Name: Understanding Segmentation in SAP Marketing Cloud
Uploaded: 2018-2-22
Duration: 526 s
Description: This video introduces you to the powerful segmentation tools of SAP Marketing Cloud that allow you to segment high volumes of customer data to identify audiences for marketing campaigns.

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<div><div><div><div><div><div><div><div><div>This video introduces you to the powerful segmentation tools of SAP Marketing Cloud that allow you to segment high volumes of customer data to identify audiences for marketing campaigns. </div></div><br></div><br></div><br><br></div></div></div></div></div>

Understanding Segmentation in SAP Marketing Cloud

In this video, you'll learn about the role of segmentation in SAP Marketing Cloud,  its benefits and key capabilities.  SAP Marketing Cloud segmentation helps marketers to narrow down their company's contact base and focus on target audiences.  This application provides real-time segmentations based on different criteria and operations.  Let's take a closer look at its functionalities.  By using simple drag and drop functionality,  marketers can easily create segmentation trees based on different attributes.  Powered by high performance SAP HANA,  the system provides real time visualization to help you explore your target audiences.  Segmentation allows you to use demographic,  transactional,  behavioral data,  as well as predictive information to narrow down your customer base. Predictive models and scores can help you segment audiences that are truly relevant.  Based on your segmentations,  you can create target groups which will be used in marketing campaigns.  Segmentation functionalities can be extended by different data sets and attributes to help marketers segment their target audiences more efficiently. The powerful segmentation capabilities of SAP Marketing Cloud provide you with various benefits.  Data is the new oil in this era.  SAP Marketing Cloud receives data from different sources and uses data to build customer profiles and predict customer behavior.  For example,  based on machine learning technology,  you can segment customers with high buy-in propensity and directly engage  them in a campaign.  Finding the right audience will also enable you to market more effectively to maximize efficient marketing campaigns and eliminate unnecessary spam. Target groups are created from segmentation models and can be directly consumed by campaign applications.  The process of identifying the right audiences to engage in them in campaigns has never been easier.  Let's now have a look at  how this works in practice.  On the home screen of SAP Marketing Cloud,  I open the Segmentation Models application.  Here I can see a list of all segmentation models already created in the system.  I click Create to create a new segmentation model.  The first thing I have to do now is to choose a segmentation profile which defines the base population and underlying data sources.  There are, for example,  all accounts for segmenting corporate accounts,  all consumers for B2C scenarios,  and all contacts for all individuals that aren't defined as a company.  As a coffee retailer, I target consumers,  so I choose all consumers as my base population.  On the left hand side of the segmentation application,  you see the list of attributes to segment your population.  They can be customized according to your business needs.  The interactive visualization section shows your segmentation structure.  Right now, it only shows the top node,  which represents the base population.  The preview section below shows real-time values of selected attributes or segments.  Let's consider a practical business scenario. As a marketer in an international coffee retail company,  I would like to run a campaign to re-engage German customers who have bought our products in the past,  but didn't buy anything in the past 90 days.  How can I do that?  First, I use the country attribute to filter out those customers not living in Germany.  Based on the power of SAP HANA,  we are able to see the real-time geographical results in the preview section.  I can simply change the geographical view to a bar chart view.  Here it shows that there are around 48,000 customers living in Germany.  After selecting DE and clicking on Keep, I create a segment for customers living in Germany.  To segment these customers who bought products before,  but not within the last 90 days,  I use the two attributes, interaction type and interaction date in the attribute group Interaction.  First I click the Attribute Interaction Type.  The results are displayed in the preview section.  If I don't find the right interaction,  I can also drag and drop the attribute to the segment.  Then I search for sales order and click Keep to identify customers who bought our products in the past.  Finally,  I drag and drop the attribute interaction date.  In the pop-up window, I specified the last 90 days as a custom period.  The data range tells me that I'm specifying a time period from today to minus 90 days.  Finally,  I press on exclude.  Now, the final segment contains customers who bought our products before, but not within the last 90 days.  In the last step,  I can create a target group based on the segment I built.  I can use this target group for campaign execution later on.  Let's consider another scenario.  As a marketer,  I would like to promote our barista products in both Germany and Austria.  To save marketing budget, it's important for me to address customers with high buying potential specifically.  How do I do that?  In SAP Marketing Cloud,  I can create predictive scores such as customer buying propensity  to help me identify potential buyers in my target audience.  This predictive model uses a trained data set to predict buying propensity.  After maintaining a predictive model for our barista product,  I'm able to consume it directly in the segmentation application.  First,  I create two segments by using the attribute country.  To get German and Austrian customers, I double-click Germany and Austria in  the geographical map.  To combine these two segments,  I can simply drag one segment on the other.  In the pop-up window,  I'm able to choose different sets of operations based on my business demands. After hitting merge, I create a segment with both German and Austrian customers.  To identify customers with high buying propensity for our Barista product,  I choose the attribute buying propensity under the attribute group scores. I choose the product Mr. Barista and the Lorenz Curve is displayed.  By specifying the 50%  top-ranked contacts,  I'm able to cover all the potential buyers.  And this leaves me to around 32,000 customers.  With this predictive functionality, I'm able to target my customers more precisely,  which saves me significant marketing budget.  After hitting Keep,  I get the final segment.  As a next step, I can create a target group based on the segment. and address that target group through campaign execution.  This concludes our video about segmentation.  Thank you for watching.