The Rise of Customer Data Platforms: How CDPs Move Beyond Data Warehouses, DMPs and CRMs

The right data foundation makes or breaks marketing strategies. Over the years, marketers have relied on a number of data platforms to manage and analyze their data. But because these systems were built for or managed by IT, marketers have been limited with how they could use their data to drive marketing execution.

Three commonly used data management systems are Data Warehouses, CRMs and DMPs.

Data Warehouses are vast, central, enterprise-wide storehouses of business data created to help organizations make better business decisions. These powerful repositories provide business analysts and data scientists with quick access to business data for use in their analytics applications and business intelligence (BI) tools.

• Primary Purpose: Data Warehouses support business intelligence and analysis. Their key benefit is faster access to a variety of business data.
• Data Types Supported: Data Warehouses aggregate data, including historic data, from various systems across marketing, finance, sales, and other functions. These include CRMs, ERPs, billing systems, supply chain systems, and other internal and external applications. Data Warehouses process and organize data into schemas to make it quickly accessible for analysis. They work best when data is consistent and well-defined.
• Intended Users: IT specialists and dedicated enterprise data management professionals with the technical background to manage the granular data and processes.
• Limitations for Marketers: Data Warehouses can’t support real-time customer engagement because they don’t provide real-time insight into cross-channel identities. Data Warehouses can’t process raw, unstructured, or complex data formats in which customer engagement data is generated. They don’t provide customer data at an individual level. They also tend to have static, latent data that’s updated weekly at most. Most importantly, Data Warehouses were created for offline use and weren’t meant to funnel data directly into marketing applications. Additional, manual data manipulation is required to get data into a usable state for marketing systems.

Customer Relationship Management systems, or CRMs, centralize all customer interaction and transaction information. Originally built for B2B sales and customer facing teams, CRMs have been adapted to support B2C use cases.

• Primary Purpose: CRM systems support direct customer engagement by managing and connecting customer accounts, attributes, and touchpoints at the user level.
• Intended Users: CRM systems are best utilized by sales, customer service, and direct marketing teams.
• Data Types Supported: CRM systems capture all historic customer engagement and transaction data for known customers generated across customer interactions. This includes data from brand touchpoints such as their website, email, mobile, offline channels, social media, order management systems, and payment data.
• Limitations for Marketers: CRM systems were designed to store customer engagement information, but not to activate it. They can’t make data available in real-time because they can’t rapidly ingest large volumes of data, process that data, or unify different data types, especially when that data has different identifiers. They also offer minimal system access and control to marketers. Furthermore, CRM systems only work with known users, typically those that have an email address and customer ID. In today’s cross-channel landscape, marketers need cross-devicel identity resolution that includes anonymous identifiers. By not capturing cross-channel identities and related channel data, CRM systems miss customers on key channels and can’t engage anonymous customers who are further up the funnel.

Data Management Platforms, or DMPs, help advertisers and publishers buy, sell, and manage digital advertising and optimize media spend by improving audience targeting. DMPs unify, store, and manage anonymous audience and campaign performance data, create rule-based audience segments, and connect audience segments to ad platforms.

• Primary Purpose: DMPs support digital advertising by providing high-value audience segments to target at the cookie-level and optimizing media spend based on segment performance.
• Intended Users: DMPs are utilized by advertisers, agencies, and publishers for awareness and customer acquisition use cases.
• Data Types Supported: DMPs consist mostly of third-party, anonymous audience and campaign performance data generated from digital interactions. They aggregate anonymous web-browser cookies and device IDs that contain audience information such as demographics, past browsing behaviors, interests, location, devices, and limited purchase information. They also enrich audience data with data from external data vendors. DMPs never store PII (personally identifiable information). While DMPs can onboard offline data, that data must first be anonymized.
• Limitations for Marketers: DMP use cases are limited to top-of-funnel display advertising and measurement. Because DMPs focus on broad, anonymous, cookie or device-level segments, they can’t support customer engagement and retention strategies. Furthermore, DMPs only store data for a limited time period, which hinders targeting precision.

With all the existing data platforms, why is there now growing interest in customer data platforms? Because marketers are still frustrated with their level of data access and activation.

Marketers don’t need yet another system to store customer data. They need a system that makes their data actionable and connected across their channels, and makes their marketing smarter and more effective. Legacy data platforms haven’t provided marketers with the control, flexibility, speed, insight, and connectivity they require. To support the 1:1 personalization that’s required to succeed in today’s fast-changing, digitally-connected landscape, marketers need their data platform to provide:

1. A single, comprehensive, persistent view of each known and anonymous customer that captures all customer interactions across every channel
2. Seamless, real-time data integration into marketing platforms and supporting applications
3. Real-time intelligence and marketing decisioning
4. A marketer-friendly interface

Customer Data Platforms, or CDPs, were purpose-built to provide marketers with data access, activation, control, and speed. Their sole focus is helping marketers deliver more relevant, responsive customer experiences by activating customer data in real-time while cutting out the time-consuming, manual work typically required.

While the industry is still debating the definition, CDPs focus on 3 key capabilities:

1. Profile Unification: CDPs provide marketers with a comprehensive, unified, persistent view of each known and anonymous customer. They can ingest any data typeーregardless of structure and complexityーprocess it, and make it immediately available for use across all systems. CDPs stitch together all historic and real-time customer data, including customer profile, behavioral, transactional, and brand interaction data.
2. Intelligence: CDPs provide a marketer-accessible interface to do advanced segmentation, create customized recommendations, orchestrate customer experiences, and more.
3. Decisioning: Most importantly, CDPs derive actionable insights from the single customer view and use it for marketing decisioning and guiding real-time marketing interactions across all their channels.

CDPs aren’t intended to replace existing data systems, but rather to unlock value from marketers’ siloed data and use it to drive marketing effectiveness and ROI. With CDPs, marketers can finally scale data-driven marketing and use their data to deliver the rich, real-time customer experiences they’ve been aspiring to for years.