Customer Data Platforms VS Master Data Management: How They Differ

Management of customer data has become increasingly important in the business world, and due to the increase in data volumes being generated every day, the need for strong data management systems has risen too. In this case, both master data management (MDM) and customer data platforms (CDP) are needed to ensure efficiency in data management. Many may not know whether to use customer data platforms or MDM in their businesses, but this comparison between the two technologies will give you a deeper insight on the same and therefore assist you to decide on when to use them.

  • What Is MDM And Customer Data Platform?

Customer data platform is a marketer-based management system, and it functions by creating a unified customer database, which can easily be accessed by other systems. Data from CDP is usually gathered from different sources whereby it gets cleaned and integrated to form a single profile for each customer. CDP enables real-time segmentation of personalized marketing and the single records prepared for each customer can be accessed through other marketing systems.

MDM, on the other hand, is a technological method used to identify, define and manage vital information about an organization. It does this by integrating the data gathered into a centralized point of reference. The data usually mastered by MDM systems include a set of permissible values, reference data and analytical data. This information helps in simplifying the decision-making process. A typical MDM does not usually provide information on omnichannel interactions, historical transactions, web clickstream data, and customer relationships. However, MDM is useful ensures consistent maintenance and distribution of information about your brand, people and locations. Since customers are the most important aspect of every business, MDM tends to overlap CDP in the provision of information to customers.

  • Other Differences

One major difference between MDM and CDP is that CDP captures all the details of a transaction including batch numbers, date and time a transaction was completed and customers details among others. However, MDM is more concerned with larger data integration from matching sets such as SAP, IBM, SAS, Oracle, Talend and Informatica among others. MDM products do more than identifying a characteristic of the key data objects. Based on different master data management best practices it is okay to say that MDM does more job compared to CDP when it comes to data integration and overall management. However, this will depend on the MDM tools that your MDM system have and its compatibility with your business needs.

Another difference between CDP and MDM is that MDM products tend to run more efficiently on SQL databases and works better with structured data. These mediums and characteristics help MDM products to manage and control standardized entity attributes. CDP, on the other hand, works well with unstructured, structured and semi-structured data which gets managed well on NoSQL system such as Hadoop. However, most integration suites or data matching sets such as SAS tend to support the NoSQL databases, and therefore Master Data Management might as well work with unstructured and semi-structured data.

  • Similarities

Both MDM and Customer Data Platforms require identity resolution function for the systems to collect data about a certain product or customer and then bring this information together into a single entry. MDM is more efficient in identity resolution, and this is the reason why some CDPs rely on MDM to carry out this function and bring forth a unified profile for all customers.

Also, both MDM and some CDPs are great when it comes to the creation of a golden record that carries vital customer data such as name and address. Again, master data management is superior when it comes to these function because it can easily match information from different systems to create the golden record. This is why it is referred to as a ‘master’ in data management. The information gathered by these two data technologies gets shared with other systems to ensure consistency is achieved.


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