Most, if not all, organizations need help utilizing the data collected from various sources efficiently, thanks to the ever-evolving enterprise data management landscape. Often, the reasons include: 1) Data is collected and stored in siloed systems; 2) Different verticals or departments own different types of data; 3) Inconsistent data quality across the organization.

Implementing a central data management system, such as a master data management (MDM) solution or a customer data platform (CDP), can address most of these challenges. 

In this blog post, we will discuss the pertinent features of these systems and outline which system would best suit your organizational needs. 

Understanding MDM

Master data management is the practice of creating a centralized organization-wide view of data that becomes the trusted single source of truth to support an organization’s operational and analytical needs. MDM can be implemented using various MDM tools or custom-built using widely available cloud technologies.

Focus: The primary purpose of an MDM system is consolidating data from multiple data sources to create and maintain a single source of truth across the organization. This is why MDM is generally owned by the organization’s IT or data analytics organization under the CIO/ CTO’s or CDO/ CDAO’s purview. 

Data domains covered: MDM systems cover a wide variety of data domains, such as Marketing, Finance, Operations, Supply Chain, Human Resources, Products, and many more. There is no limit to the type of data that can be included in MDM. Hence, MDM can have a very large scope and can become very complex to implement and maintain. 

Key Use Cases:

• Data quality: MDM enables a high level of data quality across all six dimensions – Completeness, Accuracy, Consistency, Validity, Uniqueness, and Integrity.

• Golden records: MDM creates a single view of entities by merging and deduplicating the data, often called the “golden record.” The key consideration here is that a golden record can be made for any entity, such as Customers, Products, Assets, Clients, Employees, etc. 

• Compliance: MDM enables easy implementation of regulatory compliance by managing and tagging sensitive data and controlling its usage. 

• Cross-functional reporting: MDM enables centralized and reliable reporting about various aspects of business, such as Finance, Operations, Marketing, etc. 

Exploring CDP

Gartner defines customer data platforms as “software applications that support marketing and customer experience use cases by unifying a company’s customer data from marketing and other channels.” In other words, a CDP is a central data system that collects, unifies, segments, enriches, and activates customer data. 

I want to extend this definition to include “composable CDPs,” also known as “custom CDPs,” which comprise several tools, technologies, and processes assembled to achieve the essential functions of packaged CDPs.

It is important to note that when used in the context of a CDP, the term “customer” includes all types of audience (or personas) with whom an organization interacts, including but not limited to website or mobile app users, visitors, free users, partners, potential customers, and, of course, paying customers, clients, or consumers as applicable to the organization’s industry and businesses.  

Focus: The primary focus of CDPs is to enable marketing use cases, giving marketing teams the much-needed independence and freedom to perform their activities more efficiently. This is why CDPs are generally owned and operated by the Marketing division under the CMO’s org. 

Data domains covered: Given the marketing focus, CDPs generally cover data about customers/consumers. This data can usually be divided into:

1. Profile data (identity, demographics, etc.) 
2. Event data (behavioral data, inbound/outbound communication, etc.)

Data that cannot be linked with a user, is generally not covered in a CDP.

Key Use Cases:

• Single view of customer (customer 360): CDP enables the creation of a reliable single view of a customer created by unifying profile and event data related to each customer collected from a wide variety of sources, including first-party, second-party, and third-party data sources. This single view of the customer can be made available for multiple uses, such as segmentation, personalization, and marketing automation.

• Data enrichment (calculated or predictive): Based on the unified data about the audience, a CDP can enable the generation of derived data attributes to enrich the customer profile. Some examples include Engagement Scores, Lead Scores, Lifetime Value, Risk Scores (e.g., churn likelihood, fraud risk, etc.), predictive attributes such as propensity to buy certain products or services, Next Best Product/Action/Offer, etc. 

• Activation and democratization: Many advanced CDPs have features such as triggers and integrations to perform actions based on unified and enriched data present in CDP. Examples include automated marketing communication, internal alerts to the sales team about qualified leads, etc. The unified data can also be made available to various systems for use cases such as unified reporting and dashboards, data feed to operations systems, customer service and sales teams, etc. Many of these activations can be performed in real time as soon as the customer data is updated in the CDP.

• Business-user-friendly Interface: Most packaged CDPs provide an easy user interface allowing even non-technical marketing users to perform various advanced configurations such as defining derived fields, creating automations and triggers, and performing segmentation and personalization.

Which Solution Does Your Organization Need?

When deciding on the type of data management system you should implement in your organization, you should consider the primary use cases and goals you are trying to achieve. 

MDM would be the best choice if the focus is on enterprise data governance, data quality, and regulatory compliance, maximizing the value and usage of cross-functional data, or if cross-divisional collaboration is essential in your organization. Think “clean enterprise data.”

Implementing a CDP will make more sense if the focus is on marketing and customer experience or if the goal is to maximize the value of customer data to achieve the highest level of personalization (hyper-personalization), increase marketing effectiveness, and deliver consistent customer experience across all marketing and communication channels. Think “data activation.”

In conclusion, while both MDM and CDP solutions have robust data management capabilities, the difference lies in their scope and primary goals. 

Both an MDM system and CDP can collect data from multiple sources and unify it to give a single view of entities. They also have high-level technical features such as data ingestion, data manipulation, and data access; however, they differ in more nuanced features suitable for purpose-specific use cases as discussed above.

An MDM solution can cater to various data domains and business functions; however, a CDP focuses on audience data and acts as a single and exhaustive source of truth for customers and potential customers. Moreover, each of the two systems may have pre-built features to perform certain functions that might require elaborate configuration in the other system.

While it’s important to keep costs low and focus on the key use cases you are targeting, a judicious combination of MDM and CDP may help your organization not just to establish a robust data foundation, but also go after the holy grail of personalization, which would serve as a key differentiator.