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What is a data management platform (DMP)?

A Data Management Platform (DMP) is key to organizing and optimizing your data operations. Learn how centralizing data can help you gain actionable insights, improve marketing efforts, and drive successful customer engagement.

Data Management Platform (DMP)

Data Management Platform (DMP) Definition

A DMP is a data management software platform that collects, organizes, and deploys data from customers and audiences for use in online campaigns.

Here are the main characteristics of a data management platform: 

  • Stores all customer and audience data in one central home 
  • Collects data from online, offline, mobile, and other sources 
  • Cleans, formats, and organizes data into audience and customer profiles 
  • Creates a better understanding of their demographics and preferences 
  • Feeds data to digital advertising, marketing, and publishing systems 
  • Improves ad targeting, content personalization, and data operations optimization

Why use a DMP?

Collecting a large volume of customer and audience data is not enough. That data must be made usable for analytics and automated marketing programs. A data management platform helps with this work by:

Centralizing customer and audience data:

A DMP creates a single source of truth that can be used by sales, marketing, analytics, publishing, and more.

Normalizing customer and audience data:

A DMP ensures different types of data collected from a diverse range of sources can all work together.

Improving customer and audience data quality:

A DMP helps identify and fix data quality issues so you can accurately target and personalize campaigns.

Who uses a DMP?

A cloud data management platform can be used by individuals and teams within every industry, typically in one of the following three roles.

Marketers and advertisers

Marketers and advertisers

The most common users of data management platforms. They typically use DMPs to build and target audiences, manually optimize marketing campaigns, and feed quality data to automated advertising systems. 

Publishers and content creators

Publishers and content creators

They can use DMPs to build richer audience profiles and better understand who their readers are. They can also directly sell this audience data, or use these insights to increase the price of advertising on their content.

Analysts and business executives

Analysts and business executives

They can use their centralized and enriched audience profiles to make better strategic business decisions, to automate processes, and as a tool for improving data quality and ensuring proper data governance across multiple use cases.

What are common DMP use cases?

Audience targeting
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Precise audience segmentation
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Personalization and recommendations
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Audience extension and retargeting
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Improve ad campaign performance
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Conduct advanced analytics
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Monetizing customer and audience data
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What types of data do DMPs use?

An enterprise data management platform ingests a wide range of data sources, including:

First-party data

Data that is directly collected from a source that is typically operated by the organization (e.g. its website or app).

Second-party data

Data that was collected by another first-party source (e.g. another website or app) that is purchased or otherwise obtained.

Third-party data

Data collected from multiple sources and made available for use by many organizations (e.g. data on an ad platform).

How does a DMP work?

Step 1: data collection
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Step 2: data processing
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Step 3: data organizing and segmenting
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Step 4: data activation
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Step 5: data analysis and reporting
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What are the 4 types of data management?

Hierarchical databases

Organizes data according to a hierarchy with different levels equating to different categories and subcategories of information. Data management software uses a hierarchical database management system.

Network databases

Stores data within a network that spans multiple locations. Organizes data in a graph-like structure. Ensures data remains consistent between users, departments, and locations.

Relational databases

Stores data in tables with rows and columns. These tables are connected via relationships. Electronic Medical Records are an example, and types of relational databases include SQL and mySQL.

Object-oriented databases

Stores data in objects that relate with each other. Typically used for complex data storage that requires significant control and management. Programming languages such as Python and PHP use this model.

What are examples of data management systems?

There are many data management systems available.

Data management platform examples include:

  • MySQL
  • SQL Server
  • Redis
  • Microsoft Azure SQL Database
  • Amazon RDS
  • MongoDB, Couchbase
  • Cosmos DB
  • PostreSQL
  • And many more

However, many of these are general-purpose tools that can be customized to meet a wide range of use cases. By contrast, a data management platform is a purpose-built data management system designed for the specific use cases outlined above on this page.

Is SQL a data management platform?

No. SQL is a programming language, and it uses a relational database management model. While SQL can be used to build databases, and while there is an SQL program that can be used as data management software, it is not the same thing as a DMP, which is a software platform that uses a hierarchical model and offers a more focused feature set and use cases.

CDP vs DMP

A Customer Data Platform (CDP) works similar to a DMP. Where a DMP typically focuses on working with customer and audience data where each individual is anonymized, customer data platforms typically focus on creating rich profiles of individuals who are named and identifiable.

This adds up to a clear difference between CDP and DMP across a few vectors:

 

  • CDPs are focused on creating profiles of named individuals. DMPs create audiences with anonymous individuals.
  • CDPs do not anonymize data, they use personally identifiable information. DMPs anonymize data.
  • CDPs store larger amounts of data over longer periods of time. DMPs only retain data for 90 days.
  • CDPs are more important for long-term campaigns that nurture individuals. DMPs are more important for shorter-term campaigns targeting audiences. 
  • CDPs compliment DMPs — it is a “both/and” conversation, not “either/or”.