Implementation Guide: Manage end-to-end customer return and exchange workflows

Hardware Procurement

Epson TM-T88VII Thermal Receipt Printer

iPad 10th Generation (Alternative to Kiosk)

Software Procurement

Prerequisites

• Active e-commerce platform subscription (Shopify Basic or higher, BigCommerce Standard or higher, or WooCommerce with hosting) with API access enabled and admin credentials available
• Payment processor account (Stripe, Shopify Payments, or Square) with refund API access enabled. For Stripe, ensure the account is on a plan that supports programmatic refund creation via API keys.
• Documented return and exchange policy including: eligible return window (e.g., 30 days), condition requirements (unworn, tags attached, etc.), non-returnable item categories, exchange vs. refund rules, restocking fee policy, and fraud thresholds
• Minimum 25 Mbps symmetrical internet connection at each store location (for in-store kiosk deployments). Verify with speed test to cloud provider region (us-east-1 for Zendesk).
• Wi-Fi network with WPA3 or WPA2-Enterprise for kiosk/tablet connectivity, on a separate VLAN from customer Wi-Fi
• DNS access to create CNAME records for branded return portal subdomain (e.g., returns.clientdomain.com)
• SSL certificate for return portal domain (Let's Encrypt or existing wildcard cert)
• Email sending domain with SPF, DKIM, and DMARC configured (required for Klaviyo and Zendesk email delivery)
• Product catalog exported as CSV or accessible via API — needed for training the AI agent on product categories, price tiers, and exchange compatibility
• Historical return data export (last 12 months) from current system — used to establish fraud baselines and common return reason patterns
• Client-designated project stakeholder with authority to approve return policy rules, refund thresholds, and fraud escalation procedures
• For brick-and-mortar: adequate counter or floor space for kiosk placement, available electrical outlet within 6 feet, and ethernet drop or confirmed Wi-Fi coverage at kiosk location
• PCI DSS 4.0.1 self-assessment questionnaire (SAQ) completed or in progress — the MSP will validate that the AI agent deployment does not expand PCI scope beyond current assessment
• Admin access to client's existing POS system (Shopify POS, Square, Lightspeed, or Clover) with API credentials for inventory and order data sync

Installation Steps

...

Step 1: Audit Current Return Process and Document Workflows

Before any technical implementation, conduct a thorough audit of the client's existing return and exchange process. Meet with the client stakeholder and front-line staff to map out every return scenario they handle: standard returns, exchanges (same item/different size, different item), warranty claims, damaged-in-transit claims, gift returns without receipt, and partial order returns. Document each scenario as a workflow with decision points, current handling time, and resolution rates. This becomes the requirements specification for configuring the AI agent.

Step 2: Provision Zendesk Suite Professional and Configure Base Environment

Create the Zendesk Suite Professional instance for the client. Configure the organization, set up agent accounts, configure email forwarding for the support address, enable the web widget for the client's e-commerce site, and set up the initial Help Center with return policy articles that the AI agent will reference.

<script id="ze-snippet" src="https://static.zdassets.com/ekr/snippet.js?key=CLIENT_ZENDESK_KEY"></script>

Step 3: Configure Loop Returns (Shopify) or AfterShip Returns (Multi-Platform)

Install and configure the dedicated returns management platform that provides the branded self-service portal, return policy rules engine, and exchange recommendation logic. This platform handles the business logic of returns while Zendesk AI handles customer communication.

FOR SHOPIFY CLIENTS — Install Loop Returns

returns.clientdomain.com -> portal.loopreturns.com

FOR NON-SHOPIFY CLIENTS — Install AfterShip Returns

returns.clientdomain.com -> returns.aftership.com

Step 4: Integrate Returns Platform with Zendesk

Connect Loop Returns (or AfterShip) with Zendesk so that return requests, status updates, and customer data flow bidirectionally. This allows the AI agent to see return context within the Zendesk ticket and take actions in the returns platform.

FOR LOOP RETURNS + ZENDESK

FOR AFTERSHIP RETURNS + ZENDESK

Add the following custom fields:

• 'Return RMA Number' (text)
• 'Return Status' (dropdown: Requested, Approved, Label Sent, In Transit, Received, Refunded, Exchanged, Denied)
• 'Return Reason' (dropdown: Wrong Size, Defective, Changed Mind, Not As Described, etc.)
• 'Original Order Number' (text)
• 'Return Type' (dropdown: Refund, Exchange, Store Credit)
• 'Fraud Risk Score' (numeric, 0-100)

Step 5: Configure Shipping Label Generation via EasyPost API

Set up EasyPost as the multi-carrier shipping API for generating prepaid return labels. Configure carrier accounts, set default shipping options for returns, and create the webhook endpoint that will be called by the AI agent workflow.

curl -X POST https://api.easypost.com/v2/shipments \
  -u ep_test_xxxxxxxxxxxx: \
  -H 'Content-Type: application/json' \
  -d '{
    "shipment": {
      "from_address": {
        "name": "Customer Name",
        "street1": "123 Customer St",
        "city": "Portland",
        "state": "OR",
        "zip": "97201",
        "country": "US"
      },
      "to_address": {
        "company": "Client Returns Center",
        "street1": "456 Warehouse Ave",
        "city": "Client City",
        "state": "CA",
        "zip": "90001",
        "country": "US"
      },
      "parcel": {
        "length": 12,
        "width": 10,
        "height": 6,
        "weight": 32
      }
    }
  }'

curl -X POST https://api.easypost.com/v2/shipments/{shipment_id}/buy \
  -u ep_test_xxxxxxxxxxxx: \
  -H 'Content-Type: application/json' \
  -d '{"rate": {"id": "rate_xxxx"}}'

Step 6: Set Up n8n Workflow Automation Hub

Deploy n8n as the middleware integration layer that connects Zendesk, the returns platform, EasyPost, the e-commerce platform API, and the payment processor. n8n handles complex multi-step workflows that go beyond native Zendesk automation, including refund processing, inventory updates, and fraud scoring.

Option A: n8n Cloud Setup

Option B: Self-Hosted n8n on Docker

sudo apt update && sudo apt install -y docker.io docker-compose

mkdir -p /opt/n8n && cd /opt/n8n

cat > docker-compose.yml << 'EOF'
version: '3.8'
services:
  n8n:
    image: n8nio/n8n:latest
    restart: always
    ports:
      - '5678:5678'
    environment:
      - N8N_BASIC_AUTH_ACTIVE=true
      - N8N_BASIC_AUTH_USER=mspadmin
      - N8N_BASIC_AUTH_PASSWORD=CHANGE_THIS_SECURE_PASSWORD
      - N8N_HOST=n8n.clientdomain.com
      - N8N_PROTOCOL=https
      - WEBHOOK_URL=https://n8n.clientdomain.com/
      - N8N_ENCRYPTION_KEY=GENERATE_A_RANDOM_32CHAR_KEY
      - DB_TYPE=postgresdb
      - DB_POSTGRESDB_HOST=postgres
      - DB_POSTGRESDB_DATABASE=n8n
      - DB_POSTGRESDB_USER=n8n
      - DB_POSTGRESDB_PASSWORD=CHANGE_THIS_DB_PASSWORD
    volumes:
      - n8n_data:/home/node/.n8n
    depends_on:
      - postgres
  postgres:
    image: postgres:15-alpine
    restart: always
    environment:
      - POSTGRES_DB=n8n
      - POSTGRES_USER=n8n
      - POSTGRES_PASSWORD=CHANGE_THIS_DB_PASSWORD
    volumes:
      - postgres_data:/var/lib/postgresql/data
volumes:
  n8n_data:
  postgres_data:
EOF

docker-compose up -d

sudo apt install -y nginx certbot python3-certbot-nginx

cat > /etc/nginx/sites-available/n8n << 'EOF'
server {
    server_name n8n.clientdomain.com;
    location / {
        proxy_pass http://localhost:5678;
        proxy_http_version 1.1;
        proxy_set_header Upgrade $http_upgrade;
        proxy_set_header Connection 'upgrade';
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
        chunked_transfer_encoding off;
        proxy_buffering off;
        proxy_cache off;
    }
}
EOF

sudo ln -s /etc/nginx/sites-available/n8n /etc/nginx/sites-enabled/
sudo certbot --nginx -d n8n.clientdomain.com
sudo systemctl restart nginx

Step 7: Configure n8n Credentials and Integration Connections

Set up all the API credentials and authentication connections in n8n that the automation workflows will use. This centralizes all secrets management and allows workflows to securely access external services.

• ZENDESK CREDENTIALS — Type: Zendesk API | Subdomain: clientname | Email: integration-bot@clientdomain.com | API Token: Generate at Admin Center > Apps & Integrations > APIs > Zendesk API > Add API token
• SHOPIFY CREDENTIALS — Type: Shopify API (or Shopify Access Token) | Shop subdomain: clientstore | Access Token: Create a Custom App in Shopify Admin > Settings > Apps and sales channels > Develop apps | Required scopes: read_orders, write_orders, read_products, write_products, read_inventory, write_inventory, read_returns, write_returns, read_customers, read_fulfillments, write_returns
• EASYPOST CREDENTIALS — Type: HTTP Header Auth | Header Name: Authorization | Header Value: Basic {base64encode(ep_live_xxxxxxxxxxxx:)}
• OPENAI CREDENTIALS — Type: OpenAI API | API Key: sk-xxxxxxxxxxxx | Organization ID: org-xxxxxxxxxxxx
• STRIPE CREDENTIALS — Type: Stripe API | Secret Key: sk_live_xxxxxxxxxxxx
• KLAVIYO CREDENTIALS — Type: HTTP Header Auth | Header Name: Authorization | Header Value: Klaviyo-API-Key pk_xxxxxxxxxxxx
• LOOP RETURNS CREDENTIALS (if using Loop) — Type: HTTP Header Auth | Header Name: X-Authorization | Header Value: {Loop API key from Loop Dashboard > Settings > API}

Step 8: Build Core Return Processing Workflow in n8n

Create the primary n8n workflow that orchestrates the entire return lifecycle. This workflow is triggered by Zendesk webhooks when a new return request arrives, and it handles eligibility checking, fraud scoring, approval routing, label generation, and refund processing.

Name: Return Processing Webhook
Endpoint URL: https://n8n.clientdomain.com/webhook/return-request
Request method: POST
Request format: JSON
Authentication: API Key (set a shared secret)

# fires webhook on new return request tickets

Name: New Return Request - Fire Webhook
Conditions (ALL):
  - Ticket tag contains 'return_request'
  - Ticket status is New
Actions:
  - Notify active webhook: Return Processing Webhook
  - Body: { "ticket_id": "{{ticket.id}}", "requester_email": "{{ticket.requester.email}}",
           "order_number": "{{ticket.ticket_field_ORDER_NUMBER_ID}}",
           "return_reason": "{{ticket.ticket_field_RETURN_REASON_ID}}",
           "return_type": "{{ticket.ticket_field_RETURN_TYPE_ID}}" }

Step 9: Configure Zendesk AI Agent for Return Conversations

Set up the Zendesk AI Agent (formerly Zendesk Bot) to handle the customer-facing conversation for returns and exchanges. Configure intents, conversation flows, knowledge base connections, and the handoff to n8n for backend processing. This is the autonomous agent that customers interact with.

1. Enable AI Agents

2. Configure Knowledge Base Connection

3. Create Return Intent

4. Build Conversation Flow for Return Intent

Flow Step 1: Collect Order Number

• Type: Ask a question
• Question: 'I'd be happy to help with your return! Could you please provide your order number? It starts with # and you can find it in your confirmation email.'
• Save to variable: {{order_number}}
• Validation: Regex ^#?\d{4,10}$

Flow Step 2: Collect Return Reason

• Type: Present options
• Message: 'Thanks! What is the reason for your return?'
• Options: Wrong size/fit | Defective/damaged | Not as described | Changed my mind | Better price elsewhere | Ordered wrong item | Gift return
• Save to variable: {{return_reason}}

Flow Step 3: Collect Return Type Preference

• Type: Present options
• Message: 'Would you like a refund to your original payment method, an exchange for a different item/size, or store credit?'
• Options: Refund | Exchange | Store Credit
• Save to variable: {{return_type}}

Flow Step 4: API Call to Check Eligibility

• Type: Make API call
• Save response to: {{eligibility_result}}

POST https://n8n.clientdomain.com/webhook/check-eligibility

{
  "order_number": "{{order_number}}",
  "return_reason": "{{return_reason}}",
  "requester_email": "{{visitor.email}}"
}

Flow Step 5: Branch on Eligibility

• Type: Condition
• If {{eligibility_result.eligible}} equals 'true': Go to Step 6
• If {{eligibility_result.eligible}} equals 'false': Go to Step 8
• If {{eligibility_result.eligible}} equals 'review': Go to Step 9

Flow Step 6: Confirm Return Details (Eligible)

• Type: Send message
• Message: 'Great news! Your order {{order_number}} ({{eligibility_result.product_name}}) is eligible for return. Here are the details:\n\n• Return window: {{eligibility_result.days_remaining}} days remaining\n• Refund amount: {{eligibility_result.refund_amount}}\n\nShall I proceed with your {{return_type}}?'

Flow Step 7: Process Approved Return

• Type: Make API call (fires the main n8n workflow)
• After success, send message: 'Your return has been initiated! {{process_result.message}}'

POST https://n8n.clientdomain.com/webhook/return-request

{
  "order_number": "{{order_number}}",
  "return_reason": "{{return_reason}}",
  "return_type": "{{return_type}}",
  "requester_email": "{{visitor.email}}",
  "approved": true
}

Flow Step 8: Ineligible Return Message

• Type: Send message
• Message: 'I'm sorry, but your order {{order_number}} is not eligible for return. Reason: {{eligibility_result.denial_reason}}. If you believe this is an error, I can connect you with our returns team for further review.'
• Then: Transfer to human agent (Group: Returns Team)

Flow Step 9: Escalate for Review

• Type: Transfer to agent
• Group: Returns Team
• Message: 'This return requires manual review. I'm connecting you with a returns specialist who can help.'

Step 10: Configure Fraud Detection Rules and Risk Scoring

Set up the fraud detection layer that assigns a risk score (0–100) to each return request. The score is calculated based on customer return history, order value, return reason patterns, and known fraud indicators. Returns above the threshold are automatically escalated to human review.

Step 11: Deploy In-Store Return Kiosk (Brick-and-Mortar Only)

For clients with physical store locations, set up the self-service return kiosk hardware. The kiosk runs a web application that connects to the same backend systems as the online return portal, providing a consistent omnichannel return experience.

@echo off
start chrome.exe --kiosk --disable-translate --disable-features=TranslateUI --noerrorsdialogs --disable-infobars --disable-session-crashed-bubble https://returns.clientdomain.com/kiosk

Step 12: Configure Klaviyo Email/SMS Notifications for Return Status Updates

Set up automated customer communications that fire at each stage of the return lifecycle. Customers receive real-time updates via email and optional SMS when their return is approved, a label is generated, the package is in transit, the return is received at the warehouse, and the refund is processed.

Example n8n HTTP Request node to fire a Klaviyo event:

# fired from n8n HTTP Request node for each return lifecycle event

POST https://a.klaviyo.com/api/events/
Headers: { "Authorization": "Klaviyo-API-Key pk_xxxx", "revision": "2024-10-15" }

{
  "data": {
    "type": "event",
    "attributes": {
      "metric": { "data": { "type": "metric", "attributes": { "name": "Return Approved" } } },
      "profile": { "data": { "type": "profile", "attributes": { "email": "customer@email.com" } } },
      "properties": {
        "order_number": "#12345",
        "return_rma": "RMA-67890",
        "refund_amount": "$49.99",
        "return_type": "Refund",
        "expected_refund_date": "2025-08-15"
      }
    }
  }
}

Step 13: Build Analytics Dashboard and Reporting

Create a return analytics dashboard that gives the client visibility into return volumes, reasons, fraud rates, AI agent resolution rates, refund amounts, and exchange conversion rates. This data drives ongoing optimization and demonstrates ROI.

Option A: Key Reports to Build in Zendesk Explore

Option B: Google Looker Studio via n8n Bridge

Step 14: Perform Security Hardening and PCI Compliance Validation

Validate that the entire return/exchange AI agent deployment meets PCI DSS 4.0.1 requirements and privacy regulations. Ensure no cardholder data is stored or processed by the AI agent, all communications are encrypted, and audit trails are complete.

1. Verify TLS Everywhere

Test all endpoints with SSL Labs: https://www.ssllabs.com/ssltest/. All must score A or A+, TLS 1.2 minimum.

• returns.clientdomain.com (return portal)
• n8n.clientdomain.com (automation hub)
• clientname.zendesk.com (support portal)

2. Verify No Cardholder Data in AI Agent

grep -r 'card_number\|cvv\|expiry\|credit_card' /opt/n8n/

3. Configure Zendesk Data Redaction

4. Set Data Retention Policies

5. Enable Audit Logging

6. Verify AI Transparency

7. Document Compliance

• Data flow diagram showing all systems and data types
• PCI DSS SAQ-A validation (no cardholder data stored)
• Privacy impact assessment for AI-processed customer data
• Human escalation path documentation

Step 15: Soft Launch and Gradual Rollout

Launch the AI return agent to a subset of customers first, monitor performance, fine-tune, then gradually expand to full traffic. This reduces risk and allows calibration of the AI agent's responses, fraud thresholds, and workflow automation.

Custom AI Components

Return Eligibility Checker

Type: workflow An n8n webhook-triggered workflow that receives a return request (order number, customer email, return reason), queries the Shopify Orders API to validate the order, checks return window eligibility, calculates the refund amount, and returns an eligibility determination. This is called by the Zendesk AI Agent during the conversation flow.

Implementation

n8n Workflow Definition (import as JSON):

{
  "name": "Return Eligibility Checker",
  "nodes": [
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "check-eligibility",
        "responseMode": "responseNode",
        "options": {}
      },
      "name": "Webhook - Check Eligibility",
      "type": "n8n-nodes-base.webhook",
      "position": [250, 300]
    },
    {
      "parameters": {
        "method": "GET",
        "url": "=https://{{$env.SHOPIFY_STORE}}.myshopify.com/admin/api/2025-07/orders.json?name={{encodeURIComponent($json.body.order_number)}}&status=any",
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth",
        "options": {}
      },
      "name": "Shopify - Lookup Order",
      "type": "n8n-nodes-base.httpRequest",
      "position": [470, 300]
    },
    {
      "parameters": {
        "conditions": {
          "boolean": [{
            "value1": "={{$json.orders.length > 0}}",
            "value2": true
          }]
        }
      },
      "name": "IF - Order Found",
      "type": "n8n-nodes-base.if",
      "position": [690, 300]
    },
    {
      "parameters": {
        "jsCode": "const order = $input.first().json.orders[0];\nconst requestEmail = $('Webhook - Check Eligibility').first().json.body.requester_email;\nconst returnReason = $('Webhook - Check Eligibility').first().json.body.return_reason;\n\n// Verify customer email matches order\nconst emailMatch = order.email && order.email.toLowerCase() === requestEmail.toLowerCase();\nif (!emailMatch) {\n  return [{ json: { eligible: 'false', denial_reason: 'Email does not match order records. Please use the email address associated with your order.' } }];\n}\n\n// Check fulfillment status\nconst fulfilled = order.fulfillment_status === 'fulfilled';\nif (!fulfilled) {\n  return [{ json: { eligible: 'false', denial_reason: 'This order has not been delivered yet. Please wait until you receive your items.' } }];\n}\n\n// Calculate days since delivery\nconst fulfillments = order.fulfillments || [];\nlet deliveryDate = null;\nfor (const f of fulfillments) {\n  if (f.status === 'success' && f.updated_at) {\n    const d = new Date(f.updated_at);\n    if (!deliveryDate || d > deliveryDate) deliveryDate = d;\n  }\n}\nif (!deliveryDate) {\n  deliveryDate = new Date(order.closed_at || order.created_at);\n}\n\nconst now = new Date();\nconst daysSinceDelivery = Math.floor((now - deliveryDate) / (1000 * 60 * 60 * 24));\nconst returnWindowDays = 30; // Configurable per client policy\nconst daysRemaining = returnWindowDays - daysSinceDelivery;\n\nif (daysRemaining < 0) {\n  return [{ json: { eligible: 'false', denial_reason: `Your return window expired ${Math.abs(daysRemaining)} days ago. Our policy allows returns within ${returnWindowDays} days of delivery.` } }];\n}\n\n// Check for non-returnable tags\nconst nonReturnableTags = ['final-sale', 'non-returnable', 'clearance'];\nconst orderTags = (order.tags || '').toLowerCase().split(',').map(t => t.trim());\nconst isNonReturnable = orderTags.some(t => nonReturnableTags.includes(t));\nif (isNonReturnable) {\n  return [{ json: { eligible: 'false', denial_reason: 'This item was purchased as a final sale and is not eligible for return.' } }];\n}\n\n// Check if already returned\nif (order.refunds && order.refunds.length > 0) {\n  const totalRefunded = order.refunds.reduce((sum, r) => {\n    return sum + r.refund_line_items.reduce((s, li) => s + parseFloat(li.subtotal || 0), 0);\n  }, 0);\n  const orderTotal = parseFloat(order.total_price);\n  if (totalRefunded >= orderTotal * 0.95) {\n    return [{ json: { eligible: 'false', denial_reason: 'This order has already been fully refunded.' } }];\n  }\n}\n\n// Calculate refund amount\nconst lineItems = order.line_items.map(li => ({ name: li.name, price: li.price, quantity: li.quantity, sku: li.sku }));\nconst refundAmount = parseFloat(order.total_price) - parseFloat(order.total_tax || 0);\nconst productName = lineItems.map(li => li.name).join(', ');\n\n// Determine if review needed (medium-risk indicators)\nlet needsReview = false;\nif (refundAmount > 200) needsReview = true; // High-value returns\nif (returnReason === 'Not as described' && refundAmount > 100) needsReview = true;\n\nreturn [{\n  json: {\n    eligible: needsReview ? 'review' : 'true',\n    order_id: order.id,\n    order_number: order.name,\n    product_name: productName,\n    line_items: lineItems,\n    refund_amount: '$' + refundAmount.toFixed(2),\n    refund_amount_raw: refundAmount,\n    days_remaining: daysRemaining,\n    delivery_date: deliveryDate.toISOString().split('T')[0],\n    customer_email: order.email,\n    customer_name: (order.customer?.first_name || '') + ' ' + (order.customer?.last_name || ''),\n    customer_id: order.customer?.id,\n    order_tags: orderTags,\n    return_reason: returnReason,\n    currency: order.currency\n  }\n}];"
      },
      "name": "Code - Eligibility Logic",
      "type": "n8n-nodes-base.code",
      "position": [910, 250]
    },
    {
      "parameters": {
        "respondWith": "json",
        "responseBody": "={{ $json }}"
      },
      "name": "Respond - Eligibility Result",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [1130, 250]
    },
    {
      "parameters": {
        "respondWith": "json",
        "responseBody": "={ \"eligible\": \"false\", \"denial_reason\": \"We could not find an order with that number. Please double-check and try again.\" }"
      },
      "name": "Respond - Order Not Found",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [910, 450]
    }
  ],
  "connections": {
    "Webhook - Check Eligibility": { "main": [[{ "node": "Shopify - Lookup Order" }]] },
    "Shopify - Lookup Order": { "main": [[{ "node": "IF - Order Found" }]] },
    "IF - Order Found": { "main": [[{ "node": "Code - Eligibility Logic" }], [{ "node": "Respond - Order Not Found" }]] },
    "Code - Eligibility Logic": { "main": [[{ "node": "Respond - Eligibility Result" }]] }
  }
}

Key configuration points to customize per client:

• returnWindowDays: Adjust from 30 to match client policy (14, 30, 60, 90 days)
• nonReturnableTags: Add client-specific Shopify product tags that indicate non-returnable items
• High-value threshold for review: Adjust the $200 threshold based on client's average order value
• Tax handling: The current logic excludes tax from refund calculation; adjust if client refunds tax

Fraud Risk Scoring Engine

Type: skill A JavaScript function node in n8n that calculates a fraud risk score (0–100) for each return request based on multiple signals: customer return history, order age, return reason patterns, email domain reputation, order value relative to customer lifetime value, and velocity of recent returns. Scores above 70 trigger human review; below 30 auto-approve.

Implementation

// Fraud Risk Scoring Engine for Return Requests
// Score range: 0 (no risk) to 100 (highest risk)
// Thresholds: <30 = auto-approve, 30-70 = standard processing, >70 = human review required

const eligibilityData = $input.first().json;
const customerEmail = eligibilityData.customer_email;
const customerId = eligibilityData.customer_id;
const orderValue = eligibilityData.refund_amount_raw;
const returnReason = eligibilityData.return_reason;

let score = 0;
const factors = [];

// --- FACTOR 1: Customer Return History (weight: 0-25 points) ---
// Query Shopify for customer's order and refund history
try {
  const customerOrders = await this.helpers.httpRequestWithAuthentication.call(
    this, 'shopifyApi', {
      method: 'GET',
      url: `https://${process.env.SHOPIFY_STORE}.myshopify.com/admin/api/2025-07/customers/${customerId}/orders.json?status=any&limit=50`,
    }
  );
  
  const orders = customerOrders.orders || [];
  const totalOrders = orders.length;
  const ordersWithRefunds = orders.filter(o => o.refunds && o.refunds.length > 0).length;
  const returnRate = totalOrders > 0 ? ordersWithRefunds / totalOrders : 0;
  
  if (returnRate > 0.5 && totalOrders >= 3) {
    score += 20;
    factors.push(`High return rate: ${(returnRate * 100).toFixed(0)}% of ${totalOrders} orders returned`);
  } else if (returnRate > 0.3 && totalOrders >= 5) {
    score += 12;
    factors.push(`Elevated return rate: ${(returnRate * 100).toFixed(0)}% of ${totalOrders} orders returned`);
  } else if (returnRate > 0.2) {
    score += 5;
    factors.push(`Moderate return rate: ${(returnRate * 100).toFixed(0)}%`);
  }
  
  // Check for return velocity (multiple returns in last 30 days)
  const thirtyDaysAgo = new Date(Date.now() - 30 * 24 * 60 * 60 * 1000);
  const recentReturns = orders.filter(o => 
    o.refunds && o.refunds.length > 0 && 
    new Date(o.refunds[0].created_at) > thirtyDaysAgo
  ).length;
  
  if (recentReturns >= 3) {
    score += 25;
    factors.push(`HIGH VELOCITY: ${recentReturns} returns in last 30 days`);
  } else if (recentReturns >= 2) {
    score += 10;
    factors.push(`${recentReturns} returns in last 30 days`);
  }
  
  // New customer with first-order return
  if (totalOrders === 1) {
    score += 8;
    factors.push('First-order return (new customer)');
  }
  
} catch (err) {
  factors.push('Could not retrieve customer history: ' + err.message);
  score += 5; // Small penalty for unknown history
}

// --- FACTOR 2: Order Value Risk (weight: 0-15 points) ---
if (orderValue > 500) {
  score += 15;
  factors.push(`Very high-value return: $${orderValue.toFixed(2)}`);
} else if (orderValue > 200) {
  score += 8;
  factors.push(`High-value return: $${orderValue.toFixed(2)}`);
} else if (orderValue > 100) {
  score += 3;
  factors.push(`Moderate-value return: $${orderValue.toFixed(2)}`);
}

// --- FACTOR 3: Return Reason Patterns (weight: 0-15 points) ---
const highRiskReasons = ['Not as described', 'Better price elsewhere'];
const medRiskReasons = ['Changed my mind'];
const lowRiskReasons = ['Wrong size/fit', 'Defective/damaged', 'Ordered wrong item', 'Gift return'];

if (highRiskReasons.includes(returnReason)) {
  score += 10;
  factors.push(`Higher-risk return reason: ${returnReason}`);
} else if (medRiskReasons.includes(returnReason)) {
  score += 5;
  factors.push(`Medium-risk return reason: ${returnReason}`);
}

// --- FACTOR 4: Email Domain Risk (weight: 0-10 points) ---
const emailDomain = customerEmail.split('@')[1]?.toLowerCase() || '';
const disposableEmailDomains = ['tempmail.com', 'guerrillamail.com', 'throwaway.email', 'yopmail.com',
  'mailinator.com', 'sharklasers.com', 'trashmail.com', 'temp-mail.org', '10minutemail.com'];

if (disposableEmailDomains.includes(emailDomain)) {
  score += 10;
  factors.push(`Disposable email domain: ${emailDomain}`);
}

// --- FACTOR 5: Timing Indicators (weight: 0-10 points) ---
const daysRemaining = eligibilityData.days_remaining;
if (daysRemaining <= 2) {
  score += 8;
  factors.push(`Last-minute return: only ${daysRemaining} days remaining in window`);
} else if (daysRemaining <= 5) {
  score += 3;
  factors.push(`Late return: ${daysRemaining} days remaining`);
}

// Cap score at 100
score = Math.min(score, 100);

// Determine action
let action;
if (score >= 70) {
  action = 'ESCALATE_TO_HUMAN';
} else if (score >= 30) {
  action = 'STANDARD_PROCESSING';
} else {
  action = 'AUTO_APPROVE';
}

return [{
  json: {
    ...eligibilityData,
    fraud_score: score,
    fraud_action: action,
    fraud_factors: factors,
    fraud_assessed_at: new Date().toISOString()
  }
}];

Exchange Recommendation Agent

Type: agent An AI-powered component that, when a customer selects 'Exchange' as their return type, uses OpenAI GPT-4.1 to analyze the return reason, original product, and available inventory to recommend the best exchange options. For 'wrong size' returns, it suggests the correct size. For 'not as described' returns, it suggests alternative products. This increases exchange conversion rates and retains revenue.

Implementation

# Get Product Details: retrieves full product data including all variants
# and inventory levels

GET https://{{$env.SHOPIFY_STORE}}.myshopify.com/admin/api/2025-07/products/{{$json.product_id}}.json

# Get Similar Products: fetches products in the same collection for cross-
# sell recommendations

GET https://{{$env.SHOPIFY_STORE}}.myshopify.com/admin/api/2025-07/products.json?collection_id={{$json.collection_id}}&limit=10

# Generate Recommendation: GPT-4.1 node configuration including system
# prompt and user message template

Model: gpt-4.1
Temperature: 0.3
Max tokens: 500

System prompt:
You are a helpful retail exchange recommendation assistant for {{CLIENT_STORE_NAME}}. 
Your goal is to help customers find the perfect replacement product when they are making an exchange.

RULES:
- Always recommend in-stock items only
- For size issues, use the size chart data to recommend the correct size
- For style/preference issues, suggest 2-3 alternatives from the same collection
- Include the price difference (if any) and note if the customer will receive a credit or owe additional payment
- Be warm, helpful, and concise
- Format recommendations as a numbered list with product name, size/variant, price, and why it's a good fit
- Never recommend items that are final sale or non-exchangeable

User message template:
Customer is returning: {{product_name}} (Size: {{variant_title}}, Price: {{original_price}})
Return reason: {{return_reason}}
Customer's note: {{customer_note}}

Available variants of the same product (in stock):
{{#each available_variants}}
- {{this.title}}: ${{this.price}} ({{this.inventory_quantity}} in stock)
{{/each}}

Similar products in the same collection (in stock):
{{#each similar_products}}
- {{this.title}}: ${{this.price}} ({{this.inventory_quantity}} in stock)
{{/each}}

Please recommend the best exchange option(s) for this customer.

const aiRecommendation = $input.first().json.message.content;
const originalPrice = $('Eligibility Data').first().json.refund_amount_raw;

return [{
  json: {
    exchange_recommendations: aiRecommendation,
    original_price: originalPrice,
    message: `Great choice to exchange! Here are my recommendations based on your return reason:\n\n${aiRecommendation}\n\nWould you like to proceed with any of these options? If there's a price difference, it will be adjusted automatically.`
  }
}];

Refund Processing Workflow

Type: workflow An n8n workflow triggered after a return is approved (either auto-approved by low fraud score or manually approved by staff). It creates the refund via the Shopify Returns API (2025-07), generates the return shipping label via EasyPost, updates the Zendesk ticket with all details, fires Klaviyo notification events, and updates inventory.

Implementation:

n8n Workflow — 'Process Approved Return':

• Trigger: Webhook POST to /webhook/return-request with approved:true

Node sequence:

Node 3 — Shopify - Create Return: HTTP Request body:

POST https://{{$env.SHOPIFY_STORE}}.myshopify.com/admin/api/2025-07/orders/{{$json.body.order_id}}/returns.json

{
  "return": {
    "return_line_items": [
      {
        "fulfillment_line_item_id": "{{$json.body.fulfillment_line_item_id}}",
        "quantity": 1,
        "return_reason": "{{$json.body.return_reason}}",
        "return_reason_note": "Processed by AI Return Agent"
      }
    ],
    "notify_customer": false
  }
}

Node 4 — EasyPost - Generate Return Label: HTTP Request body:

POST https://api.easypost.com/v2/shipments

{
  "shipment": {
    "from_address": {
      "name": "{{$json.body.customer_name}}",
      "street1": "{{$json.body.customer_address_line1}}",
      "city": "{{$json.body.customer_city}}",
      "state": "{{$json.body.customer_state}}",
      "zip": "{{$json.body.customer_zip}}",
      "country": "US"
    },
    "to_address": {
      "company": "{{$env.CLIENT_COMPANY_NAME}}",
      "street1": "{{$env.RETURNS_WAREHOUSE_ADDRESS}}",
      "city": "{{$env.RETURNS_WAREHOUSE_CITY}}",
      "state": "{{$env.RETURNS_WAREHOUSE_STATE}}",
      "zip": "{{$env.RETURNS_WAREHOUSE_ZIP}}",
      "country": "US"
    },
    "parcel": {
      "predefined_package": "USPS_MediumFlatRateBox",
      "weight": 32
    }
  }
}

Node 5 — EasyPost - Buy Cheapest Rate: HTTP Request body:

# Buy Cheapest Rate payload (rates pre-sorted by price; rates[0] is
# cheapest)

POST https://api.easypost.com/v2/shipments/{{$json.id}}/buy

{"rate": {"id": "{{$json.rates[0].id}}"}}

Node 7 — Klaviyo - Fire Return Approved Event: HTTP Request body:

POST https://a.klaviyo.com/api/events/
Headers:
  Authorization: Klaviyo-API-Key {{$env.KLAVIYO_API_KEY}}
  revision: 2024-10-15

{
  "data": {
    "type": "event",
    "attributes": {
      "metric": {"data": {"type": "metric", "attributes": {"name": "Return Approved"}}},
      "profile": {"data": {"type": "profile", "attributes": {"email": "{{customer_email}}"}}},
      "properties": {
        "order_number": "{{order_number}}",
        "return_rma": "{{rma_number}}",
        "refund_amount": "{{refund_amount}}",
        "return_label_url": "{{label_url}}",
        "tracking_number": "{{tracking_number}}",
        "carrier": "{{carrier}}"
      }
    }
  }
}

Node 8 — Respond to Webhook: Response body:

{"success": true, "message": "Your return has been approved! A prepaid return shipping label has been emailed to you at {{customer_email}}. RMA: {{rma_number}}. Please ship within 14 days."}

Environment Variables Required

• SHOPIFY_STORE
• CLIENT_COMPANY_NAME
• RETURNS_WAREHOUSE_ADDRESS
• RETURNS_WAREHOUSE_CITY
• RETURNS_WAREHOUSE_STATE
• RETURNS_WAREHOUSE_ZIP
• KLAVIYO_API_KEY

Return Policy Knowledge Prompt

Type: prompt The system prompt template used to configure the Zendesk AI Agent's persona and return policy knowledge. This prompt defines how the AI agent communicates with customers, what policies it enforces, and when it should escalate to a human. It is configured in Zendesk Admin Center > AI agents > Persona.

Implementation

You are a friendly, professional returns and exchange assistant for {{STORE_NAME}}. Your name is {{AGENT_NAME}} (e.g., 'Alex'). You help customers process returns, exchanges, and refunds quickly and easily.

CORE IDENTITY:
- You are an AI assistant. When asked, always acknowledge you are an AI.
- You are warm, empathetic, and solution-oriented.
- You use a conversational but professional tone.
- You never argue with customers or question their reasons for returning.
- You always look for ways to retain the customer (suggest exchanges before refunds).

RETURN POLICY (customize per client):
- Standard return window: {{RETURN_WINDOW}} days from delivery date
- Items must be in original condition: unworn/unused, tags attached, in original packaging
- Non-returnable categories: {{NON_RETURNABLE_ITEMS}} (e.g., underwear, swimwear, personalized items, gift cards, final sale items)
- Restocking fee: {{RESTOCKING_FEE}} (e.g., 'None' or '15% for non-defective returns')
- Return shipping: {{RETURN_SHIPPING_POLICY}} (e.g., 'Free prepaid label provided' or 'Customer pays return shipping')
- Refund method: Original payment method within {{REFUND_TIMELINE}} business days of receiving the return
- Exchange policy: {{EXCHANGE_POLICY}} (e.g., 'Free exchanges for different size/color. $5 bonus credit when choosing exchange over refund.')
- International returns: {{INTERNATIONAL_POLICY}} (e.g., 'International customers are responsible for return shipping costs')

CONVERSATION FLOW:
1. Greet the customer warmly
2. Ask for their order number
3. Ask for the reason for the return
4. Check eligibility (via API call — this happens automatically)
5. If eligible:
   a. If reason is size-related, proactively suggest an exchange with correct size
   b. Present options: Refund, Exchange, or Store Credit
   c. Highlight any exchange incentives (bonus credit, free shipping on exchange)
   d. Process the selected option
   e. Confirm details and provide next steps
6. If not eligible, explain why clearly and offer to connect with a human agent
7. If uncertain or high-value, offer to escalate to the returns team

ESCALATION RULES (ALWAYS escalate in these situations):
- Customer is upset, frustrated, or uses profanity
- Customer explicitly requests a human agent
- Return involves a warranty claim or product safety issue
- Order value exceeds ${{HIGH_VALUE_THRESHOLD}} (e.g., $500)
- Customer disputes the return policy or threatens legal action
- The system cannot find the order or verify the customer
- Any situation you are not confident handling

THINGS YOU MUST NEVER DO:
- Never share other customers' information
- Never make promises about refund timing that exceed the stated policy
- Never process a return for a non-returnable item without escalating
- Never ask for or reference credit card numbers (use 'original payment method' instead)
- Never blame the customer for the return
- Never make up tracking numbers or RMA numbers — only share what the system provides
- Never discuss internal fraud scoring or risk assessments with customers

RESPONSE FORMAT:
- Keep responses concise (2-4 sentences per message)
- Use bullet points for listing steps or options
- Include relevant details (order number, product name, refund amount) when confirming
- End each message with a clear next step or question

Return Webhook Receiver for Shopify

Type: integration

A Shopify webhook subscription that listens for return-related events (returns/request, returns/approve, returns/decline, refunds/create) and forwards them to n8n for processing. This enables real-time updates when warehouse staff process returns in Shopify admin, keeping the Zendesk ticket and Klaviyo notifications in sync.

Implementation

Setup via Shopify Admin API (run these commands once during deployment). Replace SHOPIFY_STORE and ACCESS_TOKEN with actual values.

curl -X POST "https://${SHOPIFY_STORE}.myshopify.com/admin/api/2025-07/webhooks.json" \
  -H "X-Shopify-Access-Token: ${ACCESS_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "webhook": {
      "topic": "returns/request",
      "address": "https://n8n.clientdomain.com/webhook/shopify-return-event",
      "format": "json"
    }
  }'

curl -X POST "https://${SHOPIFY_STORE}.myshopify.com/admin/api/2025-07/webhooks.json" \
  -H "X-Shopify-Access-Token: ${ACCESS_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "webhook": {
      "topic": "returns/approve",
      "address": "https://n8n.clientdomain.com/webhook/shopify-return-event",
      "format": "json"
    }
  }'

curl -X POST "https://${SHOPIFY_STORE}.myshopify.com/admin/api/2025-07/webhooks.json" \
  -H "X-Shopify-Access-Token: ${ACCESS_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "webhook": {
      "topic": "returns/decline",
      "address": "https://n8n.clientdomain.com/webhook/shopify-return-event",
      "format": "json"
    }
  }'

curl -X POST "https://${SHOPIFY_STORE}.myshopify.com/admin/api/2025-07/webhooks.json" \
  -H "X-Shopify-Access-Token: ${ACCESS_TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "webhook": {
      "topic": "refunds/create",
      "address": "https://n8n.clientdomain.com/webhook/shopify-refund-event",
      "format": "json"
    }
  }'

curl "https://${SHOPIFY_STORE}.myshopify.com/admin/api/2025-07/webhooks.json" \
  -H "X-Shopify-Access-Token: ${ACCESS_TOKEN}"

n8n Webhook Receiver Workflow

Create a workflow named 'Shopify Return Event Handler' with the following nodes:

const crypto = require('crypto');
const hmacHeader = $input.first().json.headers['x-shopify-hmac-sha256'];
const body = $input.first().json.rawBody;
const secret = process.env.SHOPIFY_WEBHOOK_SECRET;
const hash = crypto.createHmac('sha256', secret).update(body, 'utf8').digest('base64');

if (hash !== hmacHeader) {
  throw new Error('Invalid Shopify webhook signature');
}
return $input.all();

Testing & Validation

• TEST 1 — Standard Return (Happy Path): Submit a return request via the Zendesk chat widget for a valid, fulfilled order within the return window. Verify: AI agent asks for order number and return reason, eligibility check returns positive, return label is generated via EasyPost, Zendesk ticket is created with all custom fields populated, Klaviyo 'Return Approved' email is received by the customer within 2 minutes. Expected completion: under 3 minutes end-to-end.
• TEST 2 — Out-of-Window Return (Denial): Submit a return for an order delivered 45+ days ago (beyond 30-day window). Verify: the AI agent politely denies the return with a clear explanation referencing the return window policy, offers to connect to a human agent, and the Zendesk ticket is tagged 'return_denied' with denial reason logged.
• TEST 3 — Non-Returnable Item: Attempt to return an item tagged as 'final-sale' in Shopify. Verify: the eligibility checker catches the non-returnable tag and the AI agent explains the item is final sale, without processing any refund.
• TEST 4 — Exchange Flow with AI Recommendation: Select 'Exchange' for a 'wrong size' return. Verify: the Exchange Recommendation Agent queries product variants, GPT-4.1 generates size recommendations based on available inventory, recommendations are presented to the customer in chat, and if accepted, the exchange order is created in Shopify.
• TEST 5 — High Fraud Score Escalation: Create a test scenario with a customer who has 4+ recent returns and a high-value order ($300+). Verify: the fraud score exceeds 70, the return is NOT auto-processed, the Zendesk ticket is assigned to the Fraud Review Team with 'Urgent' priority, and an internal note lists all fraud risk factors.
• TEST 6 — Low Fraud Score Auto-Approval: Submit a return for a first-time returner with a $30 order. Verify: the fraud score is below 30, the return is auto-approved without human intervention, and the full workflow (label generation, Zendesk update, Klaviyo notification) completes autonomously.
• TEST 7 — Human Escalation Request: During a chat with the AI agent, type 'I want to speak with a human' or 'Let me talk to a real person.' Verify: the AI agent immediately transfers the conversation to a human agent in the Returns Team group with full context preserved.
• TEST 8 — Shopify Webhook Sync: Process a return manually in Shopify Admin (simulate warehouse receiving the item). Verify: the Shopify webhook fires, n8n receives and validates the HMAC signature, the Zendesk ticket is updated to 'Return Received', and the Klaviyo 'Return Received at Warehouse' email is sent.
• TEST 9 — Payment Refund Execution: After a return is marked as received, verify that the refund is processed correctly — check Stripe dashboard (or Shopify Payments) for the refund transaction matching the correct amount, and verify the customer receives the 'Refund Processed' notification email.
• TEST 10 — PCI Compliance Check: Review all Zendesk ticket records, n8n execution logs, and OpenAI API call logs. Verify: no credit card numbers appear anywhere in the system — only tokenized payment references. Test Zendesk's automatic credit card redaction by entering a fake card number in chat.
• TEST 11 — In-Store Kiosk Return (if applicable): At the physical kiosk, scan a product barcode, complete the return flow on the touchscreen, verify the label prints on the Zebra ZD421, and verify the receipt prints on the Epson TM-T88VII with correct RMA details.
• TEST 12 — Load Test: Use the Zendesk API to simulate 50 concurrent return requests. Verify: n8n processes all requests without timeout or failure, API rate limits are not exceeded (monitor Shopify 429 responses), and all 50 Zendesk tickets are correctly created and updated.
• TEST 13 — Analytics Dashboard Verification: After processing 20+ test returns of various types, review the Zendesk Explore dashboard. Verify: all charts render correctly, return volume chart shows accurate counts, reason breakdown matches test data, AI vs. human resolution rate is correctly calculated, and fraud escalation rate matches expected results.
• TEST 14 — Failover and Error Handling: Temporarily disable the n8n webhook endpoint. Submit a return request via Zendesk. Verify: the AI agent handles the API failure gracefully (does not crash or show error to customer), informs the customer that processing is temporarily delayed, and automatically escalates to a human agent. Restore n8n and verify queued requests are processed.

Client Handoff

Client handoff should be conducted as a 2-hour onsite or video session with the client's designated project stakeholder, returns team lead, and any staff who will handle escalated returns. Cover the following topics:

Documentation to Leave Behind

• System architecture diagram (PDF)
• Zendesk admin quick reference guide (step-by-step with screenshots)
• Return policy configuration reference (where each setting lives)
• Fraud review standard operating procedure (SOP)
• Troubleshooting guide (common issues and fixes)
• Escalation contact sheet (MSP support email, phone, portal URL, SLA times)
• API credentials inventory (stored in client's password manager, not on paper)
• Monthly reporting template
• Policy change request form template

Maintenance

ONGOING MSP MAINTENANCE RESPONSIBILITIES:

Weekly (1–2 hours)

• Review Zendesk AI agent resolution rate and escalation patterns in Explore dashboard
• Check n8n workflow execution logs for errors or failures (n8n dashboard > Executions > filter for 'Error')
• Review fraud-escalated tickets to identify false positives and calibrate scoring thresholds
• Monitor EasyPost label generation success rate and shipping costs
• Check Shopify API rate limit usage (aim to stay below 80% of limit)

Monthly (4–6 hours)

• Generate and deliver monthly analytics report to client: return volume trends, AI resolution rate, fraud stats, refund amounts, exchange conversion rate, CSAT scores
• Review and tune AI agent conversation flows based on escalation patterns (identify new intents or FAQ topics)
• Update Zendesk Help Center articles if return policy has changed
• Review OpenAI API usage and costs; optimize prompts if token consumption is higher than expected
• Apply n8n and Zendesk platform updates (test in staging first if available)
• Rotate API keys per security policy (quarterly rotation recommended)

Quarterly (8–12 hours)

• Comprehensive fraud scoring model review: analyze false positive and false negative rates, adjust weights and thresholds
• PCI DSS 4.0.1 compliance spot check: verify no cardholder data in logs, TLS certificates valid, audit trails intact
• Privacy compliance review: check data retention compliance, verify customer data deletion requests are honored
• Review and update the AI agent persona prompt based on new products, policy changes, or seasonal adjustments
• Performance optimization: review n8n workflow execution times, optimize slow API calls, evaluate if platform tier upgrades are needed
• Client business review meeting: present ROI metrics, discuss expansion opportunities (new channels, additional stores)

Annual

• Full system audit: security, compliance, performance, and architecture review
• Vendor contract renewals and pricing optimization (negotiate volume discounts)
• Evaluate new platform features and AI model upgrades (e.g., GPT model updates)
• Hardware refresh assessment for in-store kiosks (typically 3–5 year lifecycle)
• Disaster recovery test: simulate system failure and verify recovery procedures

SLA Considerations

• Severity 1 (Complete system down — no returns processing): 1-hour response, 4-hour resolution target
• Severity 2 (AI agent degraded — escalating all to humans): 2-hour response, 8-hour resolution target
• Severity 3 (Minor issues — single workflow failure, cosmetic): 4-hour response, 24-hour resolution target
• Severity 4 (Enhancement requests, non-urgent): Next business day response, scheduled in next maintenance window

Model/Prompt Retraining Triggers

• AI resolution rate drops below 50% for 3 consecutive days
• Customer satisfaction score for AI-handled tickets drops below 3.5/5
• New product categories or return policies are introduced
• Significant seasonal changes (holiday return surge, new collection launch)
• OpenAI releases a new model version that may improve quality/reduce cost
• Fraud false positive rate exceeds 10% in a given week

Alternatives

Replace Zendesk with Gorgias as the customer service and AI agent platform. Gorgias is purpose-built for e-commerce with native Shopify, BigCommerce, and WooCommerce integrations. It uses ticket-based pricing (not per-agent) and has a built-in AI agent that can be trained on return policies. The AI agent add-on costs ~$0.90–$1.00 per conversation.

Intercom Fin AI Agent

Use Intercom as the customer service platform with Fin AI Agent for autonomous return resolution. Fin has a proven 67% resolution rate across 40M+ conversations and costs $0.99 per resolution. Intercom provides a modern messenger-style interface popular with DTC brands.

Salesforce Agentforce + Commerce Cloud

Deploy Salesforce's full Commerce Cloud with Order Management System and Agentforce AI agents. This is an enterprise-grade solution that provides unified commerce across all channels, built-in return/exchange processing, and autonomous AI agents powered by Salesforce's Data Cloud.

White-Label Custom Build (n8n + OpenAI + Shopify APIs)

Skip the SaaS returns platform (Loop/AfterShip) and customer service platform (Zendesk) entirely. Build a fully custom solution using n8n for workflow orchestration, OpenAI GPT-4.1 for the conversational AI agent, Shopify APIs for return processing, and a custom-built web portal for the customer-facing return experience.

Loop Returns + Shopify Flow (No AI Agent)

A simpler approach using Loop Returns as the self-service return portal with Shopify Flow for basic automation, without deploying an AI conversational agent. Customers use the Loop portal to self-serve returns, and Shopify Flow handles automated notifications and inventory updates.