What is a Customer Data Platform (CDP)?
The Ultimate Guide to Building a Customer Data Strategy
Overview
A Customer Data Platform (CDP) is a marketing software application that helps brands unify all available customer data to power personalized experiences.
Today’s interactions are increasingly complex, both in-store and online, and adjusting the right message for the right customer is critical to the success of the customer experience as a whole.
Marketers tend to view the marketplace based on the channel of interaction (email, in-person, SMS, Facebook, etc.) but from the consumer standpoint (the purchaser, the patient, the consumer) it becomes obvious that the entire experience is as important as any of the channels where an interaction takes place. Throughout that process, a consumer has researched multiple avenues, and taken steps to decide on a purchase or course of action. If the brand delivers the customer experience well, with each step in the process consumers feel the message is more targeted to them on a personal level. He or she may wonder how is this personalization achieved in a complex landscape for millions of consumers?
By unifying all available data, building a Golden Record and creating and activating dynamic segments at scale, a CDP powers omnichannel personalization at scale.
Additional Resources
Defining a Customer Data Platform
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.
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.
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What is a Single Customer View/Golden Record?
One of the most powerful aspects of a customer data platform is the ability to build and maintain a golden customer record at the speed of the consumer. The single customer view, or Golden Record, that a customer data platform provides will give a deeper understanding of a customer’s preferences and behaviors. It should include every touchpoint or proxy identity the consumer presents, such as a cookie, a social media handle, device ID, smartwatch, nicknames and all known email and physical addresses.
Each customer’s Golden Record should also include transactional and behavioral data, as well as other triggers. This single central source of customer golden records unifies data across typically siloed internal and external sources, and handles data of every conceivable type, cadence and source. This is radically different from other data sources and elements in the Martech Stack, which are usually channel-specific and narrowly focused, and often are batch-driven or at least much slower to update than customers’ journeys and actions. By having real-time access to customer data, brands can engage in clientelling and create more personalized experiences that meet the customer’s unique needs and preferences.
The transactional data should include the history of all transactions and interactions that a person represented by a proxy identity has had with the brand. Behavioral and transactional data should be integrated into the golden record in real time to ensure that analytics, personalization and engagement are relevant and up to date.
Useful Resources to help make better marketing decisions
What Are the Benefits of a Customer Data Platform?
For a robust, enterprise-grade customer data platform, managing data entails applying data quality, identity resolution and governance processes at the point of data ingestion, ensuring a single view of the consumer throughout an entire customer journey. Ultimately, a customer data platform can deliver a personalized customer experience based on an organization’s own use cases and can do it in a timely, scalable manner.
A customer data platform can meet a variety of goals, but some of the primary benefits from a CDP include:
- Increased Efficiency: By bringing together relevant information from a variety of disparate sources vs. managing in silos you can have centralized control of your data. The ability to access and utilize accurate customer information across all areas of the business will save time and require less ongoing maintenance and management from IT.
- Insights and Analytics: As AI and machine learning are applied to unified customer data, the insights are increasingly targeted and available at a scale that would be impossible to see any other way. CDPs enable audience segments and provide insights without intervention of data scientists, with AI/ML built into the system for things like predictive recommendations, next-best actions, natural language processing, A/B testing and many other actionable insights in real-time that are not possible with traditional tools.
- Agility and Flexibility: Change is the only constant in today’s marketplace, requiring a system of record that can adapt with the needs of consumers in real time. A CDP that can work directly with the systems you have in place can take the data in your system and make it actionable, flexible and ready to meet the needs of the market.
- Privacy, Consent, and Compliance: In the era of GDPR, HIPAA and CCPA, regulatory pressure to comply and provide enhanced privacy is higher than ever before. Consumer awareness of consent and privacy compliance has also come to the forefront. The trust of the customer is at the forefront of delivering on these areas – and consent management is a key component of personalization within a CDP as well. A customer data platform that can embed consent and preference details into a single customer view offers the ability to deliver hyper-personalization no matter the scale of the business.
Just a few Integrations
What is a Composable Customer Data Platform?
Often when people talk about a composable CDP they’re referring to what’s called a zero-copy data or a data-in-place CDP, which means that your customer data sits in a data cloud. This is a distinction from the CDP having a built-in database in a traditional “packaged” CDP which is typically offered as software-as-a-service (SaaS) where the vendor hosts and maintains your data and builds a Golden Record on your behalf.
A composable CDP that runs in a data cloud and performs core CDP functionality without having to replicate data allows you to control your customer data behind your own security perimeter, while still connecting to all your MarTech touchpoints and enterprise data sources. A composable CDP is about choice, allowing you to bring together best-of-breed capabilities from one or more vendors to create a purpose-built, cohesive platform through API integrations to give you more flexibility and speed-to-value to achieve your unique CX and business use cases. This approach balances control with the flexibility to add or change components as your business and use cases evolve.
Customer Experience and CDPs
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.
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.
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.
Why Does Unification of Cross-Channel Marketing Efforts Matter?
Multichannel or cross-channel marketing is broadly defined as interacting with customers via multiple direct and indirect channels to sell them goods and services, engaging with customers in their channel of choice. Global multichannel marketing solutions make all channels available to the consumer (in-store, web, mobile, social, phone) for the purposes of engaging with a brand and may cross sell among a few of those channels.The need for a single customer view to engage with today’s always-on, connected consumer across an omnichannel journey highlights one limitation of multichannel marketing; the purpose of developing a single customer view is to understand how a customer interacts with a brand across all channels, not on a channel-by-channel basis. While a CDP can certainly support a multichannel marketing strategy, the technology is more suited to support omnichannel marketing, which integrates channels and eliminates data siloes and data latency to enable an organization to move at the pace of the customer throughout a dynamic, non-linear customer journey.
Omnichannel marketing more accurately reflects the way today’s consumers engage with brands across both physical and digital channels and online and offline touchpoints. The strategy enables a personalized, relevant experience that is always in the cadence of the customer journey wherever a customer chooses to engage. It enables consistent customer experiences where and when the customer interacts with the brand.
Real-Time Personalization and Real Impact
Real-time data is the lifeblood that provides brands with the depth of understanding required for delivering an omnichannel customer experience that aligns with consumer expectations. Enterprises must invest in systems that can handle omnichannel orchestration at a speed and scale that makes it invisible to the end consumer.
There is an important distinction to make between having a real-time view with respect to each channel, and a real-time view that spans the entire customer journey. A brand may have a real-time view into a customer’s browsing history, capturing clicks, time on page, opens, views, movements, etc., and use that information for real-time web personalization, but that data is typically not shared with other channels.
A classic example of how such a lack of transparency may introduce friction is an abandoned shopping cart. A customer may follow an abandoned cart up with a buy online, pick-up in-store (BOPIS) transaction, but lacking the real-time sharing of data across channels, a brand will miss out on valuable cross-sell or up-sell opportunities when the customer arrives in-store. Context and timing are crucial components in delivering the customer experience today’s consumers are demanding.