What is a Customer Data Platform (CDP)?
Customer data platforms (CDPs) are popular marketing tools that power many of our day-to-day interactions with brands. What is a CDP, though? Of course, like many marketing topics, that depends on who you ask. As Marty Kihn, SVP Strategy, Marketing Cloud at Salesforce, said on our In The Clouds podcast, “Pretty much every analyst now has some view of what a CDP is, and it’s changed.”
The term customer data platform was coined in 2013, but due to the constant evolution of the marketplace, it is still considered an emerging technology. Lev was among the first wave of partners to achieve accreditation for Salesforce’s CDP and have been consulting on it since the initial release. Here is how we define CDP:
“CDP is a data unification platform, allowing for marketers to extend their insights into customers, analyze and segment based on the unified data, and activate across all channels and touchpoints.”
Why would a marketer want a CDP? With unified data from all your sources, you can not only know your customer but you can power consistent cross-channel experiences. Audiences are created in a single location and activated to all channels, as opposed to constantly building a segment in each siloed tool based on siloed data. No matter the channel through which a customer interacts with your brand, they will be able to have a consistently personalized experience.
Common Features of CDPs
Generally, CDPs can help marketers:
Ingest data, providing a single view of the customer
Using pre-built connectors to common data sources, flexible import capabilities, and APIs, CDPs can help marketers get a complete picture of their customer data. Ingestion may be in real-time or it may use a batch process.
Organize and unify data
Once the data has been collected, CDPs are able to match contacts’ known identifiers (email addresses, phone numbers, company names) with any anonymous data you may have for them. CDPs in this category can also help with mapping data fields properly to support the integration of multiple systems.
Quickly build rich customer segments
CDPs aim to make segmentation development easier for marketers. For example, Salesforce’s CDP has an easy-to-use interface, a standardized data model, and drag-and-drop functionality to enable marketers to build segments without being reliant on a developer or an IT team to write SQL statements.
Activate segments for a personalized omnichannel experience
By activating these segments to tools like Salesforce Marketing Cloud, marketers can deliver real-time, automated personalization to customers. And because many activation tools can feed engagement data back into the CDP, marketers can continue to drive ever-increasing value with segment enrichment.
Types of CDPs
One of the reasons experts have varying definitions for CDPs is that there are different types or categories of CDPs with distinct strengths and uses. Some CDPs fall under just one type, while others can overlap into a couple of categories. It’s not uncommon for a marketing team to utilize multiple solutions labeled as a CDP due to the variation in types and features in the market today.
Personally, I place CDPs into one of the following types, often times based on the underlying technology:
An Enterprise CDP, like Salesforce CDP, is meant to work across the enterprise and be part of an enterprise suite of products. It should have robust data storage, data harmonization, and identity resolution features. As a connected solution, integrations with external data sources and data targets should be prioritized. An enterprise CDP should not strive to be an all-in-one point solution, and instead should focus on the core CDP capabilities.
Streaming Event / Tag Management CDPs
A number of CDP tools are, at their core, sophisticated real-time event processors. They accept large volumes of data based on user actions, oftentimes on a website. Rules then exist to place individuals into a segment for later use or calls are made to external systems to initiate actions. Most CDPs in this category have had a data store added on to allow a full view of all events over time. These types of CDPs are great point solutions when a specific use case arrives.
Many solutions that focused on providing AI-based recommendations or next best actions have also adopted the CDP label. These are similar to the streaming event CDPs in that they often have large volumes of real-time data coming in, but their purpose is to use that data to build affinity models, provide product or content recommendations, and use AI to determine next actions. Many can operate in multiple channels, but a key strength is often the web channel. These are also great point solutions, especially in an ecommerce setting.
Now that we’ve scratched the surface of CDPs, check out these resources to learn more about how marketers can leverage this powerful technology.