Consumers buying products and services across various online channels leave a trail of every digital marketer’s most important asset — data. But this of data is worthless if it can’t be collected, organized and put to use.
That’s where data management platforms (DMPs) come in. DMPs allow marketers to understand customers and their purchasing behaviors better. This leads to more effective marketing campaigns that drive higher engagement and sales. With DMPs, marketers can glean insights into which campaigns drive the best results among target audiences.
This article looks at data management platforms in depth — what they are, why they are important, what they are used for and their future in a privacy-focused landscape.
Table of contents
- What is a data management platform?
- DMPs vs. CDPs
- Data protection laws
- The future of data management platforms
- Additional resources
Estimated reading time: 5 minutes
What is a data management platform?
A data management platform is exactly what the name suggests. It is a digital platform that allows businesses to collect, store and organize data that is then used and analyzed to drive marketing and other business decisions. DMPs collect data related to:
- Customer demographics.
- Purchasing history.
- Website clicks.
- The online registration forms they fill out.
- And other sources.
This information is then segmented to provide businesses with actionable insights and a clear understanding of customers and their purchasing habits.
While DMPs can use first- and second-party data, they heavily rely on third-party data from online sources. The differences between data sources are essential.
- First-party data is information collected directly from your audience, like website clicks, social media follows, likes and comments, email addresses, etc. It’s considered extremely valuable because it’s collected first-hand, assuring greater accuracy and availability.
- Second-party data is first-party data that someone else has collected and sold to you.
- Third-party data is gathered by entities that don’t have a direct relationship with the consumers whose data is being collected.
Once data is collected, DMPs organize it into segments so marketers can build specific campaign audiences. These audiences can be people who fit into certain demographics or purchasing behaviors. Audience segments are built using any number of data points, like family size, household income and age ranges.
Most DMPs have reporting features for analyzing audience data to discern patterns and understand customer behavior. Because large portions of the data DMPs collect are anonymous (via cookies and IP addresses, for example), marketers get the 10,000-foot view and create generalized audience profiles.
DMPs vs. CDPs
DMPs aren’t the only avenue by which brands and businesses can harness the power of data. Customer data platforms (CDPs) are similar to DMPs in that they collect information, organize it and provide actionable insights.
But there is one significant difference: CDPs generally only use first-party data and collect and store specific information about customers using personal identifiable information (PII). CDPs connect the data points gathered back to the individual user, providing even better knowledge about customers and their behaviors.
For example, with DMPs, marketers might know that a user in a specific age group in a specific geographic area searched for women’s skincare products and is interested in workout gear and running shoes.
A CDP could tell you that user’s name, specific age, address and other identifying information. Also, because CDPs don’t rely on third-party data (i.e., third-party cookies) to collect information (remember, first-party data is gathered with permission), privacy and consent issues are less of a concern than those currently associated with DMPs which gather and use third-party data.
Data protection laws
Marketers should note that legislation, like the EU’s General Data Protection Regulation (GDPR) and, stateside, the California Consumer Privacy Act (CCPA), protects consumers as it relates to their personal data and defines guidelines for any businesses that use — or share — that data.
Consumers are more aware of online privacy issues now and expect transparency about how their data is used. Marketers must tread carefully and be prepared for how this continuing evolution will impact their strategies and tools, including DMPs.
The future of data management platforms
Central to the privacy discussion — and the compliance issues introduced by GDPR/CCPA — is Google’s plan to phase out third-party cookies in the second half of 2024. Created by advertising companies, these cookies track website visitors across the web to gain information about where consumers go and, crucially, what they buy.
Because DMPs have historically relied heavily on third-party data to fill their pipelines, a future without third-party cookies would mean platforms must gather customer information from different sources, such as point-of-sale and social media.
In an online environment without third-party cookies, many believe that DMPs are becoming redundant — with marketers increasingly turning to CDPs. That said, it’s probably premature to say that the platforms will become extinct anytime soon. DMPs will likely evolve as the conversation on data privacy and third-party cookies plays out.
One solution seems simple, pivot more wholly to first-party data. Some DMPs, like Lotame’s so-called next-gen Spherical platform, already primarily utilize first-party data, the benefits of which are already well documented.
Brands and marketers should continue to focus on building customer experiences and providing reasons for customers to engage. Ultimately, all this will help increase the volume and quality of data collected.
Dig deeper
Want to learn more?
- Discover 6 data collection tactics for marketing in the cookieless future.
- Learn the future of data management platforms in the era of CDPs on MarTech Editorial Director Kim Davis’ report.
- Learn what the third-party cookie phaseout means for marketing campaigns in this MarTech story.
- Find out how to use AI and machine learning to boost marketing data management.
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