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. Customers can also request recommendations themselves at the point of purchase, directly from the offer page (see Adobe recommendations in the ordering experience).

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)
• includePropensity (boolean) - When set to true, the response includes Adobe's customer propensity insights, such as churn risk and seat expansion potential, alongside the product recommendations. Defaults to false if not provided.

Example request body:

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

Response

When includePropensity is false or not provided, 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

Response with propensity insights

When includePropensity is set to true, the response also contains a propensity object with Adobe's insights for the Customer:

{
  "recommendationTrackerId": "e60632be-bdfc-4266-af7e-4a644069d529",
  "propensity": {
    "churn": [
      {
        "category": "allOfferings",
        "probability": "LOW",
        "refreshDate": "2026-07-16T00:00:00Z",
        "reasons": [
          {
            "reasonCode": "contract_num_months_to_renew",
            "description": "Number of months remaining until this customer's contract is up for renewal.",
            "value": "11"
          },
          {
            "reasonCode": "contract_num_days_since_last_desktop_app_launch_in_last_365_days",
            "description": "Number of days since the customer last launched any Adobe desktop app (within the past year).",
            "value": "2"
          }
        ],
        "additionalDetails": {}
      }
    ],
    "seatExpansion": [
      {
        "category": "allOfferings",
        "probability": "LOW",
        "refreshDate": "2026-07-16T00:00:00Z",
        "reasons": [
          {
            "reasonCode": "team_deployment_ratio_at_snapshot",
            "description": "Share of provisioned seats that are currently assigned to end users.",
            "value": "0.18"
          }
        ],
        "additionalDetails": {
          "predictedAddonSize": 1
        }
      }
    ]
  },
  "productRecommendations": {
    "upsells": [],
    "crossSells": [
      {
        "rank": 0,
        "product": {
          "baseOfferId": "65318387CA01A12"
        }
      }
    ],
    "addOns": []
  }
}

Propensity response fields:

• propensity - Object containing the Customer's propensity insights. Included only when includePropensity is true.
  • churn - Array of churn risk insights for the Customer
  • seatExpansion - Array of seat expansion insights for the Customer

Each entry in churn and seatExpansion includes:

• category - The offering scope the insight applies to (e.g., allOfferings)
• probability - Likelihood level (e.g., LOW, MEDIUM, HIGH)
• refreshDate - Date the insight was last calculated
• reasons - Array of factors behind the insight, each with:
  • reasonCode - Identifier for the contributing factor
  • description - Explanation of the factor in plain language
  • value - Measured value of the factor
• additionalDetails - Object with extra data related to the insight (for example, predictedAddonSize for seat expansion insights); may be empty

Get All Customer Subscriptions Details

This API supports optionally including Adobe recommendations in the response.

Endpoint

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 supports optionally including Adobe recommendations based on the Customer's order history.

Endpoint

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": [...]
    }
  }
}

Adobe recommendations in the ordering experience

Adobe recommendations are available both through the API and directly in the ordering experience. A View available recommendations option lets Customers retrieve personalized recommendations from Adobe while placing an Order, without any custom integration. Recommended Offers are presented in the same categories described above: suggested upgrades, frequently bought-together products, and relevant add-ons.

Requesting recommendations

The Adobe recommendations are automatically added to the respective Adobe Offers. On the Platform Offer page, Customers see a View available recommendations button next to View available promotions. Clicking it opens a Get Recommendations dialog.

When the Customer clicks Get Recommendations, the Platform retrieves the data from Adobe and displays the results directly in the dialog, grouped as: recommended choice, frequently bought together, and enhance your experience with add-ons.

Benefits of using recommendations

Implementing Adobe recommendations provides several advantages: