Data-management platforms (DMP) are popular among advertisers, agencies, and publishers. They are complex pieces of software that incorporate many different components and features.
Let’s take a look at what components make up a data-management platform (DMP) and how they are connected.
What Is a Data-Management Platform (DMP)?
A data-management platform (DMP) is a complex piece of software that collects, stores, organizes, and reports on and exports data. It is mainly used by advertisers (brands and agencies) to improve the targeting of online media campaigns. Publishers can also use DMPs to optimize the monetization of their inventory (ad space) and personalize their websites with product and content recommendations. Because these platforms collect huge amounts of data, they are useful for performing advanced analysis on user behavior and cross-device and cross-channel attribution.
Read our 7suite case study to learn more about how to design and build a DMP.
Data Normalization and Enrichment
The data-normalization and enrichment process organizes the data into a common format and improves data value and quality. Data is normalized by gathering IDs from web cookies, removing useless or redundant data, and changing the schema of the incoming data into the DMP’s schema. Enrichment involves making data useful and relevant for users, such as turning an IP address into a geolocation and extracting the device type from the user agent string.
Profile Merging and Building
Incoming pieces of data are used to create new user profiles or are merged into existing ones. For example, if an incoming cookie ID matches a cookie ID found in an existing profile, then it, along with any other accompanying data, will be added to it.
The data-storage component receives and stores all of the incoming data, and then pushes it to the other components. Although the concept seems rather simple, the actual technical implementation can be challenging due to the large amount of data being stored, as well as the need to move it to other areas and prevent data loss.
Segmentation and Taxonomies
Segmentation involves grouping profiles by attributes (demographic data, location, device type, etc.), behavior (clicking on a link in an email), frequency of actions (visiting a web page at least three times a month), and many others. Creating taxonomies helps the DMP define the names of the various pieces of data that are similar in meaning. For example, instead of having two taxonomies like “user” and “visitor”, you could create or define one taxonomy (e.g. “user”) that represents both terms.
A user (advertiser, marketer, publisher, etc.) creates audiences in a DMP by combining various segments. For example, if a clothing brand wanted to promote its new line of dresses, it could create an audience that included the following: women, ages 18–35, who have purchased a dress in the past six months. Users can also create multiple variations of the same audience, but differentiate them by location, device type, etc.
Analytics and Reporting
Storing large amounts of data from various sources allows users to generate detailed reports about the performance of their advertising and marketing campaigns, as well as engagement and user behavior on their websites and mobile apps. Many DMPs allow users to perform lookalike modeling to find new audiences that include similar attributes and behavior to existing ones.
Integrations and Activation
Activating audiences is one of the main use cases of a DMP. Activation refers to sending or exporting audiences to other systems, such as demand-side platforms (DSPs) and supply-side platforms (SSPs) for online media buying. Audiences can be exported via server-to-server integrations with other tools and platforms and manually in batches (e.g. CSV files).
The user interface of a DMP is the screen that allows advertisers, marketers, data analysts, and publishers to interact with the various components of the DMP. For example, they can create audiences, define segments and taxonomies, and activate/export audiences via the user interface.