---
schema_version: "1"
id: 40e634b836946ae88a8dcfdffc1de41e839ffbc0d69f26533af8deab8da627ac
title: Configure Product Recommendations for Point of Sale
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/commerce/264-0-0/rt_cms_modules_product_recommendations.md
canonical_url: https://help.salesforce.com/s/articleView?id=commerce.rt_cms_modules_product_recommendations.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 595fe22348af2eb6d2506b6ada0aa7657b84d433775ea5725918afd61d16423b
description: Configure Point of Sale CMS to use customer data to provide tailored product suggestions within the POS app.
products:
  - Commerce
release: "264"
---
# Configure Product Recommendations for Point of Sale

Configure Point of Sale CMS to use customer data to provide tailored product suggestions within the POS app.

- App Build: 5.0.0 or later
- Platform Support: iPhone, iPad
- Offline Support: No

The Product Recommendations feature in Point of Sale uses customer preferences and purchase history to show tailored product suggestions in the POS app.

## Enable App Settings

1. Go to **App Config | Edit | Modules | Recommendations**.
2. Turn on **Has Product Recommendations**.
3. Set up **Recommendations Template** to select whether recommended products appear in a list that scrolls horizontally or in a grid like the product search page.

## Configure a Recommendations Engine

Each merchant, region, and locale can have one or more recommendation engine configurations. Point of Sale supports these recommendation providers:

- Certona
- Demandware
- Dynamic Yield
- Einstein
- PredictSpring
- Product Feed (configure the product feed with a recommendation field)
- RichRelevance
- Unbxd

If configuring an engine other than PredictSpring (Point of Sale), set properties specific to that recommendation engine.

1. In the CMS, go to **Integrations | Recommendations Configuration**.
2. Edit or create an existing configuration.
3. Under **Type**, select the type of recommended products to show the customer.
    
    - **Recommendation** shows product recommendations based on the product that the customer is viewing.
    - **Add On** shows product recommendations based on other products that customers often purchase together.
    - **Bundle** shows bundle recommendations for an individual product.
4. Under **Provider**, select a recommendation engine.
    
    PredictSpring is the only provider available for the **Bundle** type. Point of Sale handles bundle resolution internally.
5. Fill out the required fields by referring to the table.
6. Select **Save**.

    
| Field | Field Type | Required | Description | Example |
| --- | --- | --- | --- | --- |
| Base URL | Text | No | Base URL for the API. For Einstein, use `https://api.cquotient.com/v3` (or the latest version available). | https://api.cquotient.com/v3 |
| API Path | Text | No | Path for the API recommendation | /path/example/1 |
| Site ID | Text | No | Site ID configured within the recommendation engine. Use the site ID configured on your ecommerce instance. For information on configuring sites, see the Commerce Cloud documentation. | 22jw233d100 |
| API Token | Text | No | Token for the API recommendation. Get this token from the Account Manager API client configuration in your recommendation provider's system. | qwlkejsiwu21932hswhh002 |
| Placements | Text | No | Applicable to Certona and RichRelevance | item\\\_page.brand\\\_app\\\_1 |
| Strategy Set | Text | No | Applicable to Einstein—recommender name | product-to-product |
| Lookup Field | Text | No | For Product Feed-based recommendation, the product field that has the recommended products. | CustomString0 |