Scores Overview and Score Builder


After completing this lesson, you will be able to:

  • Understand the key features of scores and create the rule-based scores


A score is a key or aggregated value calculated in answer to a specific question, for instance, how loyal is a given customer? The basis for score calculation is data, such as demographic, behavioral, experience, market, or any other type of data. Scores can be consumed in different marketing applications, like Segmentation, Contact Profile, Campaign Execution, Lead Management, and more.

Key Capabilities

Scores Process Flow

Types of Scores

There are two types of scores in SAP Marketing Cloud –rule-based scores and propensity-based scores.

A rule-based score is based on a rule model, which is a combination of rules. Rules are defined based on company policies and best practices in the field and experience. The score value calculation is based on an aggregation of the outcomes from all valid rules. A rule is valid if all conditions are met.

A propensity-based score uses a predictive model, which is based on predictive algorithms and historical data to calculate scores that give you insights into your contacts' future behavior.

 Rule-based ScorePropensity Score
ConceptBased on rules and conditionsBased on a predictive model

Rule are defined based on company policies, experience, and best practices

A rule model contains several rules

Each rule consists of several conditions


The predictive model is trained on historical data to detect patterns in customer behavior

Score value calculation

Calculated as an aggregation of the outcomes from all valid rules

A rule is valid if all conditions are met

Calculated from the trained predictive model

Score Builder

This image shows the process of creating or adapting existing scores in Score Builder.

Scores: Create a new score and adapt an existing score for contacts using heuristic rules and define where the scores should be used.

SAP Marketing Cloud comes with 4 pre-delivered scores: Best Email Sending Time, Email Affinity, Best Push Notification Sending Time, and Push Notification Affinity for the segmentation profile, All Consumers. You can also copy these scores and adjust them to your needs. You can find these scores in the list of all scores in Score Builder.

Rule Models: To define a new score or enhance an existing one, you need to create or maintain rule models. With a rule model, you specify how the score for a contact is calculated. The rule model contains one or more rules and each rule has conditions. You can create different rule models for different target populations within one score.

Simulation:After the scores and rule models are set up, preview the score results by selecting sample target groups to see score distribution displayed as a histogram. You may also refine rules and check histogram again for new results.

Consume: Use scores in apps such as Segmentation to rank contacts.

Creating Scores and Usage

Now let’s learn how to create a rule-based score with the Score Builder app.

In this tutorial you’ll learn how to:

  • View pre-delivered score
  • Create custom scores
  • Define score value categories to make scores easier to consume
  • Consume scores in different applications like Segmentation

Click the following link to take the tutorial: Enable Now Tutorial

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