Adobe product recommendations

Understanding Adobe recommendations

Adobe's recommendation system provides context-aware product suggestions based on what Customers currently have or intend to purchase. The recommendations differ for new Customers versus existing ones, ensuring relevance at each stage of the relationship.

Sample recommendations include:

• Creative Cloud All Apps Pro for Creative Cloud All Apps customers
• Acrobat Pro for Acrobat Standard customers
• Creative Cloud Enterprise Edition 4 for Creative Cloud Enterprise customers
• Adobe Express for non-Adobe Express customers
• Acrobat AI Assistant for Acrobat Pro customers

How Adobe recommendations work

The Platform provides API endpoints to access Adobe's recommendation system. This allows you to:

• Fetch personalized product recommendations for specific Customers (including tracker IDs from Adobe)
•  Integrate and display recommendations in marketplace interface 
• Include tracker IDs in order requests to help Adobe improve future recommendations

The recommendation engine analyzes customer data, current Subscriptions, and purchase patterns to suggest the most relevant Products. By sending tracker IDs with each recommendation response back to Adobe when orders are placed, you help Adobe gain insights into recommendation effectiveness and improve future suggestions.

Adobe organizes recommendations into three categories:

• Upsells - Better or more advanced versions of products the Customer already has
• Cross-sells - Complementary products that work well together with existing products
• Add-ons - Additional features or extensions for existing products

Customer journey with recommendations

The recommendation system enhances the customer experience throughout their journey. Here's how recommendations work at different stages:

Discovery and initial purchase

When a Customer first explores the marketplace, you can fetch Adobe's product recommendations based on their profile and browsing behavior. Adobe's recommendation engine provides different suggestions for new Customers versus existing ones, ensuring relevance from the first interaction.

Ongoing optimization

As Customers use their Products and make additional purchases, Adobe's recommendation engine continuously refines its suggestions. Including tracker IDs in order requests creates a feedback loop that helps Adobe improve recommendation accuracy over time.

Working with Adobe recommendations APIs

The Platform provides integration with Adobe's recommendation APIs, enabling you to fetch personalized product suggestions and incorporate them into Customer's experience. The following APIs support Adobe recommendations functionality.

Fetch Recommendations API

The Fetch Recommendations API allows you to request personalized product recommendations directly from Adobe for a specific Customer.

Endpoint

Request body

Required fields:

• customerId (string) - Adobe customer ID

Optional fields:

• recommendationContext (string) - Context for recommendations. Possible values:
  • RENEWAL_ORDER_PREVIEW
  • GENERIC
  • ORDERS_VIEW
• offers (array of objects) - List of products with offerId and quantity
  • offerId (string) - External offer ID on Adobe side
  • quantity (integer) - Product quantity
• country (string) - Two-letter country code (e.g., US, GB, LV)
• language (string) - Language preference. Possible values:
  • EN (English)
  • MULT (Multiple/Local language)

Example request body:

{
  "customerId": "1005298xxxx",
  "recommendationContext": "GENERIC",
  "offers": [
    {
      "offerId": "5325084CA01A12",
      "quantity": 10
    }
  ],
  "country": "LV",
  "language": "MULT"
}

Response

The API returns personalized recommendations categorized by type:

{
  "recommendationTrackerId": "99a27a8e-xxxx-xxxx-91c8-d8e241ea69ba",
  "productRecommendations": {
    "upsells": [
      {
        "rank": 2,
        "product": {
          "baseOfferId": "65325078CA01A12"
        }
      }
    ],
    "crossSells": [
      {
        "rank": 1,
        "product": {
          "baseOfferId": "65318387CA01A12"
        }
      }
    ],
    "addOns": [
      {
        "rank": 1,
        "product": {
          "baseOfferId": "30005894CA01A12"
        }
      }
    ]
  }
}

Response fields:

• recommendationTrackerId - Tracking ID from Adobe. Include this ID in your order requests when creating subscriptions based on these recommendations. This helps Adobe track recommendation effectiveness and improve future suggestions.
• productRecommendations - Object containing recommendation categories:
  • upsells - Better versions of existing products
  • crossSells - Complementary products that work well together
  • addOns - Additional features or extensions for existing products

Each recommendation includes:

• rank - Priority ranking of the recommendation
• product.baseOfferId - Adobe offer ID for the recommended product

Get All Customer Subscriptions Details

This API has been enhanced to optionally include Adobe recommendations in the response.

Endpoint

New query parameters

• fetch-recommendations (boolean) - Set to true to include recommendations in the response
• recommendation-country (string) - Two-letter country code (e.g., US, LV)
• recommendation-language (string) - Language preference (EN or MULT)

Response with recommendations

When fetch-recommendations=true, the response includes a recommendations object with personalized product suggestions:

{
  "totalCount": 9,
  "items": [
    {
      "subscriptionId": "25abxxxxb74040a7babdxxxxaf23e9NA",
      "currentQuantity": 1,
      "offerId": "65324863CA01A12",
      "status": "1000",
      "renewalDate": "2026-12-17T00:00:00"
    }
  ],
  "recommendations": {
    "productRecommendations": {
      "upsells": [...],
      "crossSells": [...],
      "addOns": [...]
    }
  }
}

Search Customer Order History

This API has been enhanced to optionally include Adobe recommendations based on the Customer's order history.

Endpoint

New query parameters

• fetch-recommendations (boolean) - Set to true to include recommendations in the response
• recommendation-country (string) - Two-letter country code (e.g., US, LV)
• recommendation-language (string) - Language preference (EN or MULT)

Response with recommendations

When fetch-recommendations=true, the response includes a recommendations object:

{
  "totalCount": 1,
  "count": 1,
  "items": [
    {
      "orderId": "9201942xxxx",
      "customerId": "1005298xxxx",
      "orderType": "NEW",
      "status": "1000",
      "creationDate": "2026-01-02T11:30:20Z"
    }
  ],
  "recommendations": {
    "productRecommendations": {
      "upsells": [...],
      "crossSells": [...],
      "addOns": [...]
    }
  }
}

Benefits of using recommendations

Implementing Adobe recommendations provides several advantages: