The standard definition of a customer data platform (CDP) invites some misconceptions, primarily because the definition put forth by the Customer Data Platform Institute in 2013 doesn’t really address business value. The Institute defines a CDP as a “packaged software solution that creates a persistent, unified customer database that is accessible to other systems.”
If we infer by the definition, as many do, that a CDP is simply another martech solution owned by marketers, we fall prey to misconceptions by focusing too much on the technology and less so on the business challenges it aims to solve. The standard definition focuses its lens on the “what” and not the “why” you might need a customer data platform.
A calculus that accounts for and applies business context to a CDPs purpose will dispel many of the common fallacies that a literal definition invites.
Not Your Father’s CRM System
The common misunderstanding that a CDP is “owned by marketers” and is just another data system that marketers must manage and maintain likely arose from marketers worrying that a CDP was just a newfangled CRM or DMP. It’s an understandable notion. After all, a CRM stores customer data and engages with customers, and a DMP is used to deliver seemingly personalized content, and those are both marketing-managed systems.
The key difference is that a CDP connects all types and sources of customer data – batch, streaming, structured, and unstructured – from across the enterprise. By generating a single view of the customer, a CDP differentiates itself from other customer data systems.
A CDP is owned by marketers in the sense that it is built with the marketing function in mind, but marketers already swimming in data will naturally resist another solution if they think it will entail having to go through IT for every change request and having to wait months for any change to be implemented, however small.
Rather, if we think about the business purpose behind “packaged software”, we get at what marketers really care about: agility and the ability to keep up with the customer. As new devices crop up, new channels emerge, and as customer journeys become less easily defined, marketers must keep pace. A CDP enables that agility, which further distinguishes it CRM or DMP systems.
The reality is that creating a persistent, unified customer database ensures that a CDP is never going to be wholly owned by marketers simply because IT needs to be a trusted partner to build, maintain, and customize the CDP solution according to unique business needs. Creating a single view of the customer through use of a CDP is a different process for each company and is largely dependent on what type of data and data sources make up a unified customer profile. “Packaged software” doesn’t mean you flip a switch and an out-of-the-box CDP spins up a unified customer profile unique to specific business requirements.
Other misconceptions around CDPs relate to the notion of simplicity. While a CDP is indeed a persistent, unified customer database accessible to other systems, the literal definition reinforces a belief that possessing a common data platform will miraculously result in optimal continuous engagements and dynamic customer journeys. The reality is that setting up a single platform for a continuously updated customer data record is just the first step in a process to improve the customer experience.
Identity resolution is an enormous challenge that requires linking records across an anonymous-to-known customer journey. Robust identity resolution solutions must know how to handle ambiguous or conflicting information such as name and address variants, missing fields, shared devices, and multiple devices, and need to offer both deterministic and probabilistic data matching to match the range of data consistency and quality found in CRM, POS, and other enterprise systems.
Marketers should rightly be wary of a vendor that promises simplicity. All CDPs are not equivalent, either in the breadth of functionality or the depth of capabilities. A CDP is not primarily about combining lightweight data assembly, analytics, and activation. An organization that undertakes an honest assessment of CDP use cases for the business will understand that a CDP must operationalize data across the enterprise to support real time decision-making. The core task of building an accurate, timely golden record must not be overshadowed by trying to “kitchen-sink” fit the entire martech stack into the CDP.
All Data is Created and Valued Equally
This brings us to a similar and intertwined misconception, that a CDP can provide high value with a smattering of martech-provided data (think web visits, device IDs, email opens, etc.). The reality is that today’s empowered customer controlling his or her own customer journey, uses several online and offline touchpoints in an undefinable pattern often lacking rhyme or reason.
Additionally, customers are providing many different sources of behavioral, transactional, and sociographic information at every touchpoint, both in traditional marketing “channels” and across the broader enterprise landscape. This broad set of customer touchpoints, if used effectively, can deeply enrich customer engagement and personalization. The challenge for a marketing organization is that the more information it collects – a necessity to paint a complete picture of a customer journey – the more it is challenged with identity resolution.
An open garden approach provides accessibility to any type of data source which helps complete a unified customer profile and underscores the importance of a CDP as far more than a collection of martech-provided data. How that data is used to deliver real-time insight is what gives a CDP value.
When organizations considering a CDP understand the complexity of building a unified customer view while still moving at the speed of the customer, the misinterpretation that a CDP delivers simplicity with a one-size-fits-all solution for all customer data problems will diminish considerably.
Near-Real Time is the Same as Real Time
One final mistaken belief about a CDP is that it will deliver optimal value by supplementing batch data with data that is only a few minutes old. The problem with this myth is that it undermines the entire reason for using a CDP in the first place, which is to obtain an up-to-date single view of the customer to inform marketers of a next-best action specific to an individual customer journey. Simply layering new information on batch data doesn’t enable you to create a dynamic model for delivering the next best action for the needs of the customer.
This misconception ignores the value of real-time, which means responding with timely and relevant information for the customer at every interaction and channel. Website visitors, mobile app users, and in-store visitors all expect personalized and immediate engagements, which means knowing where the customer is along every step of the customer journey. If a customer uses a brand’s mobile app just before dialing the call center, an account rep that knows what the customer did on the mobile app can guide an optimal customer journey that would otherwise be a missed opportunity.
Ultimately, the true purpose of a CDP is to deliver a satisfied customer. Starting with that baseline understanding and thinking about business goals before the technology will help to dispel the myths that a CDP is a panacea that will instantly solve all customer data problems or, worse, that it is just another in a long line of data systems that needlessly adds complexity to a marketer’s job. Peeling away the misconceptions uncovers a CDPs core value and the impact it can have on the bottom line.