What is the Difference Between a CDP and DMP?

Written by
Andy Pandharikar
April 20, 2022

Nowadays, you'll be hard-pressed to find a company that isn't trying to make the most of their data. As data volumes continue to grow, companies are looking for ways to manage and make use of all of this information. This is where customer data platforms (CDPs) and data management platforms (DMPs) come in.

A CDP is a system that collects, cleans, and unifies primarily first-party customer data from disparate sources. Once unified, the data can be used to build customer profiles, target marketing messages, and measure campaign effectiveness. A DMP is a system that collects, cleans, and unifies third-party data.

What Exactly is a CDP?

Suppose you are a company that wants to send a targeted marketing message to people who have visited your website but haven't made a purchase. To do this, you would need to know who these people are. A CDP can help you identify them by collecting data from your website and other internal sources, cleaning and unifying it, and then creating profiles of each individual.

A CDP is not just for digital data, however. It can also collect and unify data from offline sources such as customer surveys, CRM databases, or loyalty programs.

What Exactly is a DMP?

DMPs are used to collect, process, and analyze data from a variety of sources, including third-party data (data collected by other companies). These tools include Salesforce DMP, Cloudera, SAP Data Management, Snowflake, and many others. While there are many different DMPs on the market, they all have the same goal: to help businesses make better decisions based on data.

Modern data management platforms incorporate unstructured data processing, which is the ability to process data that is not in a predetermined format. This is important because unstructured data (such as text data and image data) accounts for 90% of all data. By processing unstructured data, DMPs can get a more complete picture of customers and their activities.

Why use a CDP over a DMP?

Data Management Platforms are great for sharing audiences, but they can't be used to store Personally Identifiable Information, such as email addresses or phone numbers, which can limit their usefulness for marketing purposes.

Customer Data Platforms, on the other hand, aren't built around sharing audiences between third parties, which means that they can be used to store PII. This makes them a more valuable tool for marketing purposes, as it allows businesses to keep track of customers and target them with relevant marketing content.

CDPs also store data in a single, scalable place, which makes it easy to access and analyze. This can be useful for businesses that want to track customer behavior over time or identify trends. On the other hand, DMPs generally have two data stores – one for all data and another for fast utilization of a subset of that data. This makes it difficult to analyze data in a timely manner.

Finally, CDPs capture raw data, with unlimited capacity, while DMPs store data like transactional marketing tools, with the resulting view being high-level and in aggregate. Additionally, DMPs only retain data for a short time, typically 90 days, while CDPs can retain data for an indefinite period.

How Commerce.AI Enhances Customer Data Platforms

The value of a CDP is all about the quality and quantity of customer data that's available. The more data you have, the better your chances of identifying profitable customers and targeting them with the right messages.

CDP users can augment their data with Commerce.AI's insights to identify trends and target customers with greater accuracy. For example, you might use Commerce.AI to learn that people who buy men's dress shirts are also likely to buy dress pants. Armed with this knowledge, a retailer could then send a marketing message specifically to those people, offering them a discount on dress pants.

The combination of a CDP and Commerce.AI can provide your business with a powerful tool for understanding your customers and creating more effective marketing campaigns.

How Commerce.AI Enhances Data Management Platforms

With access to a trove of data, including unstructured data, Commerce.AI can improve the performance of DMPs in several ways.

First, Commerce.AI can help DMPs to better understand customer behavior. By analyzing a variety of data sources, Commerce.AI can identify patterns and trends that would be difficult to discern with just structured data. For example, Commerce.AI might identify a new segment of customers who are particularly interested in a certain product or service.

Second, Commerce.AI can help DMPs to target customers more effectively. By analyzing customer data alongside external data sources, DMPs can develop a more complete picture of customers and their interests. This allows businesses to create more targeted and relevant ads, and even improve their product line.

Finally, Commerce.AI can help DMPs to measure the effectiveness of marketing and sales campaigns. By analyzing data collected before and after a campaign, DMPs can compare how well they performed relative to the market size overall, and identify any areas that need improvement.


Data is fueling the growth of businesses today, and companies are looking for ways to manage and make use of all of this information. This is where customer data platforms (CDPs) and data management platforms (DMPs) come in.

Commerce.AI helps both CDP and DMP users to better understand customer behavior, target customers more effectively, and measure the effectiveness of marketing campaigns.

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