CDP vs DMP: How to choose the right platform for your business

Leveraging customer data is essential for modern businesses that want to remain competitive. With data management tools and technology evolving rapidly, it can be hard to keep up with the best data storage and software options. For example, do you know the difference between CDP and DMP systems?

Let us guide you through customer data platforms (CDPs) and data management platforms (DMPs) so that you can understand where they both fit in the modern landscape of customer data management. After comparing CDP vs DMP, you will be able to confidently choose which platform is the best fit for your business.

Understanding DMP vs CDP: The customer data storage question

As customer data storage needs have increased in complexity, specialized data systems have become necessary to manage different needs. Although CDP and DMP systems are both designed to handle customer data so that companies can analyze their customer base, they serve different purposes.

At the highest level, the difference between CDP and DMP storage could be characterized as the difference between marketing and advertising. While CDPs offer a deep and lasting view of existing users and customers, a DMP collates transient demographic information about target markets and audiences. Therefore a CDP is most useful to teams looking to understand and improve their product, whereas a DMP helps teams design and optimize advertising.

Let’s explore the customer data platform vs data management platform question in more depth by taking a closer look at the tools themselves.

What is a CDP?

When developing your product or brand, you will have access to a wide spectrum of information on new and existing customers. This information could come from any number of sources, including page views, purchasing patterns, or app usage statistics. Refining your product or outreach to appeal to those customers requires some means of consolidating and organizing these individual sources of customer information.

A customer data platform allows you to solve problems like customer duplication, tracking, and personalization for customers across many channels, while closely controlling data to meet privacy regulations. It also enables identity resolution, an important process for improving data quality and refining customer experiences.

The data input into a CDP is usually first-party data (more on this later), which means it has higher value and imputes greater responsibility to your brand. CDPs require a high level of customer data security, corresponding to the sensitivity of their stored data.

For a deeper dive into CDPs, read our article What Is a customer data platform?

What is a DMP?

The first steps in brand advertising involve sifting through customers as a statistical distribution, rather than individual contacts with detailed data points. A data management platform collects data from a wide band of sources; however, it doesn’t allow you to identify individual customers. Instead, it combines anonymized data from large-scale customer data vendors to give a view into potential advertising targets and a reflection of conversion rates for existing campaigns.

DMPs are often thought of as “cookie jars,” a reference to the fact that most of the data suitable for a DMP comes from browser cookies that track website usage. This means DMPs can offer only limited insight into your brand or product. They may contain data about clickthrough rates in relation to particular ad campaigns, but they can’t generate something like a sales funnel or user experience analysis that would result from tracking individual customer interactions.

The data in a DMP is much less valuable on an individual basis than that in a CDP. This is primarily because most data used by DMPs is available from vendors, and is therefore replaceable. Data stored in DMPs also has a high rate of expiry. This is not only due to privacy controls and vendor terms but also because anonymized market data frequently changes as a result of seasonal effects or large-scale market changes.

When to use a CDP vs a DMP

With the parameters of each of these customer data systems now defined, it’s time to consider what your data needs are specifically. Data is a resource for solving problems, whether used to model financial forecasts, develop product features, or find new sales leads.

To determine the ideal tooling to solve your problem, first, define your question or goal, identify the data that you have access to or could gather, and decide how you will use that data to approach the problem. While your data and company start to spin up, a CDP fills the getting-to-know-the-data role quite well. A DMP can be introduced later to act on insights from the CDP and maximize advertising conversions. In all likelihood, any company of sufficient scale will want to use both CDPs and DMPs, so that they can continue customer data collection while also expanding the customer base.

Defining the data space

With so much talk about data, it is important to understand the different types of data and their uses. We’ve already mentioned first-party and third-party data, but a good understanding of what these are is crucial to understanding how the customer data space is developing. In any case, it’s worth getting a deeper familiarity with different types of customer data when contemplating your storage system.

First-party data

This is the personal, internal customer data collected by your business with the consent of the customer.

You have sole access to your first-party data, and this gives you unique insight into your market share that no other competitor could gain. On the other hand, with modern privacy regulations like GDPR and CCPA, this type of data confers responsibility to anyone who collects and maintains it. These two factors combined make properly protecting and controlling access to first-party data crucial to its usage.

Second-party data

This is a rare category of data. Second-party data is any first-party data collected by another entity and then shared with your firm as part of a contract. You will have the same legal and ethical exposure from handling the data while gaining less value from it.

While it’s unlikely that data of this type could be leveraged for marketing or advertising capacity, any contract where you handle second-party data will almost certainly require the same data controls you would want to have for your own first-party data, and it therefore has similar resource demands.

Third-party data

The ‘third party’ in this data is typically a massive advertising vendor, like Meta or Google, which has enough cookie-tracking volume to provide highly specific demographic information as a service.

Other vendors specialize in refining third-party data and can provide high-value resources as part of a subscription. Some recognizable vendors in this category include Clearbit and Zoominfo. This data is much less valuable, so systems controlling it can be as simple as vendor-provided web accounts. However, if you do want to bring third-party data into your own ecosystem to supplement analysis work, requirements for controls and security are less rigorous.

Remember the price tag

While first-party data is generally cheap to collect — the only additional costs to storing it are server space and infrastructure overhead — third-party data can be quite expensive. The contents of a DMP are mostly valuable at tremendous scale, which means vendors operate by large volumes and correspondingly large sales. DMP providers often follow a similar strategy, such that the software itself is intended for big companies with deep war chests.

Third-party data remains a strong advertising tool, but it's startup costs can be prohibitive to smaller-scale projects.

The CDP value model

Personally identifiable information (PII) is at the core of CDP functionality. It allows you to create a historically-tracked picture of your customers. As your data scales up, the resolution and value of this data store compounds on itself, tracking the journey of individual customers for a given version of the product. As more data is collected over time, historical resolution across versions provides additional avenues for potential analysis.

In this way, a CDP acts as a value multiplier for your customer data. Even non-customer data can be augmented as a CDP spools up — most CDPs are designed to maximize this functionality by absorbing information across a huge range of data sources. When choosing a CDP, make sure your candidates support ingestion capabilities that match your existing data-generating tools.

The DMP value model

Unlike the temporally-organized CDP, a DMP delivers a short-term data stream that is constantly updated, reflecting current market conditions. Rather than using a DMP to store and accrue value from customer data, it offers a way to quickly convert semi-public third-party data into market share via advertising.

Exploring real-life CDP and DMP use cases

When exploring the usefulness of customer data platforms vs data management platforms, examining real-life examples can help put their use into perspective.

Wyze - Unlocking revenue growth with a CDP

Founded in 2017, Wyze sells smart devices, such as the Wyze Cam, directly to consumers at competitive price points. Their mission is to make smart technology available to everyone.

Wyze uses the RudderStack CDP to ingest customer data from six different sources across their entire user journey. This data is cleaned and resolved to create the Customer 360 views that can be leveraged by predictive AI models. The marketing and sales teams then activates this data to deliver personalized recommendations, new features, and subscription campaigns that have resulted in increased revenue.

Princess Cruises - Creating targeted ads with DMP

Despite being the third largest cruise line in the world, Princess Cruises still has a much simpler customer journey than Wyze. Nonetheless, they still wanted to invest in a solution that would allow them to analyze their available data and improve personalization.

Using the Adobe Audience Manager (Adobe’s DMP), Princess Cruises is able to centralize data from booking forms, CRM systems, and staff notes. They can then use lookalike modeling to understand client user preferences for activities, services, and voyages and identify new customer targets.

With the Adobe Audience Manager, Princess Cruises created campaigns that targeted high-value new clients as well as encouraged previous customers to explore new cruise destinations and activities.

Modern developments in data storage

Both government legislation and user expectations about data privacy have shifted in recent years, with a profound effect on how customer data must be handled. GDPR, CCPA, and iOS 14.5 changes are notable examples of a large trend towards privacy rights biting into the world of cookie tracking that is the core of DMP functionality.

As a result of the shrinking supply of quality third-party data, many companies find themselves increasingly reliant on their own first-party data to do the heavy lifting of demographic research that was available from major third-party data vendors.

The future of CDP platforms involves responding to these ongoing market changes. Many CDP providers are pivoting towards products that could plug new holes in their data systems. This has led to CDP models that can “bundle” the function of several parts of the data stack into a CDP — including the use cases of a DMP.

Although these unifying changes are still quite new, CDPs are beginning to segregate back into old-school, modular systems highly targeted to customer data, as discussed in this article, and more monolithic systems that bundle a great deal of the data stack.

Confidently navigate the CDP vs DMP question with RudderStack

Using customer data is imperative to creating a competitive advantage and driving incremental revenue, so you want to get it right. Without an effective data management platform and strategy, you won’t be able to gain the maximum value from your data.

While there is overlap between CDPs and DMPs, ultimately you need to pick the one that will support your business goals. For example, consider if third-party or first-party data will fulfill your marketing needs. Third-party data from a DMP can be useful for building advertising campaigns that focus on a broader, unknown audience. However, if you want to build a highly personalized, targeted advertising campaign, secure and ethically collected first-party data is what you need.

As a Warehouse Native CDP, RudderStack is built from the ground up for data teams that want to create foundational efficiencies and drive business growth. Say goodbye to expensive and frustrating data wrangling and build a flexible, secure, and robustly integrated CDP within your existing data warehouse. RudderStack collects first-party data from every stage of the customer journey and integrates it within your warehouse to provide a comprehensive customer 360 that is available to downstream tools in real time. Our flexible architecture enables you to break down data silos, maximize the use of your current tech stack, and invest in the future with agile scaling and no vendor lock-in.

You can keep up to date with data storage on the RudderStack blog (try our internal search feature!), or you can review articles in our learning center to build a foundation of knowledge in the field.