Commerce, SAP Marketing Cloud

Recommendation Models in SAP Marketing Cloud

One of the toughest problems of a person is making a right choice, analyzing multiple products, discounts and reviews which isolates the customer. Passing through multiple products, brands and offers buyer just end up with a confusion in choosing the right one. Every buyer wants to be smart when he is purchasing some product from an online store and there     are many chances that the buyer might switch to an alternative smart online store which fulfill his requirement faster. Recommending the right relevant products to the potential buyers will increase the order size.

Solution Overview

SAP Marketing Cloud provides a smart online solution for customers. Product and offer recommendations suggest customer based on their interests, buying history and click through interactions. SAP Marketing consumes all these data from commerce cloud and apply Machine Learning algorithms to study and understand the user metrics and data to recommend the right products.

Features

  • Integration with multiple SAP Products
  1. SAP Commerce Cloud
  2. Hybris C4C
  • Provided rest API/OData to integrate with any non-SAP System
  • Extensive set of ML Algorithms which can be configured as per the business need
  • Each scenario can be built applying multiple algorithms
  • Activate and deactivate feasibility
  • Analyze model with preview option, you can analyze the recommendation by using consumer, context and item parameter

Potential Benefits

  • Customer Satisfaction
  • Increased Cart value
  • Increase cart conversion rate and sales
  • Presenting customers content adjusted to their preferences

Understanding with an example

Seamless collaboration between SAP Marketing Cloud and Commerce cloud has many benefits

  • Understand the customer behavior
  • Personalize storefront experience with relevant offers and products
  • Increase the conversion from abandoned cart to shopping cart

To better understand this topic let’s understand the key pieces of data exchanged from Commerce Cloud and Marketing cloud.

  1. Master Data – Products & products Hierarchies, Customer & Consent
  2. Transactional Data – Saved Carts, Abandoned cart and reviews

To drive more sales SAP marketing Cloud creates product and offer recommendation applying some Machine Learning Algorithms on top of Master and transactional data. These Recommendation are published on Commerce Cloud Storefront pages and tracks the visibility and success of recommendation and sends the Impression and click through data to Marketing cloud. These key figures are used by marketing experts to evaluate the effectiveness.

OOTB SAP Marketing provides three main Algorithms:

  1. Top-N Query– With this algorithm you can recommend customers top viewed products, top sellers and recently viewed product.
  2. Association Analysis– used to discover hidden analysis in large datasets, this grouping is based on browser session.
  3. Collaborative Filtering– It computes the similarities between consumers by considering their interaction.

Building a Recommendation Model:

Building a Model in 4 simple steps, below are key parameters that builds a recommendation model:

Under Manage Recommendation section select appropriate OOTB scenario and configure with the below parameters

  • Recommend Products– Find the right product based on the algorithm used (Example: TOP Sellers (Interactions))
  • Filter Results– Remove any unwanted recommendations, typical example is removing the products already in cart (Optional)
  • Position Products– Used to assign ranks and push products of a certain brand on TOP (Optional)

Below is a typical example of a Top selling product recommendation model

Results of Top selling products and top viewed products:

Conclusion

Recommendation allows to provide recommendation in real time across multiple sales channels this brings more sales by understanding user interactions.

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