What is a data management platform? + What it misses

For your business to flourish, you need happy customers. And to make your customers happy, you need to understand what they love, what they hate, and everything in between. Fortunately, there’s no shortage of data to get you better acquainted with your target audience.

This is one of the reasons why many organizations use a data management platform (DMP). DMPs aggregate and organize data sets about anonymized online user behaviors, which businesses use to build more effective marketing campaigns. But while DMPs are an excellent tool for working with anonymized data, they won’t give you an adequate view of your first-party customer data. As a result, many businesses combine DMPs with a customer data platform (CDP) for end-to-end customer data management.

What is a data management platform (DMP)?

A data management platform (DMP) is software that collects, organizes, and manages large amounts of primarily second- and third-party data from various sources. The ultimate goal of this data is to help organizations create more targeted audiences for paid ad campaigns. Common examples of DMPs include brands you’re familiar with, such as Salesforce, Oracle, and Amazon Redshift. These companies gather insightful data about the online behaviors of millions of people. They then aggregate that information, organize it, and sell it to help businesses better target new leads from paid ads.

But before diving into specifics of how data management platforms work, it’s crucial to understand the difference between first-, second-, and third-party data and how each type is used in marketing at a practical level.

1) First-party data is what you personally collect from your customers. This could include information like name, email address, age, email opens, mobile app interactions, or any other piece of audience data that you gather from your internal analytics tools on current leads or customers.

2) Second-party data is when one organization passes a portion of its first-party data to another company. This is beneficial to non-competing brands that share an audience.

3) Third-party data is usually a large amount of data that’s aggregated by one company. Then it’s organized, anonymized, and resold to different companies to improve paid marketing efforts.

The reason it’s important to understand these three types of data is that they highlight what DMPs are focused on and, more importantly, what they’re not focused on. DMPs don’t typically work with first-party data. There are exceptions to this rule (like Salesforce’s Audience Studio, for example), but those all-inclusive solutions are mainly used by large businesses with deep pockets.

DMPs are really suited for building and segmenting audiences to improve your paid advertising strategy. In doing so, they connect businesses with huge amounts of third-party data to improve conversions and targeting. As a result of this narrow scope, though, DMPs aren’t the ideal solution for a comprehensive view of your entire customer journey. Nor will these platforms give you insight into how your current customers engage with your brand.

How does a DMP work?

To understand how DMPs work, you’ll first need to get familiar with how companies purchase digital advertising space. There are a few key characters involved in the process:

• An ad exchange marketplace is where advertisers purchase ad placements and publishers sell their digital real estate—the ad space available on a website—through real-time auctions.

• A supply-side platform (SSP) is software that allows companies to upload their second- and third-party data. Ad exchange networks then use that data to determine the value of a publisher’s digital real estate.

• A demand-side platform (DSP) is where companies can purchase second- and third-party data to build audience segments and place more targeted ads. It’s what advertisers (the demand side) use to let publishers (the supply side) know what criteria they’re looking for in an audience group.

In a simple world, buying advertisements would be easy: advertisers would look at what space is available for their paid ads, find the website that most closely shares a specific audience, and they’d make a bid on that space. Publishers would then give a piece of their digital real estate to the highest bidding advertiser:

The problem is that, over time, lots of advertisers and publishers began filling the ad exchange marketplace. This made it more competitive for publishers selling space and more options for advertisers to tediously bid on. This is where a DMP helps run things more efficiently. An advertiser will take what they know about their audience and make a request through their DMP with specific filters around whom they’re targeting.

For example, let’s say the company Build-A-Bear wanted to place some ads. And they know their ideal audience is:

• Aged 27–38

• A parent of two or more kids

• Have a household income of $100k+

• Interested in cooking recipes for healthy snacks

Build-A-Bear configures these settings through the DMP, which then looks for the right opportunities through an SSP. The DMP here is sifting through tons of third-party anonymized data to find the best ad placement to fit Build-A-Bear’s filter requests. When the DMP finds a placement that works, it makes a bid, and the deal can be made:

As you can see, the DMP acts as a middleman to open up more targeted connections between publishers and advertisers. They are able to do so because they store so much anonymous data, predominantly through cookies (which could lead to a larger problem that we’ll touch on in just a moment).

Pros & cons of DMPs

DMPs are a valuable resource for many businesses, but that doesn’t mean they’re perfectly suited for every organization. Instead, it’s best to weigh the pros and cons of DMPs against your unique needs.

Benefits of DMPs

1. Access and utilize third-party data

DMPs allow you to aggregate and integrate data from different sources, both internal and external. Doing so lets you work with more data sets than you might be able to gather firsthand and better understand whom you need to target with your paid ads.

2. Create segmented user profiles

DMPs take that second- and third-party data and group your audience into “segments.” Customer segments are sub-groups of your audience that share similar characteristics. If you find a segment that works well, you can also use a DMP to build a “look-alike audience”—a group with similar customer profiles to your target audience. You might create the following audience segment for a paid campaign:

• Age: 30–40 years old

• Location: North America

• Interests: Underwater basket weaving

• Device Used: Desktop

Once you know the types of people who will see your advertisement, you can find the best ad placements for your offer and write more effective messaging to a specific group. When done correctly, you can personalize the user experience from the ad copy to the landing page. This level of data-driven optimization boosts conversions and sales.

3. Stay ethical with anonymized customer data

One of the most important aspects of DMPs to keep in mind is that they anonymize third-party data. None of the data can be attributed to any specific online user once a DMP makes it anonymous. That means you can rest assured that your organization will be working with data that’s legally and ethically aggregated.

What DMPs are missing

Since most companies don’t have millions of customers, DMPs are commonly used with second- and third-party anonymized data (the keyword here being “anonymized”). DMPs are designed to aggregate generic data to help with advertising.

As a result, DMPs are limited in terms of how they can be practically used by marketers. They don’t tell you anything about the customers you actually have and, therefore, won’t help you leverage data to create more meaningful customer journeys. Instead, you’d use a DMP to build more powerful advertising campaigns. So while a DMP is certainly useful for obtaining new leads, it won’t give you the audience insights needed to transform (and retain) them into paying customers.

Plus, with second- and third-party data, you and your competitors will be working from the same dataset. First-party data, on the other hand, is private to your organization and can lead to more impactful marketing strategies with your existing customers.

Finally, there’s one major problem surrounding DMPs that you should know: the sun is starting to set on this technology. As we mentioned earlier, DMPs predominantly track third-party data via cookies. Google stated that they would be phasing out third-party cookies from their browser Chrome in 2023. This would remove much of a DMP’s value because it would no longer have that third-party data available to find targeted ad space.

While many DMPs are adapting and trying to incorporate first-party data, doing so will still change what a DMP is capable of. Therefore, it’s not clear what the state of DMPs will look like in the next two years.

Why you should combine DMPs and CDPs

The real benefit to your martech stack comes when you combine DMPs with customer data platforms (CDPs) for end-to-end customer insights.

What are CDPs?

Customer data platforms (CDPs) provide insight into YOUR customers’ experience more than other data management solutions. Unlike a DMP, CDPs work with data that hasn’t been anonymized. A CDP collects and manages first-party customer data, which you can use for more comprehensive marketing strategies than if you were using a DMP alone.

When you combine the two tools together, you have access to first-, second-, and third-party data.

In the end, this gives you the best of both worlds: CDPs manage your personal first-party data that can be used to create better customer experiences and reduce churn. Then, DMPs will help you leverage second- and third-party data to create better ad campaigns to bring in new prospects.

When these two software work together, it’s easy to see how they’re complimentary:

• CDPs teach you more about the customers you already have with first-party data.

• With that knowledge, you can use DMPs to run targeted ads to people who share similar characteristics with your existing customer base.

• The new customers you attract from those advertisements bring you more first-party data.

• CDPs then help you leverage that first-party data to build an end-to-end customer experience.

For example, let’s imagine that your CDP shows your target users are 40–60 years old, interact predominantly via mobile, and live on the American East Coast. So you use that knowledge and make a request through your DMP to find the best ad space available meeting those filters. The DMP looks through its aggregated data and works with an SSP to make a bid on ad placement. If the bid is successful (meaning you can bid higher than the competition), your ad gets displayed.

When this campaign brings in new customers, you’ll have even more firsthand data to work with. You can then continue to use your CDP for many things, like engaging customers in real time based on their behaviors, cross-selling and upselling at key moments in the customer journey, and preventing data silos from forming within your business.

Curious about how customer data can move the needle for your marketing efforts? Learn more about how Segment can help you create stronger (and proven) data-driven strategies today!