3169824 - Machine Learning (BETA) Product Recommendation

Request for actication of BETA(!) feature for Machine Learning Product Recommendation

Activation is currently done for selected customers by ML development activation via requested case.

As customer, should this be an option for you, you need to be aware of and agree to the Terms and Conditions (see below)

 (Beta) Product Recommendation - Account - Sales, visible on Sales Quotes.

Recommendations are steered by product master data and transaction data used in sales quote and opportunity for the account.

Prerequisites

● To use machine learning based product recommendation, you require an SAP Sales Cloud enterprise license.

● Model training is based on one year's sales quote and opportunity data.

● You must raise a feature enablement request to the LOD-CRM-ML-SLS queue. Eligibility for participation in the beta program is checked by the Cloud for Customer Machine Learning product team.

● You must have a minimum of 50 distinct customers (should be used in the quote).

● You must have a minimum of 10,000 quotes in Closed state.

NOTE: Product recommendation currently has the following restrictions:  Restriction EU access restricted customers are currently excluded from the Beta release.

SAP Cloud for Customer

Terms and Conditions on using BETA ML Product Recommendation:

This feature is available as a beta version for test use only. It has not been released for productive use. If you activate this feature, you understand and agree to the following conditions:
● Feature is not covered by SAP support agreements or warranty obligations
● Any data loss or damage that may result from use of this feature is not the responsibility of SAP or its representatives
● You will not use this feature to process any personal data of end users
● SAP may change or remove this function at any time, and it may never appear in the generally available version of the Service

Product list vs Product Recommendation

• We use also Product List of type Cross Selling as product recommendations. Based on a product that is already part (required product) of an order or a sales quote, the system shows additional product recommendations. This setup is manual by the key user. With this approach you might also see completely new products recommended for the user.  
• The ML product recommendations are proposing products based on history data only. 
• In general the product list with its product proposals are used similar like listings in SAP ECC backend. Usually only those products from these list can be order. So it is not a recommendation and rather a help for the user to select the right products.

 

How does Product Recommendation work?

• Association rules learning is used for recommending complementary products. It helps in associating one product with another product and tries to answer which products are associated with one another. 
• Machine learning model works by looking for combinations of products that occur together frequently in Purchase history transactions. 
• The model understands various relationships through historical data like account-product, product-product and account-account and learn rules which requires support of several hundred transactions.
• Model training is on Sales quote data. You must have productive usage of completed sales quote in the last one year with minimum 50 unique products.

Prerequisites:

Model training is based on one year's sales quote and opportunity data.
● You must raise a feature enablement request to the LOD-CRM-ML-SLS queue. Eligibility for participation in the beta program is checked by the Cloud for Customer Machine Learning product team.
● You must have a minimum of 50 distinct customers (should be used in the quote).
● You must have a minimum of 10,000 quotes in Closed state

(BETA) Product Recommendation

Attach ppt and pdf

ML, machine learning, product , KBA , missing , product recommendation , LOD-CRM-PM-SLS , C4C Product Management - Sales , LOD-CRM-ML , C4C Machine Learning , How To

SAP Cloud for Customer add-ins all versions ; SAP Cloud for Customer core applications 2202