Is a data management platform (DMP) about ads? Yes, and…

If you look up definitions for what a data management platform (DMP) is, you’ll find a few different answers. Among all the different definitions, people can agree that DMPs:

  • House and manage information (usually marketing information)
  • Find and send audiences for targeting elsewhere

Today, many definitions of (and use cases for) DMPs skew heavily toward third-party data from and to ad networks and exchanges, along with a narrow focus on the “management” part. However, some DMPs have expanded far, far beyond ad data management. Of course, marketing definitions and categories are fluid (and one person’s “fluid” is another’s “horribly confusing”); one category can turn into several and products can overlap into multiple spaces, so at the end of the day, you need to focus on the problem you’re solving and choose the best option to get you there.

Let’s take a look at how DMPs have evolved beyond their older boundaries and a few of the elements that savvy marketers should look for in DMPs today.

The limits of ad tech

In their infancy, DMPs were very much about ad automation and ad buys. Digiday wrote in 2014, “With the rise of ad tech, advertisers now buy media across a huge range of different sites and through various middlemen, including DSPs, ad networks and exchanges. DMPs can help tie all that activity and resulting campaign and audience data together in one, centralized location.”

To be effective today, marketers need to maximize personal touches they have with audiences while minimizing one to many relationships (i.e., not the traditional shotgun ad approach). As much as they can, marketers need to focus on building relationships while getting to know their audience better—62 percent of millennials are more loyal to brands with personalized content.

The limitations of collecting (and using) audience data from traditional ad-focused DMPs is that they a) use the same third-party data that everyone else is using to tie activity together, which limits the reliability (and uniqueness) of segments of different groups to target and b) rely on matching users based on cookies (while people often clear their cookies, change browsers, or switch devices).

Putting all that ad data into a single place can help run more efficient ads across different ad networks, but there are always questions of accuracy: How do segments and demographics for your programmatic ads apply to your core customers? How accurate is any of the information in the first place?

Your audience, your data

More and more marketers are turning to their own data as the ultimate source of truth—bringing in information from marketing automation, email service providers, ticketing, and social profiles into their DMP and using that data to run segmented advertising. With data marketers have collected, they can better understand their collective audience and fan base, create valuable segments (whether by zip code or purchasing behavior), and even allow salespeople to view 360-degree individual profiles of fans in a CRM.

Focusing on ad tech doesn’t make a DMP any less of a DMP, so perhaps HubSpot’s definition is the most applicable to both the first-party DMP and third-party DMP categories. A DMP is “simply a marketing tool that collects comprehensive demographic, psychographic, and behavioral data about your target audience from a variety of sources, all in one unifying platform.”

A little less talk

Marketers shouldn’t stop at unification. Another recurring theme of definitions for DMPs is to call them  “data warehouses,” which is a term that has its own set of definitions. It’s not totally inaccurate—whether you’re bringing together third-party or first-party data, you are housing that data. But nearly every martech solution houses data in some way, and we don’t call HubSpot or Eloqua “data warehouses.”

When DMPs are focused on cookie IDs and third-party data, Experian states that “on its own, a DMP can’t actually do all that much,” requiring a demand-side platform (DSP) to buy advertising based on the data in a DMP. First-party DMPs should enable you to take more action within the platform in addition to leveraging valuable segments in ad platforms:

  • Run collection campaigns: Sometimes the audience data just isn’t there in the data that you currently have to feed into your DMP. You might be missing key social brand affinities or demographic breakdowns to be able to run an effective ad campaign. If you’re running live events, you might not have any information about attendees at all. By setting up a data collection campaign, whether a simple Facebook login to your Wi-Fi or a sponsored trivia contest, you can clear up your audience, either uncovering fans who might otherwise be “hidden” or helping create more complete fan profiles.
  • Send segments back into your sources: It’s not all about adding new people to your database. When you combine first-party data from various sources, you can segment within your DMP to find your ideal audiences and then send those segments into your ESP, ad platforms, etc. Yes, that first-party data can be used to create lookalikes to target new prospects on ad networks like Google and Facebook, but it can also surface lookalikes right in your existing database that you would otherwise miss, and you can then target those segments with your email or mobile app campaigns.

If you have an audience within your DMP, but you don’t know much about them, you’ll be spinning your wheels. To effectively market to your current prospects and find new ones efficiently, you need to know your audience. Use third-party data when you have to, but when people are willing to give you first-party data (like emails, social likes, interests, and deeper demographics), take advantage of it in both your marketing and advertising. Remember—if you want to be a data-driven marketer, you need to use the right data.

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