Gartner defines a Customer Data Platform (CDP) as “a marketing system that unifies a company's customer data from marketing and other channels to enable customer modeling and optimize the timing and targeting of messages and offers.” With rising interest in the benefits of CDPs, more vendors – including giants like Microsoft and Salesforce – have entered the market.
The illusive Customer 360 isn’t just a requirement for marketing, however. Departments across the enterprise – customer service, compliance, sales, and product – also require access to a unified 360-degree view of customer data, which must go beyond interaction data to also include transaction and master data.
Whether commercial or homegrown, the fundamental challenge for a CDP is accessing and unifying the data from disparate data sources. Enterprise customer data is scattered across dozens or hundreds of operational and customer-facing systems. Getting a trusted, holistic, and up-to-date view of any customer isn’t an operations problem. It’s a data problem.
If we could start over again, we’d likely architect customer-centric enterprise applications differently, especially when it comes to customer data management.
Why? Enterprises typically have customer data fragmented across dozens of different systems, each one performing a dedicated function with its own siloed, application-centric data schema. There are applications for CRM, billing, web self-service portal, mobile apps, chat, feedback management, campaign management, marketing automation – the list goes on. Each merger or acquisition can double or triple the number of these systems. Meanwhile the sheer volume of data we collect on customers keeps rising, too.
To truly know each customer and make marketing campaigns more effective, today’s marketing teams need to leverage all this customer data. Enter the Customer Data Platform (CDP), with its focus on collecting customers’ multi-channel interaction data and enabling marketers to optimally segment the customer database for marketing campaigns.
From its humble beginnings in marketing, the CDP is increasingly becoming the one source of truth for all customer data across the enterprise—digital interactions, transactions, and master data—with the promise of serving many departments for a variety of use cases.
Marketers adopt a customer data platform (CDP) to operationalize the enterprise’s collective customer data. They hope to segment customers based on their past interactions, demographics, and other customer data, to personalize the messages and offers they send out to customers. However, the use cases for having a single repository for everything the enterprise “knows” about its customers go far beyond the marketing team.
In the beginning, marketing teams selected and managed their CDP tools, for their own use cases, with customer data being marketing oriented – namely, multi-channel interaction data typically refreshed by batch integration processes. However, IT departments in enterprises are increasingly realizing the benefits in centralizing customer data for the benefits of the enterprise beyond just marketing. This means CDPs must quickly evolve if IT is to consider them as solutions to broader enterprise use cases.
Despite their promised value to marketing and other teams, most CDPs have a fundamental problem that prevents them from flexibly meeting not only marketing’s needs but new use cases as they arise. Namely, enterprise customer data remains siloed in scores of systems and fragmented across even more data islands. Providing real-time access to and control over all that customer data—and a single 360-view of any customer at any time—is mission impossible for most large organizations.
Traditional approaches to handling such data fragmentation simply don’t work for the modern enterprise.
If the enterprise could overcome the core customer data management problem, it could enable a CDP to more easily handle operational use cases beyond marketing. It must provide segmentation, analysis, and reporting engine marketing demands of it, but it must also serve real-time analytics, CRM systems, churn prediction engines, and any other system that needs access to customer data. And since every organization has its own unique mix of legacy systems (not just COTS applications), it’s imperative the CDP be extensible and customizable. A CDP with a rigid, marketing-focused data model and UI may find itself out of the running and obsolete.
If we could solve the data problem first, what more would an organization want from a truly flexible, extensible CDP? Or does it need a solution beyond a CDP?
An enterprise that requires a central, unified, customer repository to serve its various departments – from marketing, through customer service, to risk and compliance – in actuality must implement a Customer Data Hub (CDH), which differs from a CDP in the following ways:
Today, more and more enterprises are realizing that the value of a single customer view goes far beyond marketing, to also answer the needs of customer service, compliance, sales, and product teams.
Enterprises understand the necessity for a customer data hub that unifies customer journey data with customer transactions and master data, to support many different operational and analytical use cases.
No one will argue that the enterprise will continue to place ever-higher demands on customer data hubs, going far beyond CDP’s marketing-centric roots.
Customer data hubs will need to contend with fragmented customer data including customer transactions, interactions and master data – spread across dozens, if not hundreds of disparate enterprise systems and databases, the massive amount of data in those silos, and the need to deliver customer data in real time to a wide variety of applications supporting a broad range of operational use cases.
The customer data hub serves as a single source of customer data for CRM, campaign management, data privacy, customer analytics, or any other customer data-centric application. By abstracting the data integration, data governance, and security away from the consuming applications, the applications can focus on the value they deliver, not the complexities of enterprise data management and data integration. This is the true opportunity and the key to a rapid, efficient, scalable, and (yes) end-to-end customer data solution that can tame even the most fragmented data environments.
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