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CDP vs. DMP: Choose the right data platform for your needs

Using a platform to organize your customer data is essential for creating informed marketing decisions. Two such types of platforms are the customer data platform (CDP) and the data management platform (DMP). Understanding what each platform offers and how each works can help you determine the right one for your needs.

CDPs help unify a wide variety of customer data including historical, contextual, demographic, and behavioral information. This unified data is the foundation for gaining insights—from segmentation to customer predictions—that drive intelligent and personalized experiences. Different teams—including marketing, sales, and service—can discover a wealth of new personalization opportunities across different channels through insights and a persistent customer profile. DMPs collect primarily anonymous data to profile, analyze, and target online customers; these platforms help digital marketers make more informed media buying decisions and more effectively target campaigns.

These two systems are distinct in their use cases, users, and the data they collect.

The difference between CDP and DMP

CDPs and DMPs work in different ways to achieve different goals.

CDP

CDPs are used for creating personalized customer experiences by collecting and tying together customer data through personally identifiable information (PII)—like email addresses and phone numbers—to create a 360-degree view of the customer. The unified customer data, combined with artificial intelligence (AI), generates insights that optimize business processes and customer engagement in business-to-business or business-to-consumer settings.

The primary data source for CDPs is first-party data from customers who have directly interacted with the business online (through website interactions, campaign engagement, online purchases, and loyalty programs) as well as offline (through in-store purchases, in-person events). CDPs may also be able to use second-party data (sourced from businesses that collect and sell first-party data) and third-party data (collected through anonymous identifiers like cookies) in addition to first-party data.

Insights from CDPs are valuable not only to marketing teams for campaigns and churn analysis but also to sales and service teams who want to personalize customer experiences. For example, cross-sell or upsell recommendations can help a salesperson focus discussions on relevant products that a buyer might want. Next best action recommendations can help a salesperson personalize future interactions. Similarly, calculating a customer’s lifetime spend can help service organizations prioritize calls from high-value customers.

DMP

Digital marketing agencies and in-house marketing teams use DMPs to identify audiences by categories like demographic, behavior, or location in order to better target digital advertising campaigns.

DMPs aggregate high volumes of anonymous customer data originating from multiple sources. The primary data sources for DMPs are second- and third-party data. DMPs must work with anonymous entities like cookies, devices, and IP addresses to exchange information about audiences while protecting personal privacy. Because different companies—including competitors—can usually access the same anonymous data, a DMP does not provide a sustainable competitive advantage. Instead, it helps digital marketers better understand and target audiences.

CDP vs. DMP side by side

CDP DMP
Use case scenario
  • Omnichannel marketing, sales, and service geared toward individual conversion
  • Digital ad campaigns typically targeting anonymous audiences
Primary objective
  • Enhanced customer experiences through personalization
  • Improved targeting of digital ads
Primary users
  • Marketing, sales, and service teams
  • Digital marketing teams (either in-house or agencies)
Benefits and limitations
  • Flexibility to respond to changing trends
  • AI-driven segmentation and predictions to drive highly personalized experiences
  • Functionality to connect with other platforms for personalization and process optimization
  • Efficient integration of data from disparate sources
  • Accessible data that can be used by multiple teams within an organization
  • Designed to identify audiences for digital ad targeting
  • Ability to connect with other platforms for customer targeting
  • Ability to monetize by selling own data as second-party data
  • Limited identity matching because primary data source is anonymous
  • Not primarily designed for using first-party data
Questions that can be answered by each platform
  • Who are my high-value customers?
  • How I can personalize my interaction with this customer?
  • What products or services is this customer most interested in?
  • What is the next best action to take with this specific customer?
  • Which customers are at risk of churn?
  • What are the attributes of customers most likely to buy?
  • Where can I reach these customers online?
  • How can I effectively analyze large quantities of audience data to make smarter media buying and campaign planning decisions?
Primary data source
  • First-party data
  • Some advanced CDPs can use third-party data
  • Second-party data
  • Third-party data
  • Some advanced DMPs can use first-party data
Data lifecycle
  • Permanent data is initially gathered through direct customer engagement like a purchase transaction
  • Data is held for a long time
  • Transient and short-lived data is initially gathered through customers browsing the web or engaging with advertising
  • Data is held for a limited amount of time
Customer identity
  • Deterministic matching: a unique identifier (like an email address) determines which data is linked to a unique customer
  • Probabilistic matching: algorithms make data selections from anonymous user data, prioritizing segment and category over unique customer identifiers
CDP DMP
Use case scenario
  • Omnichannel marketing, sales, and service geared toward individual conversion
  • Digital ad campaigns typically targeting anonymous audiences
CDP DMP
Primary objective
  • Enhanced customer experiences through personalization
  • Improved targeting of digital ads
CDP DMP
Primary users
  • Marketing, sales, and service teams
  • Digital marketing teams (either in-house or agencies)
CDP DMP
Benefits and limitations
  • Flexibility to respond to changing trends
  • AI-driven segmentation and predictions to drive highly personalized experiences
  • Functionality to connect with other platforms for personalization and process optimization
  • Efficient integration of data from disparate sources
  • Accessible data that can be used by multiple teams within an organization
  • Designed to identify audiences for digital ad targeting
  • Ability to connect with other platforms for customer targeting
  • Ability to monetize by selling own data as second-party data
  • Limited identity matching because primary data source is anonymous
  • Not primarily designed for using first-party data
CDP DMP
Questions that can be answered by each platform
  • Who are my high-value customers?
  • How I can personalize my interaction with this customer?
  • What products or services is this customer most interested in?
  • What is the next best action to take with this specific customer?
  • Which customers are at risk of churn?
  • What are the attributes of customers most likely to buy?
  • Where can I reach these customers online?
  • How can I effectively analyze large quantities of audience data to make smarter media buying and campaign planning decisions?
CDP DMP
Primary data source
  • First-party data
  • Some advanced CDPs can use third-party data
  • Second-party data
  • Third-party data
  • Some advanced DMPs can use first-party data
CDP DMP
Data lifecycle
  • Permanent data is initially gathered through direct customer engagement like a purchase transaction
  • Data is held for a long time
  • Transient and short-lived data is initially gathered through customers browsing the web or engaging with advertising
  • Data is held for a limited amount of time
CDP DMP
Customer identity
  • Deterministic matching: a unique identifier (like an email address) determines which data is linked to a unique customer
  • Probabilistic matching: algorithms make data selections from anonymous user data, prioritizing segment and category over unique customer identifiers

Defining your goals

Think about your organization’s situation and goals before deciding between CDPs and DMPs.

  • Are you focusing on personalizing individual experiences or targeting an audience for digital ad campaigns?

  • What kind of customer data do you currently have and where is it stored?

  • Do you need to connect customer data and insights to other systems like business applications?

Answering these questions will help you determine whether a CDP or DMP is right for your business needs.

A preassembled and ready-to-go CDP for personalizing customer experiences

If a CDP might be the right fit for your organization’s needs, take a look at Dynamics 365 Customer Insights, the flexible and intuitive CDP solution from Microsoft.