DMP/CDP: What’s The Difference?
Data Management Platforms (DMPs) have been around for a long time. Especially among publishers. In recent years, a new acronym has emerged – CDP. Standing for Customer Data Platforms.
These are taking on an ever-growing market share. According to the CDP Institute, the market has grown by 23% in one year and there are more than 50 tech providers claiming to be CDPs.
What is a CDP and how does it differ from a DMP?
Unified customer experience is impossible without systematic management of customer information. Most data points are stored in a separate system that is not designed to share that information with anything else.
A CDP helps the publisher synchronize multiple internal and external data sources to a profile/customer. It gives the opportunity to get a real-time, actionable, and holistic picture. Based on this you can define strategies for how to best communicate and respond to the customer. The CDP contains personal identifiers used to target marketing messages and track 1:1 marketing to the identified user.
Unlike a DMP, which creates profiles for unidentified visitors, the CDP only works with identified visitors. This is of great importance to the quality of the data. With high-quality data, it is easy to build machine-learning models on top of it. By combining a DMP and CDP, you can let the machine-learning train the unidentified users thanks to deterministic data. The accuracy of the unidentified users will increase, which is beneficial for the advertiser.
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DMP/CDP: What’s The Difference?
Additionally, with the growth of programmatic, companies have become reliant on taxonomies to effectively target and/or block ads in real-time bidding. In short, standardized taxonomies drive higher levels of transparency and accountability in digital advertising.
Compared to a DMP, a CDP is much more advanced because it synchronizes with more internal and external systems, with the purpose of creating a holistic view of the user. Due to the fact that identified users are often based on the user’s address or personal/social ID, the user can be synchronized with external data sources, known as second-party data providers.
This can be anything from the car registry to external data providers/data exchanges to onboard user data. The result is that the publisher gets a more complete picture of the user. The most common DMP use cases for a Publishers are:
- Improved article recommendations. By understanding the types of articles a visitor reads most, the DMP creates personalized renderings of articles based on the interest of the user. Relevant articles for the visitor lead to raised pageviews/user and increased loyalty. The latter is necessary for the publishers who invest in a paid content strategy.
- Enable targeted advertising, which can increase revenue per impression and attract advertisers that can reach their own preferred segments. The IAB has standardized audience segments that all DMPs follow. Classification is crucial to making the digital advertising ecosystem function efficiently. There are three types of common taxonomies in digital advertising:
Content: Helps buyers make appropriate decisions about where to deliver their ads, ensuring that ads are served to the right place. It also helps publishers create and sell audiences.
Ad product: Helps sellers ensure that the ads delivered to align with their content, ensuring that the most relevant ads are served to their consumers.
Audience: Helps both parties match the audience, ensuring that ads are served to the right customers. - Brand new and unique ad packages, such as BMW owners.
- More accurate lookalike-audience ad packages.
- Advertising to specific customers via programmatic, Facebook, and Linkedin, often called custom audiences.
A publisher needs to identify the user, either by having carried out some form of digital purchase or registration. The latter is of strong growth. More and more publishers are starting to use a paywall to gain access to reading content on their sites. It can either be a free or paid model. These models are potentially road bumps in terms of traffic decrease for sites that launch this model. However, with identified users, new and unique advertising business might be launched.
Reading an editorial review—for example, a spring bike test—is a good indicator that the reader might have a purchase intent. With this first-party data, the publisher can create niche purchase integrity segments for advertisers traditionally created by a third party. The ability to create audience groups for advertisers (e.g. around Black Friday), means that the publisher can raise eCPM on the ad package.
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