What Are the Tradeoffs Between DMPs, MDMs and CDPs?

The marketing technology landscape is increasingly difficult to navigate. The number of tools available rises markedly each year, adding to the already-bewildering array of three-letter acronyms used in digital marketing. 

Alphabet Soup: Decoding DMPs, MDMs, and CDPs

Data platforms, broadly speaking, are no different. The market offers a variety of data collection software, including data management platforms (DMPs), master data management solutions (MDMs), and customer data platforms (CDPs). All three ostensibly aim to achieve similar goals:

  • Gather and manage customer data from various sources.
  • Provide richer insights about those customers.
  • In their own ways, provide data and insights back to the business. 

But go one level below that veneer of similarity, and the resemblance fades fast. Before adding a data platform of any kind to their tech stacks, business leaders must understand how these solutions differ, the parts of the organization they impact, and the outcomes that should measure against them.

Defining DMP, MDM, and CDP

To understand the fundamentals of the DMP, MDM, and CDP and their desired outcomes, let’s look at Gartner’s definition of each:

  • Data Management Platform: A DMP is software that controls data flow in and out of an organization. It supports data-driven ad strategies, such as segmentation.
  • Master Data Management: MDM is a technology-enabled discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise’s official, shared master data assets. 
  • Customer Data Platform: A CDP is a marketing technology that unifies a company’s customer data from marketing and other channels to enable customer modeling and optimize the timing and targeting of messages and offers.

Side by side, it’s clear that each solution offers its own range of capabilities geared toward specific goals. Still, it’s pretty tricky to compare and contrast based on these descriptions alone (whoever said identifying the right data technology to power your strategic growth initiatives is easy?).

Selecting the best solution(s) for your business means deeply understanding how these platforms handle different yet essential marketing and business tasks. It’s also why well-defined use cases are crucial to the success of any technology selection, implementation, and ongoing utilization.

The Tradeoffs: When To Use a DMP, MDM, or CDP (and When Not To)

The rise of digital channels where consumers engage with brands — on websites, mobile apps, social platforms, etc. — drove the creation of solutions like DMPs, MDMs, and CDPs. These solutions allow marketers (and publishers) to recognize people by their different proxies and stitch them together for a single view of the customer.

While DMPs, MDMs, and CDPs all serve a data unification function for the business, the underlying architecture and practical utilization of each are quite distinct (and, in some cases, not practical for use at all).


DMPs were explicitly designed to improve the quality of programmatic ad targeting and were once a widely adopted and crucial piece of the ad tech ecosystem. These solutions rely on third-party cookies to collect anonymous audience data from multiple sources and bucket that data into broad segments using algorithms and selective methods of identity resolution. DMPs also pass those segments to programmatic buying platforms to inform ad targeting against high-reach audiences.

However, evolving consumer privacy regulations and the demise of third-party cookies means DMPs are going the way of the dodo — even as they race to re-architect and re-invent themselves for this new world.

Some vendors have already announced plans to sunset their DMP offerings, which could signal the beginning of the end for programmatic advertising. It also means companies dependent on third-party data and DMPs for user tracking and targeting will have to re-evaluate their digital marketing strategy and pivot to tools that leverage consented data if they want to survive (and thrive) in the post-third-party cookie era.


MDM software acts as a single source of truth for various types of business data, including consented customer data. Using batch processes to find connections between different data sources and reconcile them, MDMs create a “golden record” of customers and their various attributes: name, location, address, purchases, etc. By pooling data into a single point of reference, an MDM gives teams across the company (customer service, finance, sales, product development, etc.) the data they need to meet their business needs.

However, this so-called golden record is a bit of a misnomer. It’s actually a “golden association” of a lot of data to one master ID with varying degrees of certainty (email matching has a higher degree of certainty than device matching, for instance).

Moreover, the lack of user interface (UI) for segmentation, activation, and analysis is fine for the IT team but not so fine for marketers, publishers, and other business users to extract much value (okay, use at all) from the customer view created by MDM solutions. These teams can’t execute efficiently when forced to wait on IT and other technical resources for the data they need to engage with customers in the moment.


CDPs are the newest player in this so-called data platforms section of the market. The CDP sets itself apart from DMPs and MDMs in two key areas:

  1. the activation-first nature of single customer view it provides organizations and;
  2. the user-focused interface designed to make the data accessible to marketers, publishers, and other growth-focused teams for journeys, campaigns, and other orchestration programs. 

The first-party data that customers and prospects have consented to drives CDPs.

They use distinct methods of identity resolution to determine when two or more profiles are the same unique individual and then merge those profiles into one persistent profile. Since this consented data is unified and updated in real-time and made accessible via a UI, business users can activate it instantly — in segments, with campaigns and personalization, and via analytics — while achieving better compliance with GDPR, CCPA, and other privacy regulations at the same time. 

Which Technology Is Right for Your Organization

None of the technologies described above is a silver bullet capable of solving all customer data problems. Since each solution varies in terms of its functionality and capabilities, business leaders need to understand the areas in which they excel, the parts of the organization they impact, and the outcomes they are meant to achieve.

Developing clearly defined use cases can help decision-makers narrow in on these critical factors and ultimately select the right solution for their business.

When employed correctly, use cases describe the current state, target outcome, supporting activities, and relative complexity required to successfully reach marketing or business goals. Going through this exercise can help business leaders level set on where they are today and make more deliberate choices about what solution will work best for their organization going forward.