Building Personalization APIs for Developers

Why APIs for Personalization?

Personalization can’t just live in UI tweaks or Flow automations. Teams need APIs that expose personalization logic so any system—storefront, app, email, or mobile—can plug into it.

APIs make personalization:

  • Composable → logic lives once, reused everywhere.

  • Scalable → multiple devs/systems can call it.

  • Future-proof → easy to upgrade rules/models later.


API Types for Shopify Personalization

1. Profile API

  • Endpoint returns enriched customer profile.

  • Fields: loyalty tier, churn risk, next-best-action, recommended SKUs.

2. Recommendation API

  • Given product/customer → return ranked recs.

  • Uses embeddings, purchase history, and context.

3. Contextual API

  • Input: request headers (geo, device, session).

  • Output: real-time personalization payload (promo banner, default shipping, theme variant).

4. Experimentation API

  • Handles A/B assignment.

  • Returns variant assignment consistently across channels.


Example: Architecture Flow

  1. Shopify warehouse builds personalization profiles.

  2. Profiles exposed via /api/profile/:customerId.

  3. Storefront (Hydrogen, Liquid, or React) calls API → injects dynamic UI.

  4. Email service queries API → inserts recommended SKUs in campaign.

  5. Mobile app fetches API → personalizes in-app banners.


Copilot Kit: Personalization APIs

Open VS Code with GitHub Copilot Agent Mode and try:

1. Profile Endpoint

Create: "Scaffold a Next.js API route `/api/profile/[id]` that fetches customer metafields from Shopify Admin API and returns JSON {loyalty_tier, churn_risk, rec_products}."

2. Recommendation Endpoint

Create: "Write a Node.js Express endpoint `/api/recs` that takes customer_id, queries a vector DB (Supabase/Postgres), and returns top 5 similar products."

3. Contextual API

Create: "Generate a Next.js API route `/api/context` that reads request headers (geo, user-agent), queries personalization rules, and returns JSON {promo_banner, default_shipping, theme_variant}."

4. A/B Assignment

Ask: "Write a function that assigns customers to experiment buckets A/B/C, stores assignment in Redis keyed by customer_id, and returns consistent assignment via API."

Why This Matters

  • Dev Flexibility: APIs let you decouple personalization from any one system.

  • Cross-Channel Consistency: Same personalization across web, app, email, ads.

  • Scalable Experiments: API-driven testing ensures reliability.

  • Foundation for AI: ML models can plug into APIs without breaking UI.


Takeaway: Personalization APIs turn your store into a platform. Instead of sprinkling rules everywhere, centralize logic and expose it via APIs so developers and marketers can build faster, smarter, and consistently.