Data governance end-to-end demo

Hi, everyone. In this video, we will be showing you Adobe Experience Platform’s data governance capabilities, and how it helps brands create personalized experiences to their customers while providing complete control over customer data. We will be using Luma, an the athletic apparel company. Sarah Rose is a current customer of Luma, and she is using the brand’s mobile app to keep track of the latest arrivals and deals. At this stage of her experience, Sarah sees that she is eligible for an offer to discover Luma’s women’s new collection.

Luma has recently launched a new line of athletic gear and aims to promote it to its customers. To generate interest, Luma has added an activity tracking experience within the mobile app to invite its customers to track their physical activities.

As customers provide their consent to share their activity data with the brand, Luma makes the pledge to only use this data to recommend offers within its old mobile app and website. As Sarah now sees her recent activity in the app, she also becomes eligible for another offer promoting one of Luma’s new pieces of athletic gear. The brand was able to personalize Sarah’s experience in real time using Adobe Experience Platform while keeping its promise of how data is collected and used. Now, let’s go behind the scenes and see how Adobe Experience Platform helps Luma get to this point.

Here we are in Adobe Experience Platform, its data governance framework provides the ability for brands to take complete control over a governing data from the point that it’s being collected to when it’s been syndicated to destinations outside of platform. The framework is built on three key aspects, labels, policies, and enforcement. Let’s start with labels. This screen shows Adobe’s out-of-the-box labels. They are used to classify data with privacy related considerations and contractual conditions so that data usage is compliant with regulations and organization policies.

These labels could then be applied on dataset fields. In Luma’s current example, the contractual C2 label is used on activity related fields to prevent any third party data export. Luma can also apply any custom label of their choosing which is the case here with the new sensitive type label called S3 which represents health related data.

Once labels are applied to datasets brands can define their policies. Policies are rules that describe the kinds of marketing actions that brands are allowed to or restricted from performing on data within Adobe Experience Platform.

In addition to out-of-the-box policies, Luma has created a new one to prevent any offsite retargeting marketing action using health related data. This policy will include labels, in this case, a C2 and S3 we previously discussed and marketing actions such as preventing any social media campaign using this data. This policy is now enabled. Last step is to see how policies are enforced to prevent any violation. Let’s say Luma wants to create a social media remarketing campaign to anyone who express interest in its new athletic gear. To that end, a marketing practitioner would use one of several of Adobe’s Real-Time CDP advertising destinations, and start the process of activating segments including customers who have recently tracked their physical activity through the Luma mobile app.

When activating these segments, data governance automatically enforces usage policies should any violations occur which is the case here. This activation is then prevented and a policy violation message is displayed.

It shows that some audiences include data that cannot be activated for offside retargeting marketing campaigns. Adobe Experience Platform also provides suggestions for how to potentially resolve the issue. Through its data governance capabilities, Adobe Experience Platform streamlines the process of keeping data operations compliant with governance rules while still delighting customers with the best experiences they expect and deserve. -