Commentary

Demystifying DMPs, CDPs

This industry loves a good acronym.

First it was DSP (demand-side platform), then came DMP (data-management platform), and now we have CDPs to contend with.  A CDP is defined as a customer-data platform, and many people are confused about the difference between a DMP and CDP.  

In my humble opinion, and one that is relatively informed on this topic, the difference is simple.  A DMP is for media management in advertising and a CDP is for broader uses across multiple channels.

When we initially launched the DMP category, the promise was to use customer data across multiple channels.  The first use case was site optimization; the second, advertising.

I still think those are the primary use cases for a DMP, but the use of data has expanded along with its challenges, while the role of the DMP has become more focused and in some cases even come into question.  

GDPR and other legislation has put some of the control back into the hands of consumers, and marketers are interested in finding ways to optimize experiences across all channels, not solely dedicated to advertising.

This actually becomes simpler or more complex depending on your go-to-market strategy.  If you are focused with your media spend on Google and/or Facebook, it gets easier to take a DMP out of the mix for advertising purposes because those channels are becoming notoriously less friendly towards third-party DMPs, instead offering their own solutions.

That leaves a marketer with the option of focusing ad dollars against one to two channels and then looking to tailor the experience of the messaging across other channels. That’s where the CDP comes to play.  As a marketer myself, I tend to do this for my own go-to-market needs.

I also hear about more marketers using CDPs to improve creative delivery, which is not something DMPs were ever able to really make work at scale.  The challenge was, they required a third-party creative platform to manage the message build, but the CMP/CDP combo is interesting because it puts all of these under one roof.

There are a couple of players in this category that seem to have aligned with the concept of an “experience cloud.”  Adobe coined that term first, and I think it has legs.

Data is not going away, so you have to have a solution in place to make this work at scale.  You may go DMP if you are active on the open web, or you can go in-house with Google and Facebook and supplement with a CDP.  

The X factor here is, where will AT&T, Verizon, Amazon, and retailers like Target/Walmart land?  How will they agree to work with these companies? How much access are they going to give marketers either to leverage the data they make available or to leverage their own data on their specific platforms?  It also leaves the question of how much you want to learn and optimize across all your channels vs. dealing with each channel in a stand-alone manner.

The biggest risk I see here is to third-party, multichannel attribution companies.  The rise of the silo’d approach marks two or three steps backwards for attribution.  One would hope we are headed toward a more integrated marketing and advertising reporting stack, but I only see that happening if these companies begin to find ways to share data with one another, and that’s not likely.  In the traditional media world, you never would have seen ABC, Fox, CBS and NBC share ad data with one another, but then Hulu rose up, and now a few of these folks have line of sight into what the others are doing.  Maybe it’s possible down the line?

It’s a tangled web of interwoven data in the digital ad industry, and it certainly seems to be tightening up a bit.

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