When marketing, analytics, and customer-service teams use different customer records, they can disagree about churn, contact details, or who should be excluded from a campaign. A single source of truth is the shared, authoritative data foundation they use instead of maintaining competing versions. An error can be corrected once and reflected wherever that data is used. section 4.4.4 section 4.2.1
In a composable marketing architecture, the marketing data lakehouse holds this foundation. A composable customer data platform (CDP) reads from it to create and activate segments rather than becoming a second large customer-data store. Audience definitions, personalization fields, and experiment configurations can then serve multiple channels without belonging to any one destination. section 5.4.5 section 4.2.1
A source of truth earns trust through more than centralization:
- Represent the customer accurately, including complex account, contact, or household relationships. section 4.4.4
- Monitor for duplicate fields, stale data, and logical inconsistencies before they disrupt live campaigns. section 4.4.4
- Govern sensitive data and introduce the shared foundation incrementally; reconcile old and new outputs before retiring legacy systems. section 5.4.5 section 5.5
From analysis to campaign
An analytics team adds customer-level segmentation labels to shared lakehouse tables. Because the composable CDP uses those tables, marketing can put the segments into live campaigns without rebuilding the model in a separate system. Analytics can also examine live audience membership and experiment labels to assess results or develop new models. section 4.2.1
Table 4.5 Data trust and reliability considerations
| Solution |
Considerations |
| Composable CDPs |
(+) Composable CDPs focus on connecting directly to your central customer profile rather than creating a secondary customer profile. Alerts and monitoring can be delegated to the marketing data lakehouse, which is helpful. |
| Marketing clouds/engagement platforms |
(-) While there are virtualized views, MCs require teams to manage a hosted customer profile, which may add latency and discrepancies compared to a primary customer profile used by analytics teams. |
| Monolithic CDPs |
(-) While there are virtualized views, monolithic CDPs require teams to manage a hosted customer profile, which may add latency and discrepancies compared to a primary customer profile used by analytics teams. |
| In-house builds |
(+) Build solutions often connect directly to the organization’s unified first-party data, which means they work on the same source of truth as analytics teams and other functions at the organization. This is often the deciding factor for companies that choose to build. |
Compare a CDP that connects to a central customer profile with platforms that maintain a hosted profile. The distinction matters because a second profile can introduce latency or discrepancies. section 4.4.4
The practical payoff is consistent decisions: fewer disputes over customer facts, more dependable personalization, and segments based on current data. Centralizing does not remove the need for data quality, monitoring, or governance; it gives teams one foundation on which to do that work. section 4.2.1 section 4.4.4 section 5.1.3
