The Personalised Product Recommendations use case is designed to help you insert real-time, 1-to-1 product suggestions directly into your marketing messages. By integrating your external product recommendation engine with a Data Connection, you can use each customer's ID to pull a unique set of recommended products into any template. This method allows you to scale hyper-personalized content across all campaigns and ensures your recommendations are always timely and relevant.

Problem Statement

You want to insert real-time, personalized product recommendations into emails, but managing this manually or with static, non-personalized content doesn’t scale and offers a poor customer experience.

Goal

Your product recommendation engine generates a list of recommended products for each user. You want to:

• Display these recommendations in your campaign messages.
• Optionally apply filters (e.g., show only in-stock or high-margin items).
• Avoid duplicating templates for different recommendation types.

Solution

Data Connections can be used to deliver personalized product content for each user. By setting up a Data Connection keyed by customer_id, updated automatically via API, you can pull product details into your template using formulas. This enables 1:1 product messaging at scale.

Implementation

Step 1: Create a Data Connection with Recommendation Data

Create a Data Connection where each record corresponds to a user ID and contains their recommended products. This data is often structured with nested fields (e.g., a JSON object or array).

Recommended method: Use the External API creation method to automatically push new recommendations into Optimove as they are generated by your recommendation engine.

Example JSON Structure:

[
  {
    "user_id": "1010514000996424",
    "recommended_products": [
      {
        "product_id": "P1001",
        "name": "Classic Leather Sneakers",
        "brand": "UrbanWalk",
        "price": 89.99,
        "image_url": "https://example.com/images/P1001.jpg"
      }
    ]
  }
]

Step 2: Use Formulas in Your Email Template

Pull product data into your template using dot notation in your personalization formulas to access the nested data fields.

Example Formulas:

Product brand: [%DC_987zyx:[%CUSTOMER_ID%]::recommended_products.brand:%]
Product name: [%DC_987zyx:[%CUSTOMER_ID%]::recommended_products.name:%]

Outcome

By integrating your product recommendation engine via Data Connections, you achieve:

• Fully personalized content based on real-time preferences.
• Flexible presentation and filtering control.
• A scalable system for applying product recommendations across multiple campaigns and channels.