Do you recall the magic medicine Mary Poppins had? It tasted like anything you fancied. When poured from one bottle, it became lime cordial for Jane, strawberry for Michael, and even rum punch for Mary Poppins herself.
Today’s marketers aim for a similar effect with their content and offers—making experiences feel personal for every customer. Without magic on hand, they rely on software. Customer data platform or data management platform, for instance.
At first sight, a CDP and a DMP are very similar tools. They both help you collect data from multiple sources and use it for precise targeting and personalization. However, they deal with distinct types of data, which reflects on implementation and use cases.
Which of the tools is better, should you use both, or neither one is needed for that particular goal of yours? Let’s figure this out step by step.
What is a Customer Data Platform (CDP)?
A customer data platform (CDP) creates a unified database where every one of your customers has a profile.
Profiles combine information about your customers and their interactions with your company across channels and touchpoints, all collected following their preferences.
You can connect your CDP with other systems that rely on the information stored in the customer profiles to personalize marketing campaigns, website content, and customer services, at scale.
Main Features and Capabilities of CDPs
The customer data platform is a relatively new type of software. This is why, the feature set varies significantly from vendor to vendor.
While some of the solutions are built around identity management as a core capability, others seem to focus on managing tags that collect data.
For instance, CDPs such as Tealium and Segment function as data integration tools.
Lytics and Redpoint are quite robust and help with marketing campaign orchestration and personalization.
In the enterprise segment, you can find even more comprehensive CDPs provided by Salesforce, Microsoft, Oracle, and Adobe.
To help you get an idea of the most advanced capabilities that you can find in a CDP, we’ll list a bunch of outstanding features of Adobe RT-CDP.
The complete list of RT-CDP features with detailed descriptions is available on the Adobe site. Here are the features worth highlighting:
- Unified people and account profiles, combining personal and company data.
- Real-time profile enrichment, adding data to profiles as soon as activity happens.
- People & account identity resolution for accurate person-to-account matching.
- Marketing-friendly segmentation, user-friendly drag-and-drop segmentation canvas.
- Data collaboration, privacy-friendly data partnerships not reliant on 3-party cookies.
- Standardized data taxonomy, ensuring that data is compatible, unified, and accurate.
- Vendor tag management, to collect/send data from/to all available platforms.
- Data labeling, to ensure appropriate private and public data access and use.
- Data usage enforcement, leveraging automatic alerts about data misuse attempts.
- Customer consent management and use of both known and unknown identifiers.
- One-to-one personalization for granular and timely experience personalization.
- Behavior-informed experiences, triggering real-time responses to conversion events.
- AI-powered insights and propensity scoring, empowering profile-level predictions.
- In-context reports and metrics, out-of-the-box reports, charts, and dashboards.
These and other features enable companies with large customer bases to deliver hyper-relevant experiences with speed and accuracy. Now, let’s see what you can do with the help of a CDP.
When to use a CDP?
Let’s look at an example of including a CDP in the customer experience personalization process for an e-commerce business.
Say you have an online store running on Adobe Commerce.
You want to optimize every step across your customer’s journey—from their first anonymous visit to doing regular purchases.
With Adobe RT-CDP, you can do that.
You connect your Adobe Commerce store to Adobe RT-CDP. Your store becomes both a data source and a destination for the CDP. It uses the first-party data collected from the store to enrich customer profiles.
With every action a visitor takes in your online store, their profile in the CDP becomes more detailed and up-to-date.
As soon as they search for a particular product, view the page of the product, create an account or log in, add the product to the cart, and go to check out—it’s reflected in their profile right away.
Upon receiving every piece of new data the CDP ‘considers’ if it should add this particular shopper to one of the audience segments (or remove them). It also ‘considers’ if a particular trigger should work at each step and defines what offers to display, what cart price rules to apply, or what discounts to offer, you name it.
For example, a shopper can be added to the Nike Fan audience after browsing this brand’s shoes. Next time they visit your store’s home page, they’ll see a customized banner.
This particular person will see a Nike banner featuring shoes instead of a brand-neutral default banner that might be featuring something of no particular interest to them.
Similar profile updates and segmentations happen inside CDP every time new information is collected about every customer.
As data is accumulated, the profile becomes more robust and granular. So, you can optimize every step of your customer’s journey based on both historical and real-time in-session data.
What is a Data Management Platform (DMP)?
A data management platform (DMP) collects and consolidates pseudonymous data about audiences visiting 3-party, 2-party, and your own online properties.
The platform can help you segment audiences to improve targeting and build lookalike audiences to broaden the reach of your marketing and advertising campaigns.
Most often DMPs work in tandem with advertising platforms helping companies optimize and scale customer acquisition.
To build and extend audiences, DMPs source information from data brokers, marketplaces, aggregators, ad exchanges, and data enrichment services.
Main Features and Capabilities of DMP
DMPs have been in use for a long time. Among the most advanced solutions, there is Adobe Audience Manager, which seamlessly integrates with both Adobe and non-Adobe applications.
Another solution is Salesforce DMP (Audience Studio), which offers versatile customer data management capabilities.
One more player, Oracle BlueKai, on the other hand, prioritizes data activation and audience segmentation for advertising purposes.
In a nutshell, DMPs function as data pipelines. They collect information from various sources, transform it, and deliver it to multiple destinations.
Despite variations among DMP solutions, their capabilities are generally similar:
- Data normalization organizes data into a common format, removing redundancy.
- Data enrichment enhances data quality by adding additional data points.
- Data segmentation categorizes data into distinct groups based on similarities.
- Profile merging consolidates user profiles that share a common identifier.
- Audience creation groups user profiles with common attributes to form target audiences.
- Taxonomy creation helps organize and structure data in a hierarchy.
- Data activation sends DMP segments into tools for targeted advertising.
It’s crucial to keep in mind that audiences are made using anonymized IDs, like device IDs, cookies, or hashed email addresses. These IDs don’t directly show a person’s private information.
When to use a DMP?
Typically, you would use a DMP to enhance your programmatic advertising within your partner’s network.
You connect your DMP to a Demand-Side Platform (DSP) that automatically buys ad impressions on your partner’s websites. The DSP and DMP synchronize unique user identifiers between their databases.
This synchronization allows your DSP to utilize the audiences you’ve created in the DMP for precise targeting and the purchase of more relevant ad impressions.
When your partner’s website sends bid requests to your DSP, the DSP compares the data about the website visitors with the information about target audiences from your DMP.
DSP decides whether to bid on an impression for a specific visitor or not, based on the most comprehensive data set available to your company.
It’s important to note that you don’t have specific information about the individuals in your audience, nor do you know who the visitors to your partner’s website are.
However, if the software identifies a match between pseudonymous identifiers in your audience and your partner’s site visitors, it proceeds to purchase an ad impression.
What is the difference between CDP and DMP?
As it has been mentioned above, the main difference between the two platforms is in the ways of handling data of different types:
- 1-Party Data is collected directly by your company from its own interactions with customers or users. It comes from sources like website visits, mobile apps, CRM systems, and customer surveys. It typically uses personally identifiable information (PII) such as email addresses, names, phone numbers, and customer IDs. It may also include behavioral data like browsing history and purchase behavior.
- 2-Party Data is obtained through partnerships or agreements between two companies. In this arrangement, one company shares its 1st-party data with another. For example, a retailer might share its customer data with a manufacturer for joint marketing efforts. This data can include a variety of identifiers, including PII, depending on the agreement between the two companies, and include behavioral data and demographic information.
- 3-Party Data is collected by data providers that are not directly affiliated with the company using the data. These sources gather information from various online and offline channels, such as social media, public records, and online behavior. It often relies on pseudonymous identifiers, such as cookies and device IDs, to protect users’ privacy.
CDPs primarily focus on known customer data, including personally identifiable information (PII). And DMPs focus on pseudonymous third-party data collected from external sources.
Let’s summarize the difference between the tools in a DMP vs. CDP Comparison table.
| Characteristics | Data Management Platform | Customer Data Platform |
|---|---|---|
| Application | Focuses on attracting customers by improving ad targeting and simplifying media buying. | Covers the complete customer journey, including attracting, keeping, and managing customer relationships. |
| Data Types | Uses partially anonymous data, mainly 3rd-party data enriched with masked 1st-party data. | Handles identifiable data, primarily 1st-party data, with some 2nd-party data from partners. |
| Use case | It’s mostly used for pseudonymous audience segmentation and creating lookalike audiences. | It’s used to build a comprehensive and up-to-date 360-degree view of identifiable customers. |
| Profile Identifier | Utilizes anonymous digital IDs (non-PII), like cookie IDs, IDFA, etc. | Generates customer profiles with lasting IDs (PII), such as customer ID, name, email, address, etc. |
| Data Retention | Stores data for brief periods mainly for advertising targeting. | Keeps data for extended periods, accumulating information over customers’ lifecycles. |
| Data Privacy | Poses a significant risk of privacy regulation violations. | Has a low risk of violating privacy regulations. |
In a world with stricter privacy rules and no more third-party cookies, both Customer Data Platforms (CDPs) and Data Management Platforms (DMPs) are changing.
CDPs are good at handling data directly from customers and respecting their privacy choices. They successfully help companies follow privacy laws and offer personalized experiences.
In contrast, DMPs using third-party cookies for tracking face challenges and must find alternative methods to collect data while complying with laws.
Conclusion
Deciding between Customer Data Platforms and Data Management Platforms for your marketing needs can be difficult.
Both options have advantages, and your specific requirements will determine which one is the right fit for you.
Whether you’re already using one of these platforms, considering a switch, or just starting—it can be puzzling. And we’re here to help.
If you opt for Adobe Experience Cloud, Axamit can assist you in implementing and customizing Adobe RT-CDP. Our team provides technical support throughout the entire process and can help your employees ramp up the required skills to use it effectively.
FAQ
Does Gartner have a Magic Quadrant for customer data platforms?
As the technology is still new, Gartner has not released a Magic Quadrant for CDPs yet.
How does DMP work with CDP?
DMPs and CDPs can work together effectively. DMPs concentrate on third-party data for advertising and targeting, while CDPs centralize first-party customer data for personalization and retention. Combining them enables you to manage marketing campaigns for both acquiring new customers and keeping existing ones.
