What is a Customer Data Platform (CDP)?

Four Key Capabilities of a Customer Data Platform

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. Here are the core capabilites that should be included in all CDPs.

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 CDP should offer 4 core capabilities: Automated data ingestion and data quality, unification and identity resolution, segmentation and activation, and data observability.

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 (also known as a Golden Record or Customer 360) 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.

What Are the Benefits of a Customer Data Platform?

We live in an era of extremely high customer expectations. Today, most modern brands know that they need to put the customer at the center. However, despite have having more data and technology, CX is on the decline, according to the Forrester CX Index. There is a huge opportunity for improvement. In fact, brands that get it right can earn $10s to $100s millions for every one-point increase in Forrester’s CX index.

The CDP is the foundation for understanding your customer. It brings together data from all of a brand’s different sources, fixes it, and makes it available for campaigns across the enterprise.  It provides an actionable understanding of the customer so Marketers can drive truly personalized experiences across any channel or touchpoint, whenever and wherever the customer desires, so they feel valued and understood. Companies that achieve this type of personalization at scale experience higher satisfaction rates, higher sales conversion rates, and reduced sales and marketing costs.

Redpoint CDP users experience these benefits.

Additional benefits 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.

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.

Yet composability as a concept has been over-marketed to the point of confusion. When choosing a composable system, it’s important to take a balanced approach. Consider whether the various components you choose will meet your requirements, and not become an operational nightmare. You may end up with interface to pull in your data, another for identity resolution, a third to create a segment — likely using SQL — a fourth for your reverse ETL and to activate your segment, etc. Not a single application encompasses the whole business function of bringing in your customer data, creating a trusted unified profile and activating it to your end channels in a controlled way.

Some composable CDP vendors focus on one area, versus the entire spectrum of CDP capabilities.

How a Customer Data Platform Supports Omnichannel Marketing

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.

Yet today’s consumers expect an omnichannel experience. The always-on, connected customer wants a consistent, streamlined experience between physical and digital channels and online and offline touchpoints.  This requires a single customer view.

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 certainly supports a multichannel marketing strategy, the true magic happens with it is used to support omnichannel marketing. The CDP 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. This 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, driving exceptional brand loyalty.

Real-Time Personalization for 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.