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Transcript

In this video, I’ll review the use cases for partner data support in the real-time customer data profile with specific focus on the pre-visit, off-site prospecting use case. These are the topics I’ll cover. If you have not already done so, I encourage you to review the Partner Data Support Overview video that provides a good background on the deprecation of third-party cookies and the emergence of newer technologies to support the key use cases impacted. Data partners have had several years to pivot their technology to fill some of the gaps as a byproduct of third-party cookie deprecation. The good news is that key acquisition and enrichment use cases can be supported by both data partners and ÃÛ¶¹ÊÓƵ’s real-time CDP in this new era of cookie lists. There are separate videos that cover each of these use cases in depth. This video focuses on off-site prospecting of new customers. I’ll start with showing a diagram and explaining the workflow for this use case. It starts with some initial planning, such as the number and cadence of prospect profiles you expect from the data partner, which identities you’ll require downstream, and whether these identities are tied to widely accepted, durable identifiers. Once that part is figured out, there’s licensing to address between you and the data partner. After the licensing, the partner builds the prospect list based on your requirements. Steps 3 through 6 represent the workflow in the real-time CDP. You’ll use familiar workflows for data modeling, ingestion, profile creation, audience building, and audience activation to destinations accepting partner IDs. Now I’ll hop into the experience platform and show you how to handle the implementation of this use case. I’ll start with identities. There’s a specific identity namespace to be used for partner data called partner ID, as you can see here. Because partner identifiers are based on probabilistic models and are subject to churn, they are kept separate from the identity graph in real-time CDP. The intent of this use case is to acquire new customers, and some of the prospects will become customers. So in effect, we want to keep these profiles separate from the deterministic or first-party profiles. I’ll cancel out of this modal, and I’ll show you the identity that has already been created in my instance of platform for a partner data source. Next, I’ll discuss data modeling, specifically the XDM and schema that will be used for the data partner source for this use case. I’ll select Create Schema in the upper right corner, then Browse. I’ll filter the class by partner. When I do this, I see the XDM individual prospect profile class. This is exactly the class I want to choose for this schema and this use case. This schema allows you to ingest partner profiles that are treated separately from first-party data profiles. I’ll select this from the list, and then I’ll select Assign Class at the top right. Now I’ll add a field group to my new schema. I’ll filter this list by partner. ÃÛ¶¹ÊÓƵ provides a predefined field group, or you can create your own. I’ll select the first field group, and we’ll look at the fields in the preview first. Looks good, I’ll add this to the field group. All the partner profiles are found under this node right here. There are additional nodes for industry-specific attributes, as you can see here. Further down is the partner ID. This is the field you’ll want to mark as the primary identity for this schema. There’s only a single identity namespace option available. That’s because our system is designed to ensure there’s no mixing of prospect profiles with first-party profiles, so it’s a nice guardrail. I’ll cancel out of the schema creation workflow, and I’ll show you an existing schema, which is like the one I’ve been building right now. As you can see, it’s set up like the schema I just showed you in the workflow, and the partner ID is set as the identifier. Also, the schema is enabled for profile. Considering the type of data used for this use case, and all the partner data sources for that matter, data governance is a crucial element. I’ll select policies under privacy. Now, toward the bottom of the labels list, there’s a predefined third-party item for partner ecosystem. This is what you’ll want to use to restrict the marketing actions for partner data sources. Now I’ll go back to the schema we just reviewed. I’ll select the labels link at the top, and the third-party policy has been applied to all the field group nodes for partner attributes. Now that the schema and data governance labels are in place, it’s time to create a dataset. One has already been created in my experience platform instance, so we’ll take a look at it. Once in the dataset, I’ll select the last 30 days to see more activity. I noticed some uploads on July 24th and 25th, and below I can see the status of the batches. This is the same as viewing batches for other types of datasets in experience platform. I’ll click through one of them to see the details. Okay, so we’re ready to ingest the partner data. We can use any file-based pathway to get partner data into platform. I’ll show you where these are in the interface. First, I’ll go to sources under connections. When I click on cloud storage, it advances to the available connectors for that category. You’d more than likely be using an S3 right here, or at the end of this group there’s an option for SFTP. From workflows, you can select map CSV to XDM schema if you’re working with small files or if you’re testing. I’ll launch the workflow to show you what that looks like. On the detail step, make sure you choose the correct dataset name. On the next step, you can either choose a file on your computer or drag and drop one to the drop zone right here. After that, you’d go through a mapping step, but I’m going to cancel out of this workflow since I won’t be ingesting new partner data. Let’s jump to viewing prospect profiles. To reinforce ÃÛ¶¹ÊÓƵ’s commitment to separate third-party profiles from first-party profiles, a dedicated accordion menu exists. It’s labeled prospects. I’ll select profiles underneath. Next, I’ll select a profile ID to view the content, so it works similarly to the profile viewer for your first-party profiles except that it’s limited to just partner profiles. Another distinction for partner profiles is that our system applies an automatic time-to-live cadence to this data. Every 25 days, the prospect profiles are deleted from the system to ensure data partners refresh the data regularly. One of the key benefits to managing partner prospect profiles in real-time CDP is to centralize your audience strategy in a single system. Like prospect profiles, prospect audiences are kept separate from your first-party audiences. I’ll select audiences under prospects. Once that loads, the existing audiences display in the browse list. I’ll select create audience in the top right to show you that the experience for creating new audiences here is the same as it is in other locations. The main difference you’ll notice, that is if you create audiences on your first-party profiles, is that these are based solely on the prospect profile and not the XDM customer profile or individual profile. I’ll expand this and then expand the USAAM node. From here, I can drag and drop a partner attribute to the builder canvas and define it. I’ll cancel out of here since I’m not creating a new partner audience. Last, we can activate the audience. I’ll select a pre-configured S3 account that’s used explicitly for partner audience activation. Next, I’ll select activate audiences from the three-picker menu next to it. On the select audiences step in the workflow, only prospect audiences display. I’ll also mention that this respects the data usage policy I applied earlier, third-party. The remaining workflow is the same in terms of scheduling and mapping. After that, daily batch jobs will be sent out. I’ll cancel out of this since I won’t be activating my audience. This concludes the workflow for implementing the offsite prospecting use case in the real-time CDP. Hopefully, you feel confident getting this set up for your organization. Thanks and good luck!