What is a Customer Data Platform (CDP)?

What is a Customer Data Platform?

 

A customer data platform (CDP) is a software application that supports marketing and customer experience (CX) use cases by unifying a company’s customer data from marketing and other channels. The CDP Institute defines a customer data platform as packaged software that creates a persistent, unified customer database that is accessible to other systems. Unlike a data warehouse or data lake, a CDP is usually bought and controlled by marketers or business users.

A customer data platform creates a comprehensive view of each customer by capturing data from multiple systems, linking information related to each customer and storing this information to track customer behavior over time. Data stored in the CDP can be used by other systems for analysis and to manage customer interactions. The CDP restructures the data, adds calculated values and shares the results in formats other systems can accept. These features distinguish a customer data platform from other systems that work primarily with their own data, store limited details for limited periods, do not maintain a permanent database or systems that directly interact with customers.

A CDP can manage any type of customer data. It enables an operational data environment that ingests an enterprise’s data from all sources – whether batch or streaming, internal or external, structured or unstructured, transactional or demographic, personal or general – that provides an always on, always updating unified customer profile (also known as a golden record) and makes it continually available at low latency to all touchpoints and users across the enterprise.

A complete, robust customer data platform will satisfy any use case for interacting with a customer, household or business entity with high ROI and low TCO. Cleansed and ready-to-use real time data and flexible, re-usable segmentation support real-time interactions, personalization, product recommendations and other last-mile interactions with the customer. A complete CDP may be used as a standalone, closed-loop system, and in concert with an existing organization’s MarTech stack, integrating with any customer-facing technology such as CRMs, ESPs, DXPs, DMPs and MMHs.

In addition to creating a unified profile of each customer, integrating all that is knowable about that customer, and making the profile accessible to any technology across the enterprise, at its core a customer data platform should:

• Ingest all messy customer data and fix it – as data is ingested into the system
• Resolve identities at individual and relationship levels to create a unified customer profile that is accurate and always ready for business use
• Empower business users to visualize customer data, build reusable segments without code, and activate it in different channels and CX programs
• Make the unified profile available to drive any enterprise application

Four Key Capabilities of a Customer Data Platform

 

Automated Data Ingestion & Data Quality

Seamless data integration and superior data quality are must-haves for a customer data platform.  A CDP must welcome any and all data; data from every source and every type all hold important clues about a customer’s behaviors, preference and patterns – which paints a complete picture of an individual customer.

Volume alone, however, is not enough to ensure an accurate unified customer profile, which is where automated tasks come into play for managing even the most complex data. Cleansing, matching, advanced identity resolution, persistent keys and enrichment are all vital for returning a unified profile that combines every customer identifier with complete behavioral and transactional data.

Unification & Identity Resolution

Once a CDP pulls together customer data, it is important to resolve the identities of individuals across devices and channels. Advanced, tunable identity resolution using a combination of deterministic and probabilistic matching should also resolve identities in the context of an individual or household level, business grouping or other entity.

Identity resolution is the process of finding, cleansing, matching, merging and relating all the disparate signals (martech touchpoints, enterprise systems, databases/data lakes) about a customer to produce an accurate, complete and up-to-date view. Identity resolution is instrumental for building a Golden Record which, when updated in real time, provides a deep understanding of a customer’s preferences and behaviors and is the basis for marketers to orchestrate relevant, personalized omnichannel experiences.

Data Observability and Measurement

Managing data quality is one of the most challenging issues facing IT organizations today. At every step of the data lifecycle – entering, storing, associating and managing data – there is a risk of introducing errors. Data quality is paramount to ensure relevant, personalized experiences across an omnichannel customer journey. Ensuring that data is perfected and ready for use is a function of data observability.

Data observability provides marketers confidence that a CDP’s data is in good health, alerting them to any data issue before it impacts customer experience. By alerting marketers and business users to data issues, it gives them the opportunity to tune or fix campaigns and analytics with trusted data.

Segmentation & Activation

Dynamic, AI-driven segmentation in a no-code environment is an important customer data platform function for creating meaningful audiences, even amid a constantly changing customer journey and updated Golden Record. Dynamic segmentation maximizes customer lifetime value through insight-driven targeting based on customer behaviors, choices and actions and informed by audience profiles, visualizations and propensity models.

By leveraging generative AI to build segments, marketers have the needed tools at their fingertips to power both proactive and reactive customer engagement across dynamic customer journeys.

A complete, robust CDP is the foundation for great customer experience across all customer journeys – marketing, service and support – and an indispensable solution for building long-lasting brand loyalty and driving tangible revenue growth.

How Does a Customer Data Platform Help Understand Customers Better?

 

The key to delivering superior customer experiences is creating, maintaining and effectively utilizing perfect data about each customer. The fundamental building block of perfect data is first-party data. Everything else is just a form of proxy for trying to identify and understand the customer.

Perfecting an organization’s own first-party data with advanced identity resolution processes, data cleansing and enhancement at the moment data is ingested from every source is vital to ensuring that organizations interact with the right customer, household or entity. Relevant, valuable interactions depend on the organization really understanding who the customer is, and that requires high-quality data sets that are both accurate and timely.

For the customer, that value is measured by consistent relevance across an omnichannel customer journey. A brand must recognize an individual customer across every channel and engagement touchpoint, demonstrated by the delivery of a frictionless experience.

Achieving and persisting relevance is dependent on a deep understanding of the individual. The key ingredient – perfect data. In return for a superior personalized experience, customers say they are willing to share more about their needs, preferences and behaviors. The insights derived from this data are what will build the relationship and increase opportunities through delivering better personalization.

How Customer Data Transforms Customer Experience

 

There are many ways in which customer data can be utilized throughout the customer experience. With a customer data platform, enterprises can:

• Enhance Personalization: Delivering next-best action recommendations and personalization based on preferences to customers no matter where they are in the customer journey.
• Improve Customer Engagement: Understanding the customer can help the organization shape the engagement as well. For example, a customer could automatically be suppressed from communication that would be duplicative or have content be replaced in real time for something that is accurate.
• Support Data-Driven Decisions Making: Data understanding and data visualization enables decisions at all levels of an organization to be made based on real data without the need of a data scientist to interpret that data.
• Optimize Marketing and Sales Efforts: A CDP can streamline communication holistically, not driven by channel needs, often reducing the touchpoints while simultaneously increasing the return on investment.