The DMP conundrum
What happens when you KonMari your martech stack?
DMPs are used by as many as 80% of B2C brands in the US to boost the efficacy of web advertising and personalization. But now many brands are re-evaluating their DMP’s underlying business case, where the technology sits in their organization, and even if they need one at all.
The reason is simple: for most companies, the macro environment has shifted considerably since first getting started with their DMP. First, there were Walled Garden and app environments that didn’t support cookies. Then there was GDPR and Intelligent Tracking Prevention (ITP) on Safari browsers. Next up are CCPA and Google contemplating its own version of ITP for Chrome. And the pace of change doesn’t show any signs of slowing.
To be sure, it’s not that DMPs do not ever have an important role to play in the modern martech stack. In most cases, they probably do! It’s just that their role is changing and, amid all this change, it’s become clear that, at a minimum, a DMP requires a robust enterprise data strategy and architecture underpinning it to maximize its value.
Here are three steps every brand can take to evaluate the role of a DMP in their strategy and architecture:
- Clarify the why and how of their DMP usage: Define your use cases and compare them to your DMP’s current capabilities. Business needs change, consumer behaviors change, regulations change, and technology infrastructures change. Is your DMP still fit for purpose and does that purpose still matter?
- Validate ROI assumptions: With your use cases defined, re-run your business case assumptions to ensure the ends still justify the means. Does your DMP still provide tangible value over and above the total cost of ownership?
- Run the KonMari test: Solid use cases and ROI are necessary but not sufficient reason to stick with a DMP. Like anything worth keeping, it needs to spark joy (especially if the ROI is sketchy). Consider the DMP’s ease of use, its flexibility, its ability to collect and activate data from emerging channels, and the quality of insights provided.
If your DMP isn’t sparking joy or providing the ROI you had hoped for, then it’s time you took action. Download this ebook from mParticle to learn what you can do about it.
Latest from mParticle
Get your flywheel in motion with Data Master
Learn how mParticle's Data Master enables you to increase data quality throughout the customer data pipeline, allowing insights to compound, and making every campaign and product launch better than the last.
GOAT: Lifecycle marketing for scalable growth
Learn how GOAT uses mParticle to streamline their data pipeline and increase Customer Lifetime Value.
mParticle launches new features to help brands create ‘data flywheel’
New features for seamless data quality management, and transformation to serve as a foundation for improved customer experience and better insights.
Better data, better insights, better results: Helping brands create a data flywheel
Introduce total quality management and enforcement into your customer data pipeline with new Data Master features and Calculated Attributes. With Data Master and Calculated Attributes, establishing a source of reliable customer data that will create a customer data flywheel, where the data quality and data’s impact on the product cycle will continuously improve over time.