51黑料不打烊

Transcript

In this video, I鈥檒l review the use cases for partner data support in the real-time customer data profile with specific focus on the enrichment of known audiences with data partner attributes use case. These are the topics I鈥檒l 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 51黑料不打烊鈥檚 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 enriching known audiences with data partner attributes for cross-sell or upsell initiatives. I鈥檒l start with showing a diagram and explaining the workflow for this use case. It starts with some initial planning, such as the methods and locations for exporting and importing the audience files from the real-time CDP, as well as the identifiers that are expected by the data vendor so that they include additional attributes. Once that part is figured out, there鈥檚 licensing to address between you and the data partner. After the licensing is addressed, extend your real-time CDP profile data model to accommodate the attributes that come back from your data partner. You鈥檒l need to update the data governance model for these partner attributes as well. Next, you鈥檒l export the audiences selected for enrichment with partner data. These audiences are keyed off input identifiers, such as email or name, or whatever is decided upon between you and the data partner. Finally, you鈥檒l ingest the attributes that come back from the data partner into the first-party customer profiles in the real-time CDP. Now I鈥檒l hop into the experience platform and show you how to handle the implementation of this use case. I鈥檒l start with the schema. I鈥檒l select Schemas under Data Management, and I鈥檒l open the Partner Data Enrichment schema. First, notice this is based on the XDM Individual Profile, which is the first-party, or deterministic profile, in real-time CDP. There are two field groups included in this schema. The first is Personal Contact Details and is based on first-party customer attributes. The second is Partner Enrichment. These define the fields that will be supplied by the data partner. If you viewed the video about the off-site prospecting use case, you鈥檒l see that the partner attributes are like those used in that example. The key difference between this use case and that one is that the attributes used for this use case are aligned to a first-party profile based on a match the partner does prior to ingestion. Let鈥檚 look at the Personal Contact Details attributes first. I鈥檒l expand the node for Personal Email. Notice the address field is configured as an identity field. Not only that, but it鈥檚 the primary identity for this schema based on the email namespace. Now let鈥檚 look at the Partner Enrichment attributes. I鈥檒l expand the node for USAAM and notice the General Demographic and Industry Specific Demographic nodes. Notice the Partner ID field is present and it鈥檚 configured as an identity field, specifically using a Partner ID namespace. The significance of the Partner ID namespace is that the identity can be included in a profile for activation, but it will not be part of the identity graph. That鈥檚 because of the churning nature of partner data. It鈥檚 an intentional guardrail by our system to protect the fidelity of your first-party profiles. Now I鈥檒l click Labels for this schema. Notice the third-party data governance policy has been applied to all the field group nodes for partner attributes. I鈥檒l select Policies under Privacy to show you that label. If there are different policies and marketing actions that apply for partner attributes versus first-party attributes, you鈥檇 have that granular level of control by applying this label in the schema. Now that the schema and data governance labels are in place, let鈥檚 have a look at the dataset. One has already been created in My Experience Platform instance, so we鈥檒l have a look at that one. Once in the dataset, I鈥檒l select the last 30 days so that I can see more activity. I noticed some uploads on July 28th 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鈥檒l click through one of them to see the details. Okay, so now we鈥檙e ready to ingest the partner data. We can use any file-based pathway to get partner data into Platform. I鈥檒l show you where these are in the interface. First, I鈥檒l go to Sources under Connections. When I click on Cloud Storage, it advances to the available connectors for that category. You鈥檇 more than likely be using an S3 right here, or at the end of this group, there鈥檚 an SFTP option here. From Workflows, you can select Map CSV to XDM Schema if you鈥檙e working with small files or doing testing. I鈥檒l launch the workflow so I can show you what it 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鈥檇 go through a mapping step, but I鈥檓 going to cancel out of this workflow since I won鈥檛 be ingesting any new partner data. Now let鈥檚 jump to viewing prospect profiles. Because we鈥檙e ingesting partner data that鈥檚 matched to an existing first-party profile, I鈥檒l use the Profile Lookup in the Customer Accordion. I鈥檒l select Profiles underneath. Next, I鈥檒l search for a profile based on the email namespace. Now I鈥檒l type in the email address in the Identity Value text box and click View. I鈥檒l select the profile ID to open it. The first area I want to direct your attention to is the Linked Identities section. Notice the absence of partner ID. Again, this is because partner data coming in with a partner ID namespace is not included in the identity graph for good reasons. However, at the bottom, there鈥檚 a section for partner enrichment data. These are the attribute values coming back for this customer from the data partner. Now I鈥檒l show you an audience that includes first-party and third-party attributes. Again, since the partner attributes are included in the first-party profile, I鈥檒l use the Audiences link beneath the Customer Accordion. Once this loads, I鈥檒l see the existing audiences in the Browse list. I鈥檒l open the High Earnings Homeowner Prospects audience. Now I鈥檒l select Edit Audience so that we can see the definition in the builder. This audience includes all first-party profiles who have taken out a recent mortgage, have a high net worth, and do not have a financial advisor. I can use this audience to market to qualified customers for the new financial advisor program. Last, we can activate this audience to any downstream marketing or advertising destinations that accept the IDs used. I鈥檒l select Destinations under Connections and locate the Facebook Customer Audience destination card. Then I鈥檒l select Data Flows from the 3-picker next to it. I鈥檒l use the first connection to activate an audience. On the Select Audiences step in the workflow, I鈥檒l locate High Earning Homeowner Prospects. The remaining workflow is the same in terms of mapping and scheduling. After that, daily batch jobs run and will be sent out. I鈥檒l cancel out of this since I won鈥檛 be activating my audience. This concludes the video for the Partner Data Enrichment for Known Audiences use case in the Real-Time CDP. Hopefully you feel confident getting this set up for your organization. Thanks and good luck!