0,\n    \"preferred_categories\": [\"Kitap\", \"Ofis Malzemeleri\"],\n    \"predicted_churn_score\": 0.85,\n    \"profile_tags\": [\"inactive_long_time\", \"low_spender\"],\n    \"timestamp\": \"2024-06-08T09:00:00Z\"\n}\n"
      },
      "typeVersion": 1
    }
  ],
  "pinData": {},
  "connections": {
    "(Parse Offer JSON)": {
      "ai_outputParser": [
        [
          {
            "node": "Generate Win-Back Offer",
            "type": "ai_outputParser",
            "index": 0
          }
        ]
      ]
    },
    "Set 'Not Found' Status": {
      "main": [
        [
          {
            "node": "Log 'Not Found' in System Log",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Generate Win-Back Offer": {
      "main": [
        [
          {
            "node": "Log Sent Offer in System Log",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Log Sent Offer in System Log": {
      "main": [
        [
          {
            "node": "Send Win-Back Offer via Email",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Send Win-Back Offer via Email": {
      "main": [
        [
          {
            "node": "Process Each Eligible Customer",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Fetch Customer Data from Sheet": {
      "main": [
        [
          {
            "node": "Filter High Churn Risk & No Campaign Customers",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Process Each Eligible Customer": {
      "main": [
        [],
        [
          {
            "node": "Generate Win-Back Offer",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "(LLM Model for Offer Generation)": {
      "ai_languageModel": [
        [
          {
            "node": "Generate Win-Back Offer",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Check if Eligible Customers Found": {
      "main": [
        [
          {
            "node": "Process Each Eligible Customer",
            "type": "main",
            "index": 0
          }
        ],
        [
          {
            "node": "Set 'Not Found' Status",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Scheduled Start: Daily Churn Check": {
      "main": [
        [
          {
            "node": "Fetch Customer Data from Sheet",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Filter High Churn Risk & No Campaign Customers": {
      "main": [
        [
          {
            "node": "Check if Eligible Customers Found",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

Workflow n8n Google Sheets, fidélisation client, reconquête : pour qui est ce workflow ?

Ce workflow s'adresse aux équipes marketing et aux responsables de la fidélisation au sein des PME et grandes entreprises. Il est conçu pour les professionnels ayant une connaissance de base des outils d'automatisation et des données clients, souhaitant optimiser leur processus de gestion des désabonnements.

Workflow n8n Google Sheets, fidélisation client, reconquête : problème résolu

Ce workflow résout le problème de la gestion des désabonnements en permettant aux entreprises d'identifier rapidement les clients à risque et de leur envoyer des offres de reconquête personnalisées. En automatisant ce processus, les utilisateurs éliminent les frustrations liées à la gestion manuelle des données et réduisent le risque de perdre des clients précieux. Grâce à cette approche proactive, les entreprises peuvent améliorer leur taux de rétention et renforcer leur relation avec les clients.

Workflow n8n Google Sheets, fidélisation client, reconquête : étapes du workflow

Étape 1 : Le workflow commence par un déclencheur programmé qui vérifie quotidiennement les données des clients.

  • Étape 1 : Il récupère les informations des clients à partir d'une feuille Google Sheets.
  • Étape 2 : Un filtre est appliqué pour identifier les clients à haut risque de désabonnement qui n'ont pas encore reçu d'offre.
  • Étape 3 : Si des clients éligibles sont trouvés, le workflow les traite un par un.
  • Étape 4 : Une offre de reconquête est générée à l'aide d'un modèle de langage.
  • Étape 5 : L'offre est envoyée par email et enregistrée dans un journal pour un suivi ultérieur.
  • Étape 6 : En cas d'absence de clients éligibles, le système enregistre cette information pour éviter des actions inutiles.

Workflow n8n Google Sheets, fidélisation client, reconquête : guide de personnalisation

Pour personnaliser ce workflow, commencez par ajuster le déclencheur programmé selon vos besoins. Modifiez l'ID du document Google Sheets et le nom de la feuille pour correspondre à votre base de données clients. Vous pouvez également adapter les conditions du filtre pour cibler d'autres segments de clients. Pour l'offre de reconquête, personnalisez le modèle de langage utilisé pour générer des messages qui résonnent avec votre audience. Enfin, assurez-vous de vérifier les paramètres d'envoi d'email pour garantir que les messages atteignent vos clients sans problème.