LLM Integration Guide

Real-time AI enrichment with OpenAI GPT-4o through Xano middleware for customer segmentation and personalization

Overview

This architecture uses Xano's native OpenAI integration to enrich customer data in real-time. When a user updates consent preferences or completes a purchase, Xano calls GPT-4o to generate AI-powered segments, lifetime value predictions, and personalized recommendations—all within 200-500ms.

Why Xano + OpenAI?

  • Native Integration: No custom API code needed, Xano handles authentication and rate limiting
  • Sub-500ms Latency: GPT-4o inference completes before user sees response
  • Structured Outputs: JSON schema enforcement ensures consistent data format
  • Cost Efficiency: Only fires on meaningful events (consent updates, purchases), not page views

Implementation Steps

1

Configure Xano OpenAI Integration

In Xano dashboard, add OpenAI API key and select GPT-4o model with structured output mode

2

Define JSON Schema

Create output schema for customer segments: high_value_buyer, price_sensitive, frequent_browser, etc.

3

Create Xano Function

Build serverless function that accepts customer data and returns AI-enriched segment classifications

4

Add Database Trigger

Set up Postgres trigger on consent_updates table to automatically call AI function on INSERT/UPDATE

5

Store AI Segments

Write enriched data to Shopify Meta Objects via GraphQL for persistent storage and UCP compliance

6

Trigger n8n Workflow

Fire webhook to n8n for background tasks: BigQuery sync, email campaigns, Google Ads audience updates

Prompt Engineering for Customer Segmentation

System Prompt Example

You are a customer segmentation AI for an e-commerce platform.

Given customer data (order history, consent preferences, browsing behavior),
classify the customer into ONE primary segment and up to 3 secondary segments.

Available segments:
- high_value_buyer: LTV > $500, frequent purchases
- price_sensitive: high coupon usage, cart abandonment
- frequent_browser: many sessions, low conversion
- new_customer: first purchase within 30 days
- loyal_customer: 5+ purchases, high retention
- at_risk: no purchase in 90 days, declining engagement

Return JSON with:
{
  "primary_segment": "string",
  "secondary_segments": ["string"],
  "confidence_score": 0.0-1.0,
  "ltv_prediction": number,
  "recommended_actions": ["string"]
}

User Prompt Template

Customer ID: {{customer_id}}
Total Orders: {{order_count}}
Total Spend: ${{total_spend}}
Last Purchase: {{days_since_last_purchase}} days ago
Avg Order Value: ${{avg_order_value}}
Consent Given: {{marketing_consent ? "Yes" : "No"}}
Browsing Sessions (30d): {{session_count}}
Cart Abandonment Rate: {{abandonment_rate}}%

Classify this customer and provide actionable recommendations.

Handling AI Responses

Xano receives structured JSON from GPT-4o and processes it through the following pipeline:

Step Action Duration
1. Validation Verify JSON schema matches expected format ~5ms
2. Confidence Check If confidence_score < 0.7, flag for manual review ~2ms
3. Shopify Update Write segments to Meta Object via GraphQL ~100ms
4. Webhook Trigger Fire n8n webhook with enriched customer data ~50ms
5. Response Return Send success confirmation to frontend ~10ms

Total Processing Time: 200-500ms (including GPT-4o inference)

Performance & Optimization

When to Use AI Enrichment

✅ Good Use Cases:

  • Consent preference updates
  • Purchase completion
  • Account creation
  • High-value actions (>$100 cart)

❌ Avoid For:

  • Every page view
  • Low-value browsing
  • Anonymous users
  • Bot traffic

Caching Strategy

Cache AI segments for 24 hours to reduce API calls:

  • Redis Cache: Store segment in Xano memory
  • Shopify Meta Object: Persistent storage
  • Refresh Trigger: Only on significant events

This reduces GPT-4o calls by 90% while maintaining accuracy.

Integration with GTM/GA4

After Xano enriches customer data with AI segments, push the results to GTM DataLayer for analytics tracking:

Frontend DataLayer Push

// After successful Xano API response
window.dataLayer = window.dataLayer || [];
window.dataLayer.push({
  'event': 'ai_segment_updated',
  'customer_id': response.customer_id,
  'primary_segment': response.primary_segment,
  'ltv_prediction': response.ltv_prediction,
  'confidence_score': response.confidence_score
});

// GA4 will automatically track this event
// Use it for:
// - Custom audiences in Google Ads
// - Personalized remarketing campaigns
// - Looker Studio dashboards