In an increasingly digitalised environment, businesses are seeking to better understand their customers by relying on data. Integrating a Customer Data Platform (CDP) has become essential for centralising, unifying, and leveraging this information. In this context, the configurable Customer Data Model (CDM) plays a key role, especially for marketing teams. This model provides a simplified structure tailored to business needs, facilitating decision-making and campaign execution.
A Simplified and Accessible View of Data
The primary benefit of a CDM lies in its ability to simplify access to data for business users. Through a high level of abstraction, raw data, which is often complex and technical, is transformed into indicators and metrics suited to business needs. A library of pre-calculated indicators allows marketing teams to easily access essential information without having to manipulate raw data directly.
Ease of Use for Business Users
Another significant advantage of the Customer Data Model is the autonomy it provides to non-data specialists. By offering a “business” view of information, it becomes easier for marketing teams to select and use the most relevant targeting dimensions. This simplification reduces the risk of errors in audience selection and speeds up the deployment of marketing campaigns. Furthermore, the time to market for simple use cases is significantly reduced, thanks to the library of predefined indicators.
An Essential Preparatory Phase
Integrating a CDM requires a rigorous preparatory phase, particularly concerning the data layer. This phase must be anticipated from the project’s inception, following a thorough study of user personas. The goal is to identify business needs and prepare a tailored library of indicators. Additionally, a continuous enrichment process for this library, in collaboration with data teams, must be established to ensure the relevance of indicators over time.
Customer Data Model vs Data Lake
Unlike a data lake, which can sometimes be perceived as rigid, the Customer Data Model offers greater flexibility through a low-code approach. Marketing teams can thus create or adjust indicators without modifying the underlying data lake structure, making the model less intrusive and more adaptable to changing business needs. In conclusion, the Customer Data Model is a true asset for marketing teams, simplifying access to data and increasing their autonomy.