Name: Understanding Score Builder in SAP Marketing Cloud
Uploaded: 2018-6-8
Duration: 260 s

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<div><div><div><div>This video will show you how to effectively use the Score Builder to create and adapt scores for contacts using heuristic rules. Typically, marketing professionals use scores in Segmentation to rank contacts and to address them later through personalized campaigns based on their score value. <br></div><div><br></div></div>NOTE: Your SAP Marketing Cloud interface might look slightly different, but the overall process stays the same.<br><br></div></div>

Understanding Score Builder in SAP Marketing Cloud

In this video you will be introduced to the score builder. Firstly, let's take a look at the key features of the score builder. As a marketing expert, you can take an advantage of a simple user interface. You can easily create scores based on rules and define outcome values for fulfill conditions. Scores can be defined for use and customer applications such as contact profile or customer journey manager, and they can have assigned semantics and restricted validity. Additionally, on the topic of performance, the outcome of a score for selected target group can be simulated and shown in a histogram. Further, the persistence of score values is possible for historical comparisons in trend analysis. Let's move on to the process steps and score builder. Initially, as a marketing expert, you want to get an overview on the existing scores. Next, you can also create a new score for specific purposes and define visibility in other applications. You have to create and maintain rule sets by defining rules or enhancing the existing ones. You can create different rule sets for different target populations within one score. Finally, you can 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. Now you can see what the Score Builder application looks like. Score builder incorporates the SAP marketing Cloud rule framework. Two predefined scores are shipped best email sending time and email affinity. By choosing a particular score, three tabs are available. Rule sets used to create and maintain the rules based on SRF vocabulary. Details used to view underlying semantics and using client application. Use to maintain score thresholds and define relevant client applications. The semantics parameters need to be selected when the score is created. Once the score is created, this parameter cannot be changed anymore because aggregation behavior is affected and could lead to different results. Semantics define how the score shall behave and which values are allowed. You can either keep the field blank or choose one of three options. Best contact time, best contact weekday, and channel affinity. Please pause the video to read more about the value ranges and how the score is calculated. Depending on semantics. Now let's see how to create a new rule set which will be used in score. After the score is created, click on the plus sign on the right upper side. This will open a rule set window which contains three parts rules, details, and a preview. Our goal is to create a rule which would be applicable for people aged 26 to 40 from Germany in USA, and will increase the score value when the contact opens a specific email or checks out on the website successfully. This maps to the interactions email opened and checkout successful. The rule would be valid for the interactions within six months. Click on the add rule and find type of interaction in the first field. After you find it in the third field, choose email opened and set the value to five and then condition. Click on duplicate on the right side. Now let's just change the type from email open to checkout successful and change the value from 5 to 8 because the interaction is stronger in the details area on the right side, specify that the score will be available only for customers from Germany and the United States. Finally, open the time frame for analysis and pick six months as a dynamic value to check how score can be beneficial in segmentation. Scroll down to the preview area. Choose age group 26 to 40 as a target group and click save. As you can see, the rules are applied to the target group as you released the rule set. Remember to choose the desired client applications where you want to use that score. Also, let's add a score category which will be presented in the contact profile for those with the corresponding score. Now we are in the contact profile application for user Lorie Campbell. As you can see, the score with 12 plus result is maintained on the scores tab. Thank you for watching.