Can Customer Data Platforms Make Decisions? Discuss.

I’ve had at four conversations in the past twenty four hours with vendors who build a unified customer database and use it to guide customer treatments. The immediate topic has been whether they should be considered Customer Data Platforms but the underlying question is whether Customer Data Platforms should include customer management features.

That may seem pretty abstract but bear with me because this isn’t really about definitions. It’s about what systems do and how they’re built.  To clear the ground a bit, the definition of CDP, per the CDP Institute, is “a marketer-managed system that creates a persistent, unified customer database that is accessible to other systems". Other people have other definitions but they are pretty similar. You’ll note there’s nothing in that definition about doing anything with data beyond making it available.  So, no, a CDP doesn’t need to have customer management features.

But there’s nothing in the definition to prohibit those features, either. So a CDP could certainly be part of a larger system, in the same way that a motor is part of a farm tractor. But most farmers would call what they’re buying a tractor, not a motor. For the same reasons, I generally don’t to refer to systems as CDPs if their primary purpose is to deliver an application, even though they may build a unified customer database to support that application.

The boundary gets a little fuzzier when the system makes that unified database available to external systems – which, you’ll recall, is part of the CDP definition. Those systems could be used as CDPs, in exactly the same way that farm tractors have “power take off” devices that use their motor to run other machinery.  But unless you’re buying that tractor primarily as a power source, you’re still going to think of it as a tractor. The motor and power take off will simply be among the features you consider when making a choice.*

So much for definitions. The vastly more important question is SHOULD people buy "pure" CDPs or systems that contain a CDP plus applications. At the risk of overworking our poor little tractor, the answer is the same as the farmer’s: it depends it on how you’ll use it. If a particular system offers the only application you need, you can buy it without worrying about access by other applications. At the other extreme, if you have many external applications to connect, then it almost doesn’t matter whether the CDP has applications of its own. In between – which is where most people live – the integrated application is likely add value but you also want to with connect other systems. So, as a practical matter, we find that many buyers pick CDPs based on both integrated applications and external access.  From the CDP vendor’s viewpoint, this connectivity is helpful because it makes their system more important to their clients.

The tractor analogy also helps show why data-only CDPs have been sold almost exclusively to large enterprises. Those companies have many existing systems that can all benefit from a better database.  In tractor terms, they need the best motor possible for power applications and have other machines for tasks like pulling a plow. A smaller farm needs one tractor that can do many different tasks.

I may have driven the tractor metaphor into a ditch.  Regardless, the important point is that a system optimized for a single task – whether it’s sharing customer data or powering farm equipment – is designed differently from a system that’s designed to do several things. I’m not at all opposed to systems that combine customer data assembly with applications.  In fact, I think Journey Orchestration Engines (JOEs), which often combine customer data with journey orchestration, make a huge amount of sense. But most JOE databases are not designed with external access in mind.  A JOE database designed for open access would be even better -- although maybe we shouldn't call it a CDP.

To put this in my more usual terms of Data, Decision, and Delivery layers: a CDP creates a unified Data layer, while most JOEs create a unified Data and Decision layer. There’s a clear benefit to unifying decisions when our goal is a consistent customer treatment across all delivery systems. What’s less clear is the benefit of having the same system combine the data and decision functions. The combination avoids integration issues.  But it also means the buyer must use both components, even though she might prefer a different tool for one or the other.

Remember that there’s nothing inherent in JOEs that requires them to provide both layers. A JOE could have only the decision function and connect to a separate CDP. The fact that most JOEs create a database is just the matter of necessity: most companies don’t have a database in place, so the JOE must build one in order to do the fun stuff (orchestration).  Many other tools, such as B2B predictive analytics and customer success systems, create their own database for exactly the same reason. In fact, I originally classified those systems as CDPs although I’ve now narrowed my definition since the database is not their focus.

So I hope this clarifies things: CDPs can have decision functions but if decisions are the main purpose of the system, it’s confusing to call it a CDP.  And CDPs are certainly not required to have decision functions, although many do include them to give buyers a quick return on their investment. If that seems like waffling, then so be it: what matters is helping marketers to understand what they’re getting so they get what they really need.


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*I’ll guess few of my readers are very familiar with farm tractors. Maybe the more modern analogy is powering apps with your smartphone. For the record, I did work on a farm when I was a lad, and drove a tractor.