DMP vs CDP Comparison: What`s The Difference?

Having personalization as one of their main functions, users can find data management platforms (DMP) and customer data platforms (CDP) quite confusing.

DMPs were originally created for advertising use cases, where the focus is always on audience management via their device IDs, IP addresses and cookies that are created from their buying engagements. In contrast, CDPs consolidate and store personally identifiable data of users, like name, email addresses, postal addresses, mobile numbers.

Therefore, both have similarities as they both influence customer buying behavior, but their functionalities are distinct enough to even make them strong allies. Here are some key differences between the two, that business leaders must recognize.

Comparison Table

According to Gartner, a data management platform is a software that controls the flow of data in and out of an organization. It supports data-driven ad strategies, such as segmentation.
According to Gartner, a CDP is a marketing system 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.
The Need
The requirement for DMP came into being when marketing leaders felt the need to target their audiences more precisely for advertising, as well as for broadening their reach. It started getting used to support users in comprehending information about customer psychographics and demographics, thereby shedding light on what customers find attractive and what encourages them to buy.
With the expectation of customers on the rise, the maturing market felt a strong need for an interface that’s web-based and was solely for marketers. It was required to be helpful for marketers in a more analytical sense, so that data collection, profiling, segmentation, and support could be eased, and smarter decisions could be facilitated. Besides, since marketing was growing at a tremendous pace, it was involving data integration and multichannel campaigns at a breakneck speed.
Built For
Advertising professionals, ad agencies and marketers need DMPs to avoid ‘ad blindness’ and to capture their targeted audience at the right time in the buying funnel through relevant messaging. Advertisers use it to deliver high-impact campaigns by centralizing client audience data so that better optimization programs and smarter media buying decisions can be taken based on audience analysis and latest campaigns. Marketers use it to build segments, audience mining, and tailor messages according to audiences’ prior behavior.
Built for marketers, CDPs are data hubs needed for extensively analyzing customer behavior as well as for unearthing business-oriented insights to enhance customer engagement. Since they centralize customer data from all types of systems, channels, and applications, CDPs today have turned into an information reservoir about customers. Besides, features like data modeling, data quality, automation, and real-time personalization make today’s CDPs a worthwhile investment for enterprises.
Data Ingestion & Management
Data is ingested from various client and media sources like marketing analytics, CRM, ad server, publisher partners and point of sale (POS). As a next step, imported data is matched with other data that originates from supposedly the same device. Data is also collected from mobile apps, client’s website, as well as other channels that use native apps. It is then augmented and enriched with 3rd party vendor data; private data exchanges are established. Additionally, organization and configuration for anonymization matching happens. Lastly, data is made available for execution.
Ingestion of data can happen from all kinds of sources, be it online or offline. CDPs can generate a comprehensive view of customers by piecing together several disparate customer data sources, including customers’ behavior and historical background, so that personalized experiences could be to created for them. This structured data from a CDP, is then delivered to other martech systems. It helps in enabling personalized messaging campaigns, as well as in profiling, segmenting and de-duplication of customer identities. The whole activity is aimed towards tracking the intent of customers.


Chief function of a DMP is to serve advertisements. It is designed to enable cookies retargeting and lays emphasis on anonymous segments and categories. DMPs give marketers, who are striving for maximum ROI from campaigns and optimized conversion, scalable insights via failproof data mining. Marketers use DMPs for:

  • Audience Extension— Using recognized prospects and customer attributes as a means for better identification and prospect targeting.

  • IdentiAd targeting— To extend and generate audiences for ad campaigns, including multichannel retargeting.
  • Personalization— To facilitate the creation as well as implementation of enhanced, more personalized messaging across marketing channels.
  • Ad-measurement— To report and figure out results, and offer appropriate campaign outcome data.
  • Customer Insights— Gather smarter insights about customers via data enrichment and indexing.
  • Exporting segmented customer lists for deriving business intelligence or executing campaigns
  • Channel Integration— Improve the prospect’s experience across various channels by offering a standard set of audience attributes and insights.


The main functions of CDPs are to collect, organize, consolidate, as well as offer customer data for advanced execution by a variety of personalization mechanisms or marketing techniques. CDPs are aimed at complete customer lifecycle and are therefore much more flexible than DMPs when it comes to the number of applications they can be implemented on. They are used by companies in a variety of ways like:

  • Recognizing and categorizing customer conduct, actions, and attributes throughout your offline and online systems.
  • Describing the profiles of customers and their management for use in the future.
  • Analyzing customer behavior for enhanced segmentation.
  • Examining customers’ purchase history and engagement habits for further recommendations relating to eCommerce or content.
  • Data management, that comprises of cleansing, validation, and integration
  • Predictive analysis to evaluate customers’future actions.
  • Exporting segmented records of customers for unearthing business insights or carrying out campaigns.

Get a free demo

See for yourself why thousands of enterprises trust us to bring their CDP vision to life. Pimcore is Gartner Cool Vendor. Get in touch.
Headquarter Austria
+43 662 230991

We will use your personal data solely to process your request. For a better-localized experience, we might share your data with certified solution partners in your geographical region. Read our privacy policy.