In late 2016, the Customer Data Platform Institute launched to assist marketers in the effort to finally centralize customer data in an accessible, actionable place. The effort was well-received and continues to build momentum.
The most recent Marketing Technology LUMAscape shows more than 20 customer data platforms (CDPs), a category that didn’t even exist two years prior.
Whether they formally use that term or not, an increasing number of companies are offering a unifying data solution, bringing email reactions, chat records, social media responses, site visits, purchases and more together in one platform.
While this is a fantastic option to organize customer data to uncover cross-sell and upsell opportunities, it cannot be mistaken as the magic bullet to achieve all data-centricity.
In order to realize a more comprehensive data strategy, there are three critical components that CDPs lack.
1. Prospecting Database
CDPs are a customer-centric solution. However, in my experience, customers for most companies generally only make up about 2% of the total U.S. population — less than 5 million people.
For a handful of megabrands, that number may be higher. So these brands, whose customer base spans the majority of the U.S. adult population, may be content to build on their understanding of their current customers. But they’re the exception, not the rule. For others, CDPs don’t satisfy the need to build awareness among and acquire new customers.
In order to survive, most brands must ask themselves, “How do I reach people that I don’t know yet?” They need to move people from unknown prospect to customer to drive business growth. To do that, they need third-party data — information that CDPs tend not to have.
2. Identity Graph
Most CDPs also lack a complete identity graph: a database that connects customers to all their digital IDs. First-party data typically has one connection, such as an email address, but it typically lacks mobile IDs, other emails and cookies. It’s not that the CDP couldn’t connect those elements, it’s that they don’t have all of the elements. You can’t connect data you don’t have.
3. Predictive Modeling and Decisioning
Unlike some data management platforms (DMPs) — which CDPs have been likened to — most CDPs do not have the technical infrastructure to deliver predictive modeling and decisioning. A CDP can tell you some basic information about the people who sign up for email updates or have purchased from you, but they’re limited by the depth of the first-party data they have access to. Generally, they won’t have the machine learning and AI to drive decisioning or to build a lookalike model that tells you which customers might sign up or purchase.
Because CDPs focus on first-party data, they also can’t help you determine the best prospects in the remaining 98% of customers that you don’t know, which is a missed opportunity in activating your first-party data. A sample of known customer data can be used to build lookalike audiences, which gives brands promising new pools in which to fish.
What’s Next for CDPs
The name says it all: These data platforms are built to focus on a brand’s customers, but they do not solve all the challenges that marketers face when it comes to data-centricity. To fill in these gaps, brands need additional data, onboarding and modeling partners to drive growth.
It’s uncertain if CDPs will incorporate such prospecting data or onboarding capabilities in the future. But there will likely be new forms of platforms with more sophisticated abilities that emerge as the industry matures.
Undoubtedly, more platforms, like CDPs, DMPs, and others, will build more expansive asset collections to help marketers manage not only their customer data, but their prospect data and modeling needs. I think we’ll see identity graphs be built as part of these comprehensive offerings as well, rather than act as stand-alone solutions.
So while CDPs reign as the vogue platform right now, I think there is plenty of room for more improvements to help marketers achieve data-centricity.