Insights and analytics in a CDP are more precise, with workflows designed for customer exploration, dashboarding, and predictive analysis, up to the largest data sets and down to individuals (since activation can happen one-to-one in many of the leading tools). Precision insights also mean that teams have data they can trust, not just for marketing activation but for other critical business cases, like financial forecasting and reporting. Using one platform for customer data management means numbers align across teams, plans, reports, use cases.
Finally, a CDP powers measurement based around the customer, focusing on behavior and outcomes, so that brands can have a clear view of what’s working and what isn’t to power adaptation and innovation.
Some things are still hard
The dream of a totally comprehensive view into the “entire” customer advertising journey still remains elusive. Why? Customers see and engage with ads and content across a variety of platforms; they search on Google and then see a video advertisement on Facebook. The so-called walled gardens of tech — Facebook, Google, Amazon — still aren’t going to let large parts of their customer data co-mingle in any outside platform. That’s just as true for CDP as it is for DMP.
Could this change? It might, with Google’s Federated Learning of Cohorts (FloC) — a proposal to create customer cohorts to pass to and from other platforms in a way that would protect customer privacy. This solution is in the prototype phase and we are at least a year from seeing what use cases it can enable and how to do it safely for the customer.
Marketing teams need to add focus on building first-party data sets with opt-in and to continuously quantify the value of those customer names. In the DMP world, marketing teams could use third-party cookies across the open web to amass large sets of customer data and segments into their DMP. Without third-party cookies, this changes. Now marketers can collect anonymous data from their first-party data (typically browsers of their websites who have acknowledged cookies, and customers who provide their PII at some point along their journey). This requires two strategies:
1) Allocating performance budget to accelerate growth of opted-in first-party customer data.
2) Quantifying the incremental value of each new customer name acquired in order to measure the ROI of customer name collection to the business. This type of analysis often requires designing a control group strategy to understand the incremental customer lifetime value of marketing to newly acquired customer names.
Need to replace your DMP? What to look for in a CDP for an effective transition:
Given the similarities between what CDPs and DMPs aim to accomplish, and the ways that CDPs overcome the limitations of DMP, a CDP is a smart investment for brands wondering what to do with their DMP. Not all CDPs are going to achieve this equally though. Here are some key things to look for:
A CDP should come with rich off-the-shelf audience insights and predictive analytics to produce audiences, coordinate omni-channel journeys, and drive incremental ROI performance, plus the ability for all teams to easily explore customer data and analytics to create unlimited custom attributes, segments, and campaigns.
It must have anonymous-to-known capabilities alongside connections and interoperability with the cookie-less ad-tech ecosystem of the future, like Throtle and UID2.0. It should support direct sync to Facebook, Google, and Amazon, as well as continue to innovate new direct sync to emerging data providers built for a post-cookie advertising ecosystem.
Your CDP should have the enterprise scale and power to handle the customer data needed to fulfill critical advertising and measurement use cases - think customer interaction data like impression logs or other mega-scale data sets. This can quickly go to trillion-entry scale and surpass the compute capacity of many platforms, so they can’t process the data and make it available in real-time — which creates implementation and operation headaches or inability to execute use cases.
There should be dedicated workflows for every team across the business to access and use customer data — whether IT for data management and governance, analytics teams for workflows that are both sophisticated and easy to use, or marketers and media teams for no-code point and click exploration, audience creation, and campaign management. And it should be easy for not only the marketing teams but also the full enterprise to get the right customer data sets into the tools and platforms where they need it (for customer care, website teams, market research, finance). Your CDP investment needs to meet these needs or it will become just another customer data silo amongst others.
Your CDP should be independent and system-agnostic. Interoperability is make-or-break for a successful CDP initiative, and a make or break from an advertising perspective. If your CDP is part of a marketing cloud or walled garden, there are going to be issues integrating data from outside that technology provider. An agnostic CDP should work with your investments in large marketing clouds and also enable the flow of data to any platform or technology system across your ecosystem and to any DSP, publisher, or paid social channel.
Your CDP provider should be sufficiently funded with large, long term renewing customers so you know it can stay independent for the long term, protecting you from being forced through an acquisition into a walled ecosystem with misaligned priorities for your data.
Let’s take a moment to say farewell to Salesforce DMP and its promise. As for DMP as a broader category? Let’s watch and see. In the meantime, CDPs are stretching well beyond the vision of the DMP and into bold new territory.
If you'd like to talk more about how a CDP can take you further than a DMP, get in touch.