Data Management Platform (DMP)

A DMP, or data management platform, is a software tool used primarily in advertising and marketing to build profiles of anonymous individuals, store summary data about each individual, and share their data with advertising systems.

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What Is a DMP (Data Management Platform)?

A DMP, or data management platform, is a software tool used primarily in advertising and marketing to build profiles of anonymous individuals, store summary data about each individual, and share their data with advertising systems. 

Why Are DMPs Used in Advertising and Marketing?

DMPs are used to store, manage and analyze data about ad campaigns and audiences. A DMP connects to a DSP (Demand Side Platform) or SSP (Supply Side Platform) to purchase ads through ad networks. A DMP ingests anonymous identifiers for your customers, matches these against third party lists, builds a look-alike model with summary data, and selects similar anonymous individuals from third-party lists, and sends those lists to advertising systems. 

In short, a DMP is a platform for audience data. It’s useful for audience segmentation, building lookalike audiences, and optimizing paid media spend. It doesn’t store first-party data—most of the data it uses is third-party data stored in the form of cookie IDs and based on user behavior.

Who Should Use a DMP?

Marketers who are getting started with audience segmentation for digital advertising can get the most utility out of a DMP. The platform is good for building look-alike audiences based on a few key data points: For example, people who live in Albuquerque and own an iPhone.

Most marketers aren’t focused exclusively on digital ads, of course. That’s why it makes sense to integrate a DMP with other parts of the Martech stack, in order to cover the entire customer journey. Instead of the two data points above, a full stack would enable you to identify John Wick, who lives in Albuquerque, owns an iPhone, is currently researching Android handsets, and who recently bought a set of bluetooth earbuds from your online store. That type of granular data isn’t possible with a DMP.

What’s the Difference between a DMP and a Customer Data Platform?

A DMP can be a useful tool to have when building your marketing strategy. It’s a good first step to becoming a more data-driven marketer. But it works better as part of an ecosystem, not as a stand-alone solution. Let’s compare with a similar-sounding platform that is often equated to a DMP: the Customer Data Platform, or CDP.

While DMPs are focused on anonymized audience data, a CDP is built for all types of customer data. A DMP is for audience segmentation, while a CDP is for building a comprehensive, 360-degree view of named, individual customers.

The platforms have different capabilities to support their respective functions. DMPs, for example, don’t store first-party data or personally-identifiable information (PII). They are generally cookie-based and rely on anonymized data to create audience segments.

By contrast, a CDP can aggregate data from a host of different sources, including first-party data and PII. CDPs are built with security and privacy features that make them a safe repository for individual customer data. 

The differences extend to how each platform stores and retrieves data, as well. DMPs retain data for just 90 days. CDPs rely on long-term data retention to build robust customer profiles (thus the extra security).

DMPs work well for the function they’re intended for: Short-term tasks involving broadly-defined audience segmentation. For a detailed view of individual customers and intelligent orchestrating of the customer journey, a CDP is essential.

Fortunately, most CDPs can work together with any DMP. As long as the CDP can use the DMP identifier for its ID resolution, the third-party data from the DMP can be used to enhance the customer profiles in your CDP.

More To Explore

CDP Strategy

What is the CIO’s Role in Selecting a CDP?

CIOs should take a primary role to discuss the need for CDPs, the growth opportunities CDPs enable, and the due diligence on the scalability, security, and flexibility of customer profile data solutions.