A customer data platform (CDP) is a software system that collects customer data, builds a unified view of your customers (by building profiles), and then uses those profiles to add value across the company by:

Ideally, the database that the CDP leverages should unify all customer data and be  accessible to other systems within your company, though that isn’t the case for many CDP vendors. Regardless, the key elements of a CDP — according to the CDP Institute, a vendor-neutral organization dedicated to helping companies manage customer data — are:

CDPs vs. DMPs vs. CRMs

As there is often confusion between customer data platforms, data management platforms (DMPs), and customer relationship management (CRM) software solutions, it’s worthwhile to explicitly note their different purposes.

CDPs vs. data warehouses vs. data lakes

We’ve covered both data warehouses and data lakes elsewhere, but it’s worth the effort to summarize the primary differences.

CDPs primarily deal with first-party customer data; that is, data that was either supplied directly by the customer, or inferred from their actions and behavior within your product or service offering. The collected data is specifically organized to allow business users to generate actionable insights into customer behavior.

The core value a CDP brings to a software product is its integration across the data stack. By relying on a CDP, it’s possible to identify users, create user profiles, and keep track of users’ behavior and preferences in various parts of the application, from the front end to each back-end microservice.

Data warehouses can manage structured data of almost any scale. The data stored in a warehouse is usually extracted from a variety of sources, but before storage, the data is transformed into a standardized format.

The most valuable aspect of a data warehouse is the structure it provides: it allows the data from the warehouse to be used directly as an input into artificial intelligence prediction models, for business intelligence analysis, and for other business purposes.

Data lakes can manage multiple kinds of unstructured data. The data is made available for quick ad hoc queries, but usually requires further processing before it can be used in other systems and business processes. What makes data lakes uniquely valuable is the high volume of storage they provide, as well as the ability to manage and query unstructured data at low cost.

Customer data platforms come in many flavors

CDPs vary significantly in functionality across the market. Some products offer a full-fledged solution that includes a data warehouse; some only offer an interface on top of an existing data warehouse, while some offer a hybrid model where you can bring your own data warehouse but the CDP powers its service offering primarily from storing your data in its warehouse. The exact way a CDP is set up tends to be organization-specific and doesn’t translate well across organizations. At some organizations, CDPs also take on functions of other data systems - for example, they become the primary data warehouse.

Various CDP vendors also offer different perspectives on who should be responsible for the CDP within the organization. Traditionally, CDP products were built for marketing teams, but many modern companies use a CDP that’s maintained by their engineering team, or a dedicated data operations team, enabling CDPs to add value across the company’s systems. Some CDP products are open-source, enabling engineering teams to customize the platform to their company’s needs.

CDP business rationale: Build vs. Buy

The underlying goal for most businesses implementing a CDP is to improve their customers’ experience. While such an improvement sounds straightforward, it’s everything but straightforward for a large business with thousands of employees and numerous stakeholders involved in business decisions.

Soumyadeb Mitra, RudderStack’s CEO, goes into the details of how to address this challenge in the post Build or Buy? Lessons From Ten Years Building Customer Data Pipelines. In short, to give the right teams the necessary information about what needs to be changed to improve customer experience, the following steps are needed:

Once the decision is made on implementing a CDP, there is another important decision to make: should you build your own CDP, or should you implement a third-party product instead?

For those choosing to build, the common challenges include:

Those buying a third-party solution will likely run into issues like:

The challenges of building your own CDP are highly complex, and using third-party software can be a way to avoid the headache of self-building. It’s worth considering whether you have the resources to build your own CDP, as well as evaluating the cost of  any third-party software and the level of control you will have over it, before making a decision.

Next steps in customer data platform development

Properly planned CDPs give your business an edge in establishing, maintaining, and refining the customer experience and driving increased sales and profit through better-developed leads. It is also important to think about CDPs in the larger context of Customer Data Infrastructure (CDI). A CDP is the engine powering your data collection and processing, but there is also data storage, data modeling, data pipelines, and more to think about for a robust tech stack.

You can learn more about customer data in our corpus of related articles, including:

Together, these articles will help you to chart your path to establishing a customer data platform and improving your marketing reach.