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The Five Major Components of a Customer Data Platform

The Five Major Components of a Customer Data Platform

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Thinking about implementing a CDP? Understanding the main components of a customer data platform (CDP) is a good way to make the decision.

A CDP is not a marketing campaign execution tool, but it does provide a solid foundation for marketing personalization. While a CDP is frequently employed to better orchestrate the customer journey, that isn’t the only reason you’d want to consider using a customer data platform. The unified customer profiles built in a CDP can be made available to sales and service teams so that they can close more and bigger deals and provide better customer support.

In the previous blog post, we discussed why your organization would want to consider implementing a customer data platform solution. 

There were six main reasons discussed

  1. Increased demand for personalized customer experiences
  2. The customer data problem of siloed data
  3. Need to track multi-touch points 
  4. Demise of third-party cookies in 2024
  5. Government regulations regarding privacy
  6. Unified profiles can be used in data clean rooms

It’s not unusual for sales and service teams to work with some of the same technology tools. For example, an organization’s customer relationship management (CRM) system is a commonly shared platform. 

CRM systems were designed to collect first-party data about an individual customer, member, patient, or donor, depending on the use case. A CRM can also be used to collect first-party data about companies or organizations. First-party CRM data will likely include name and contact information, at a minimum. 

In contrast, there are some tools and platforms used primarily by marketers. One such example is a data management platform (DMP) that can be used to segment audiences and optimize ad spend. A DMP is a cookie-based solution that temporarily stores second and third-party data about audiences and advertising campaigns. As we learned in the previous blog post article, third-party cookies are going away in 2024, which is an important reason why a CDP implementation could be worth considering sooner rather than later. 

Five main components of a customer data platform (CDP)

A customer data platform is a repository for large quantities of internal and external customer data. CDP input data sources often include data from an organization’s customer relationship management (CRM) system and data management platform (DMP). Both CDPs and CRMs are persistent, long-term storage solutions, whereas DMPs generally have shorter retention periods around 90 days or so.

Customer data platforms generally include at least five major components which are described next (see figure below). There is one caveat. Consent management is a very important item not always included in the requirements for a customer data platform. If you use a CDP for marketing use cases, however, you’ll need to consider how to manage and track consent.

1. Data Ingestion and Storage

At its core, a CDP must provide a data storage component where all the customer data is securely stored and managed. Additionally, you will need to have a way to bring all the customer data into the storage layer. Data ingestion for external data sources is usually automated by using various connectors. It’s very important to consider data governance as part of this component. Depending on the CDP selected, your organization could be responsible for all data governance requirements. 

2. Data Modeling and Processing 

Before ingesting data into your CDP, you’ll want to design and create your data models. It’s a good idea to build a data dictionary as part of the data modeling exercise, prior to data ingestion. Creating a data dictionary will help highlight any formula fields to be created and data transformations to be undertaken. 

3. Identity Management and Consent Tracking

Data matching and identity resolution are the next critical steps to achieving a unified customer profile once data is ingested and securely stored in a CDP. Identity stitching, accomplished by analyzing and resolving data across multiple touchpoints, systems, and attributes, ultimately helps us better understand a customer’s interests and needs. Identity resolution can be achieved using both deterministic matching, best used with first-party data, and probabilistic matching. 

4. Profile Enrichment and Audience Building

After reconciling identities, you’ll be able to enrich those identities with external data sources. Once the holistic unified profiles are available, you’ll be able to extract information to be used for analytical purposes. For marketing use cases, you can also use unified profiles to create segments and audiences for marketing campaigns. 

5. Actions and Insights 

This component makes data in the data layer accessible to machine learning tools or other platforms where the data can be used to achieve actionable insights. With actionable data, organizations can better orchestrate the customer journey. Targeted actions also make it possible to engage with customers in real-time. For example, a customer searching for product installation instructions on the website for a recently purchased item could automatically be sent an email with the needed information. 

Explore types of CDP solutions available

Some customer data platform solutions, such as Salesforce Data Cloud can be purchased as a full product suite with all major components included in one platform. Another approach to acquiring a CDP would be to build your own customer data platform. 

Most organizations that build a customer data platform opt for a composable CDP which allows individual best-in-breed module selection and combination to satisfy their CDP requirements. Both of these customer data platform acquisition approaches are discussed in more detail in the next blog post.

Remember to reach out to the team at Sercante for guidance when you’re ready to implement a CDP at your company or organization.

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  • Joyce Avila has a diverse work experience spanning over several industries and roles. Joyce currently holds the position of Program Lead, Data Cloud at Sercante.

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