Once upon a time, a data management platform (DMP) was an essential component in one’s technology stack, as it was a critical cog in companies’ marketing campaign machines.
Many businesses have built their programmatic advertising strategies around the DMP in recent years. Specifically, they relied on the tool to provide anonymized, cookie-based audience data to run and improve the targeting for their advertising campaigns.
Some businesses, like media and publishing organizations, have used the data management platform to create audience segments they can sell to advertisers and agency buyers.
But data management platforms have oversold, overpromised, and underdelivered to marketing professionals and their organizations for much of the past decade.
Marketers at well-known companies told AdExchanger they’re “in the process of sunsetting their DMPs.” Meanwhile, agencies said “clients are moving away from DMPs en masse.”
With the swift death of third-party cookies — thanks in large part to privacy changes implemented in Safari, Chrome, and other browsers — the usefulness and effectiveness of a data management platform for marketing teams has diminished substantially.
One consultant told Digiday 80% of the ad experts he spoke with around the time GDPR went into effect in mid-2018 said “they were not getting the most from their DMP.”
Publishers have heard the data management platform’s death knell for some time too.
AdExchanger also reports many marketers are “abandoning first-generation DMPs and trying out a new breed of segmenting engines that don’t require cookies.”
It’s now clear: The data management platform’s days as an integral part of companies’ marketing strategies are coming to an end. And there’s ample proof to support its downfall.
Why data management platforms aren’t worth the investment for marketers
I already broke down how a customer data platform (CDP) differs from a DMP (and offers considerably more benefits for modern marketers). Thus, I won’t do so again here.
Instead, I’ll lay out an increasingly obvious state of affairs: that the data management platform has failed — and will continue to fail — many marketers who rely on the tech.
Downside #1: Losing data after a matter of days is stupid.
Picture it: You’ve spent all this time figuring out what customer and ad campaign data to collect. And you’re running great data analysis to understand how to make the most of it.
It’s awesome. Until you start losing all of that data because the cookies expire. Suddenly:
- That historical data analytics you’ve been so carefully conducting? Far less potent.
- That lifecycle marketing strategy you’re trying to construct? Way too fragmented.
- That single customer view you so desperately want to achieve? Just not happening.
The exact cookie expiration date now varies across browsers. The point is this audience data quality and reliability is as low as it’s ever been for marketers, publishers, and advertisers.
Simply put, none of your customer data sources should have an artificial shelf life.
Rather, all your customer data should be stored, dynamically updated, and always accessible in persistent profiles where you can activate it in a matter of seconds. Not available for a limited time only and, in turn, limiting your marketing capabilities.
But that’s the data management platform’s bread and butter: Cookie-based data that simply doesn’t last. And is not nearly as effective as its near-polar opposite: first-party data.
Downside #2: Black boxes of customer data suck.
There’s a really annoying TV commercial in which people whine, “But it’s my money, and I need it now!” Marketing professionals should feel the same way about their customer data:
“It’s my customer data, and I should have full and total access to it when I need it.”
That way, if you have questions about reports, you can go in and understand the data analysis, rather than just cross your fingers and trust that what your DMP spits out is right.
If you can’t trust your data or know what’s going on with it at all times (and in real time), what’s the point of gathering and storing it in a data management platform?
Black boxes lack transparency and visibility into the quality, accuracy, and reliability of your customer data sets. Moreover, they are major hindrances to marketing success.
And your data management platform could be enabling this mindset.
Downside #3: It’s crazy to wait weeks for segments.
Speaking of real-time data, some marketers are willing to wait more than 10 minutes — let alone days or weeks — to get a segment that can be used in activation channels.
Real talk: If it takes your DMP two-plus weeks to build customer segments, there’s virtually zero chance those segments re still accurate by the time they’re finished.
So much will have happened in customers’ journeys during those two weeks that attributes describing them change after two hours, never mind two weeks.
A customer segment definition that isn’t updated in real time isn’t old. It’s ancient.
What’s more, it’s nearly impossible to take advantage of dynamic first-party data (e.g., behavioral and contextual data points) when creating unique segments.
Other tech, like our customer data platform, offer real-time data collection and machine learning to build customer segments based on granular profile traits and behaviors.
With other options for customer segmentation at your disposal — and one, in particular, that can take data stored across your stack and allow you to quickly and efficiently segment individuals as desired — the dependency on a DMP makes even less sense.
Downside #4: There’s better technology out there.
The tech landscape isn’t static. The 7,000+ martech vendors in the marketplace today continue to enhance their SaaS solutions to make marketers’ lives and jobs easier.
Thus, it shouldn’t come as a surprise there’s a fair amount of feature overlap from one type of martech to another. And that the landscape is always evolving.
And such is the case with the data management platform and related systems.
For example, identity resolution tools have adopted data collection functionality DMPs have traditionally been known for. Many can now match existing profile IDs with those offered by anonymous, third-party data providers and send paired IDs directly to DSPs.
As you can see, this circumvention of data management platforms renders one of its core features seemingly useless for marketers with the former system in their martech stacks.
In the same vein of other martech developing similar features, many marketers are going directly to Facebook and Google for their audience targeting needs for ads.
And, in turn, are questioning the cost of using DMPs to simply load data into those tools.
Why it’s time to get rid of your data management platform — and get a CDP
I used to be of the mindset that data management platforms won’t suddenly disappear from the martech landscape overnight or even be removed from many marketing teams’ stacks for failing to produce the desired return on investment needed to meet their KPI targets.
But the plain truth today is this:
Data management platforms just aren’t as dependable or practical as they once were. And they’ve already proven to be a letdown.
My advice? Leverage your first-party data through the persistent customer profiles offered in CDPs like BlueConic, and you’ll see the (big) difference it can make in your marketing.
Want to know more about the benefits of CDPs compared to DMPs? Download our eBook to discover the key differences between the two technologies.