What Is MDM (Master Data Management)?
MDM (Master Data Management) refers to initiatives aimed at centralizing and maintaining consistent "master data" across an entire organization.
Master data consists of core data that serves as the foundation for business operations, such as customer, business partner, product, and organizational information.
It is common for data to be stored differently across departments or systems; for example, the same business partner might be recorded as "XX Co., Ltd." in the sales department and "(Co.) XX" in the accounting department. The purpose of MDM is to resolve such inconsistencies and redundancies, defining a single, "authoritative" master record for the organization.
The main features of MDM are as follows:
Establishing a Single Source of Truth (SSOT)
MDM defines the single, correct source of data that the entire organization should reference. By aligning disparate customer information from various departments into a unified standard, it ensures that every department perceives the same reality. This helps reduce operational rework caused by discrepancies in understanding.
Data Cleansing and Elimination of Duplicates
This process involves determining whether multiple records with different notations refer to the same entity and consolidating them.
This prevents duplicate registrations and redundant outreach, leading to improved data accuracy.
Foundation for Data Governance
MDM establishes rules for who registers, updates, and manages data, ensuring that data quality is maintained continuously. MDM is not a one-time setup; it functions as a mechanism to preserve quality through ongoing operations.
What Is a CDP (Customer Data Platform)?
A CDP (Customer Data Platform) refers to a foundation for collecting and integrating various customer-related data and storing it in a state that can be utilized for marketing and sales initiatives. It is characterized by its ability to aggregate information from diverse touchpoints—such as website browsing history, email open rates, sales meeting history, and purchase data—centered around the individual customer.
A CDP plays a role in connecting integrated customer data to practical applications by linking with various tools that support the execution of initiatives, such as Marketing Automation (MA), SFA, and BI tools.
It can be said that the focus is placed more on 'bundling data to make it easy to utilize' rather than simply 'organizing data correctly'.
The main features of a CDP are as follows:
Integration of Diverse Touchpoint Data
It collects customer behavioral data dispersed across multiple channels, whether online or offline, and bundles it into a profile for each individual or company.
This makes it possible to transform fragmented customer understanding into a comprehensive, multi-dimensional view.
Connection to Initiative Execution
It outputs integrated customer data in a format that can be utilized for specific initiatives such as segmented distribution, personalization, and scoring.
By linking with MA and SFA, it realizes a consistent, data-driven approach.
Accumulation and Updating of Behavioral Data
Because customer behavior changes daily, a CDP continuously ingests data to keep profiles in an up-to-date state. This allows for initiatives that capture changes in customer interests and consideration phases.
Differences Between MDM and CDP
While MDM and CDP share the commonality of 'integrating data', there are clear differences in their objectives and approaches. The differences between the two can be understood as follows:
Difference in Purpose: Accuracy vs. Utilization
MDM aims to ensure the accuracy and consistency of core data referenced across the entire organization. In contrast, CDP aims to utilize customer data for marketing and sales initiatives. It is easier to understand if you view the former as a defensive foundation and the latter as an offensive foundation.
Difference in Data Handled: Master Data vs. Behavioral Data
MDM primarily handles master data, such as customer names and account information, which changes relatively slowly. In contrast, CDP mainly handles activity data, such as behavioral history and response data, which changes daily. The nature of the data targeted by each is different.
Difference in Primary User Departments
MDM is often led by IT or data management departments and operated as a foundation to support data quality across the company. CDP tends to be led by marketing or sales departments and is utilized for the purpose of enhancing the sophistication of their initiatives.
Difference in Approach to Data Quality
MDM is premised on improving the quality of the data itself through data matching and cleansing. On the other hand, while CDP excels in functions for aggregating and utilizing data, it is said that the accuracy of data matching and the correctness of the master data, which are prerequisites for integration, are not necessarily guaranteed.
What is important here is that the two are not in conflict, but are inherently complementary.
No matter how advanced a CDP's customer data utilization may be, if the underlying master data is inaccurate, the precision of that utilization will hit a ceiling.
For example, if the same account is registered as two separate companies, both the target of initiatives and the history of engagement will be fragmented.
The results of data utilization are significantly influenced by the quality of the data that serves as its foundation.
Common Challenges in B2B Customer Data Utilization
There are significant differences in how customer data is handled between B2C (consumer) and B2B (corporate) sectors.
In B2B, the primary entity is the company, and the structure involves multiple contacts and departments linked to a single client. This characteristic creates challenges specific to B2B data utilization.
The Difficulty of Corporate Data Consolidation
Company names are often fragmented due to various factors, such as the presence or absence of legal entity status, variations in spelling, and registrations at the branch or department level. Accurately determining whether entities are the same company is considered more complex than consolidating individual consumer data. If this determination is incorrect, sales history and engagement status become fragmented, preventing a unified organizational understanding of the customer.
The Hierarchical Structure of Companies and Contacts
In B2B, multiple decision-makers and contacts exist within a single company. Simply aggregating data based on individuals makes it difficult to see the overall picture at the corporate level, such as which companies are being approached. The need for a data structure centered on companies is a challenge unique to B2B.
The Necessity of Connecting with External Data
Data held internally (first-party data) alone is insufficient to capture the latest status of existing clients or information on potential customers with whom there is no prior contact. It is necessary to connect with external corporate information (third-party data), such as company location, size, and industry, to supplement internal data.
Data Obsolescence
Corporate information changes over time due to relocations, mergers, acquisitions, and organizational restructuring. Even if data is cleaned once, leaving it unmaintained leads to obsolescence, resulting in misguided approaches and lost opportunities. A mechanism for continuously updating data to the latest state is essential.
What these challenges have in common is that they all relate to the quality of master data—specifically, whether companies are correctly and uniquely identified and managed in their latest state. Establishing this foundation, which precedes utilization via a CDP, is particularly critical in B2B.
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Customer Data Platform Capable of Master Data Management
As discussed, MDM is a framework that supports data accuracy, while CDP is a mechanism that supports data utilization; ideally, you should not have to choose between the two.
In particular, B2B customer data utilization requires both the maintenance of accurate master data centered on companies and a utilization platform that translates that data into actionable strategies.
Therefore, it is essential to adopt the concept of developing a B2B customer data platform equipped with master data management functions. Specifically, a platform that meets the following requirements is recommended.
A Mechanism to Uniquely Identify Companies
The premise is to have a platform that eliminates variations in notation and duplicates, allowing for the unique identification of the same business partner.
The accuracy of this identification determines the precision of all subsequent data utilization.
Integrated Management of Master Data and Utilization
It is desirable to handle accurate master data management and customer understanding—including behavioral data—as well as strategy execution in an integrated manner without fragmentation. By ensuring the foundation and utilization are seamlessly connected, high data quality is directly reflected in the precision of your strategies.
Continuous Supplementation and Updating via External Data
It is important not to rely solely on internal data, but to connect with high-freshness external corporate information to continuously update the master data. This enables approaches that capture the ever-changing reality of your business partners.
By establishing such a foundation, it is possible to balance the strengths of CDP, which is its utilization capability, and the strengths of MDM, which is its data quality, within a B2B context. Rather than being constrained by tool names or classifications, designing a foundation from the perspective of creating a state where accurate and up-to-date customer data can be centrally managed and utilized with the company as the axis is considered to lead to results.
Conclusion
MDM is a defensive foundation that ensures data accuracy and consistency, while CDP is an offensive foundation that leverages customer data for initiatives. The two are not in conflict but are complementary. Particularly in B2B customer data utilization, there is a demand for a foundation that can realize both the maintenance of accurate master data centered on companies and its utilization in an integrated manner. It can be said that establishing a B2B customer management data platform capable of master data management is important for enhancing the results of data utilization.
Our customer data integration solution, uSonar, is a solution that supports the foundation of such B2B customer data management. Through a unique code system called LBC (Linkage Business Code), it performs high-precision corporate data matching that eliminates variations in notation and duplication, making it possible to centrally manage customer information scattered within the company on a per-company basis. By seamlessly supporting everything from master data maintenance to utilization, it addresses the challenges of data utilization unique to B2B.
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