Working with Commerce Marketing

The Commerce Marketing scenarios provide consumers with relevant product recommendations or offer recommendations.

SAP Marketing Cloud Recommendation allows business analysts and marketing experts to create recommendation models that provide consumers with relevant recommendations in real time, simultaneously across multiple sales channels. Recommendation models leverage algorithms and SAP HANA to query and retrieve recommendations from sales or business event data.

Recommendations enable you to:

• Leverage deep Analytics insights of your customers
• Enable seamless buying journeys cross channels
• Deliver unique experiences
• Enrich customer dynamic profiles by capturing clickstream
• Provide smart offers recommendations
• Provide context-relevant real-time product recommendations

Watch this video to learn more about the key capabilities of Product Recommendation:

An algorithm is a component that is used to find meaningful patterns and rules in data. The algorithms delivered with SAP Marketing Cloud fall into one of the following algorithm types:

• Association
• Collaborative Filtering
• Item Mapping
• Post Processing
• Query
• External Algorithms

To learn more about algorithms, please read the Help documentation

Let’s look at the process flow of Offer Management in SAP Marketing Cloud. The five-step process includes creating, refining, designing, presenting, and measuring.

In this video, you’ll learn about product recommendation, promotional offer and coupon with some examples. Watch the video to learn more.

For more information, see Recommendations (SAP Business Technology Platform) Integration Guide.

The following graphic will give you an overview of Offers in SAP Marketing Cloud:

The diagram below shows the relationship between offer management and coupon management, by representing which aspects of a coupon are controlled by which application. Location and eligibility is managed by the offer app. Coupon code validity will be managed by the coupon, but the calculation is based on the offer validity. Relationship, visualization, and coupon type are handled by the coupon app.

To ensure coupons and coupon codes are maintained in SAP Marketing Cloud correctly, make sure to follow one of the following scenarios.

Import coupon and codes through the OData Coupon API or the OData offer import service. Please read this documentation for more details.

• Manually maintain/import coupon and upload externally maintained codes through a CSV file.
• Manually maintain/import coupon and import externally generated codes through an integrated external coupon service system.
• Manually maintain/import coupon and manually maintain externally created codes.

For more information about offer management and coupons, please read this page in the online documentation.

The following marketing apps enable you to carry out the commerce marketing scenarios:

• Recommendation Model Types: The marketing expert creates, maintains, and manages model types in this app. A recommendation model type is a representation of a recommendation scenario (e.g. cross-selling, viewed together).
• Recommendation Scenarios: In this app, the marketing expert assigns a model type to a scenario. A recommendation scenario enables external systems to post interactions to an SAP Hana database or receive recommendations using an OData service.
• Recommendation Algorithm Defaults: The marketing expert can maintain default parameters and data source pre-filter values that algorithms contain when they are initially added to models.
• Recommendation Models: The marketing expert creates, maintains, and manages models in this app. A recommendation model is a reusable component that consists of algorithms that consume historical data to retrieve recommendations.
• Manage Recommendations: In this app, the marketing expert maintains and evaluates the effectiveness of recommendation scenarios. The expert also creates, maintains, and manages models.
• Using either Manage Recommendations or Recommendation Models: The marketing expert can analyze the recommendations a generated model returns using consumer and leading item parameters. Additionally, the marketing expert can manually activate a model, or activate it automatically on the activation date. Once activated, a model is then the active model for the model type it is assigned.