What is a Customer Data Platform?

Learn more about what a Customer Data Platform (CDP) is and how you can make sense of the rapidly evolving Customer Data Platform market.


In the past few years, several market shifts have led growth teams to rethink the way that they connect, govern, and activate customer data. New legislations, such as GDPR and CCPA/CPRA, have increased the importance of managing user consent. Elevated customer expectations have led brands to focus on delivering contextual experiences across channels in real time. The extreme rise in tools available to help marketers and product managers deliver such experiences have led teams to favor a best-of-breed approach to tooling, making it important to prioritize data interoperability across tools.

The legacy method–maintaining fragmented customer data in DMPs, CRMs, Enterprise Data Warehouses, and "stitching" it all together with MDM or ETL solutions–is breaking. In the modern context, it’s become too cumbersome to maintain tech debt, manage data quality across systems, and ensure data privacy over time. 

These new priorities call for new systems. Customer Data Platforms (CDPs) have become a favored technology amongst Product Managers, Developers, and Marketers in recent years due to their capability to simplify the data pipeline and support more contextual customer experiences. That said, the rapid evolution of the CDP market has led to some (warranted) confusion of what exactly a CDP is.

What is a Customer Data Platform?

While the category was originally formed around 2013, the Customer Data Platform space first began to generate awareness around 2017. At that time, many adjacent solutions, such as tag managers, analytics tools, and marketing automation platforms, began to brand themselves as CDPs, resulting in a cluttered market.

Generally, a Customer Data Platform is a centralized data infrastructure that aims to aggregate and make sense of a company’s customer data. 

There are five key functions of a CDP:

  • Data collection: The ability to ingest first-party, individual-level customer data from multiple sources via packaged API connections and SDKs, and store that data in a usable format
  • Data governance: The ability to granularly enforce which events gets passed onto each system, and process data subject requests - access, portability, erasure
  • Data quality protection and profile unification: The ability to monitor data accuracy, consistency, deduplication, and structure, and to unify events and attributes to persistent profiles at the individual-level as data is collected
  • Segmentation: An interface that enables business users to build and manage audience segments
  • Activation: The ability to send audience segments and forward events to external tools and systems through pre-built integrations, as well as to orchestrate contextual marketing experiences across channels

It’s worth noting that not all CDP vendors accomplish each of these functions to the same extent, and therefore the ways in which teams adopt CDPs is still varied.

What are the different types of Customer Data Platforms?

According to the CDP Institute, there are currently well over 120 different companies that offer CDP solutions. Sorting through the noise of the CDP market has been difficult for even the most industry-savvy teams. That said, several distinct categories of CDPs have begun to emerge: Infrastructure CDPs, marketing cloud offerings, application-layer marketing hubs, and CDP tool kits. While most share some overlapping capabilities -  identity resolution, segmentation, API integrations - the deployment choice between them is significant.

  1. Infrastructure CDPs
    Infrastructure CDPs establish a new foundational data infrastructure layer to help teams move data freely and securely between systems and applications in real time, while managing data quality and protecting consumer privacy. Using embeddable SDKs and APIs, these CDPs collect 1st-party data from multiple customer touch points (Mobile, Web, OTT, POS systems, and more). Data is then cleansed and linked to individual customer profiles before it’s sent downstream to best-of-breed advertising, marketing, operational and analytics systems. While adoption of infrastructure CDPs requires initial investment from engineering teams, post-implementation they provide self-serve data routing capabilities to non-technical teams, such as Product, Marketing, Analytics, and Customer Support. Included in these capabilities is the ability to leverage predictive insights to create audience segments. Once built, audience segments can be connected to marketing engagement tools for personalized campaigns. This functionality saves thousands of development hours in the long run.
    Example vendors: mParticle, Segment
  2. Marketing Clouds
    Several of the large multi-suite martech cloud companies have announced a CDP solution within the last 24 months. The cloud offerings aim to introduce a CDP module, as part of an integrated suite, that facilitates profile unification, segmentation and data activation. However, these products typically limit data sources and destinations to the cloud’s suite of products, promoting vendor lock-in and discouraging a best-of-breed approach to building your data stack.
    Example vendors: Adobe, Salesforce, Microsoft
  3. Multi-Channel Marketing Hubs
    Multi-channel marketing hubs make up the vast majority of vendors claiming to be CDPs. These providers offer data orchestration capabilities that facilitate marketing initiatives, such as offer management and triggered messages, by sending instructions to multiple downstream solutions from within their interface. Typically, these vendors are heavily reliant on data ingested via batch imports from 3rd-party sources, as opposed to collecting real-time, 1st-party data. This often results in a lack of data quality, as  aggregated data can be inaccurate or filled with inconsistencies. These CDPs like to tout features targeted towards marketers, BI analysts, and other “data consumers,” such as journey mapping, reporting and nascent machine learning capabilities. Unfortunately, they lack the data foundation required to deliver on these features in an impactful way.
    Example vendors: Amperity, Lytics
  4. CDP Toolkits
    These are ideal for developer-led teams that may want to integrate a CDP into their core application and utilize basic features, such as discovering segments and performing advanced analytics, on top of their 1st party data. Scalability of these solutions is limited to niche features when compared to a solution that can meet multiple enterprise needs across functions. Also, building and maintaining a CDP in-house tends to increase the total cost of ownership overtime, as any data plumbing necessitates significant help from expensive developer resources.
    Example vendors: Rudderstack, Jahia jCustomer.
Different kinds of CDPs

How can you determine which kind of Customer Data Platform is right for you?

The complexity of the CDP market shouldn’t stop you from finding the solution that is right for your team. Here are several guiding questions you can use to understand which vendors you should be focusing on:

  1. Which tools are you currently using?
    The foundational value of a Customer Data Platform lies not just in what happens within the CDP interface, but also in its ability to make high-quality customer data available in all of the tools and systems in your growth stack without draining developer resources. It’s really important to make sure that any CDP you are considering integrates with the tools that you are using. If you’re interested in forwarding data to your CDP from another tool, such as a BI system or attribution tool, check that each CDP has the necessary feed integrations available. Furthermore, these integrations should be well built, easy for business users to connect, and able to forward data in real time.
  2. Where do you need to collect data from?
    Ensuring that you can get data into your Customer Data Platform efficiently is critical to CDP success. The vast majority of Infrastructural CDP providers are proficient in collecting customer data from web. If you have a mobile app or OTT app, however, make sure that any CDP you’re considering also has the ability to collect customer data through a native iOS or Android SDK, and additionally that that SDK is lightweight and stable. If you’re interested in sending data to your CDP from the server side, check that a CDP has an HTTP API that will enable it to collect data S2S. Marketing hub CDPs often rely on data ingested via batch imports from 3rd-party sources, as opposed to collecting real-time, 1st-party data. Little ownership over the data collection process can lead to data quality issues throughout your data pipeline.
  3. What do you need to use your customer data for?
    The functions that you expect to execute with your Customer Data Platform will also have an impact on which vendors you should be considering. If you’re including the ability to run simple machine learning, message orchestration, and analytics on 3rd-party data within your CDP, you may be interested in exploring application-layer Marketing Hub CDPs. If, on the other hand, you favor using leading engagement tools, specific product analytics systems, need to be able to collect 1st-party data from multiple sources at scale, and/or have advanced identity resolution capabilities, you’ll want to consider an infrastructural CDP. Infrastructure CDPs, such as mParticle and Segment, will handle complex data collection, identity resolution, data quality protection, and data connection at scale so that you can save engineering hours and use your preferred downstream tools more effectively.
  4. How much flexibility do you need?
    Business strategies shift, and the martech ecosystem is constantly evolving. If flexibility is important to your growth strategy, it’s important that your CDP enable you to test new tools, collect data from new sources, and change your data schema when you need to. It’s also important that your CDP partner has a history of successfully building new integrations. Marketing cloud offerings, such as Salesforce Customer 360 and Adobe Real Time Customer Data Platform, will favor sharing data with their own applications and therefore may make it more difficult to share data with new external tools, leading to vendor lock-in. Independent CDPs, on the other hand, are agnostic of where you send your data, making it easier to stay agile.

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