Learn why next-generation CDPs are a key driver of modern customer experience strategy including their 5 defining capabilities, how they evolved, and top CDP benefits
A customer data platform (CDP) is “packaged software that creates a persistent, unified customer database that is accessible to other systems,” according to the Customer Data Platform Institute (CDPI). In its simplest form, a CDP brings known and unknown customer data together into one view, bridging the gap between customer relationship management systems (understanding known customers) and data management platforms (understanding context, but with unknown customers).
CDPs are a relatively new category for marketing technology (MarTech), gaining their name in 2013 from David Raab, founder of the CDPI. The CDPI also developed a RealCDP certification program that outlines five defining capabilities of a CDP:
Simply put, CDPs help unify customer data to make marketing efforts more effective. They are designed specifically to drive relevant customer interactions, communications, and engagements.
However, CDPs are beginning to evolve for use at an enterprise level, building on the designed-for-marketing foundation by bringing in more advanced capabilities, like governance and continuous analytics. A “next-gen” or enterprise CDP consolidates and manages structured and unstructured customer data—which can include a trusted customer profile along with demographic, firmographic, psychographic, behavioral, transaction, interaction, and intent data from internal, external, and third-party sources—in a single database. The next-gen CDP then makes that data easily accessible for deep analytics, marketing activation, and for broader customer experience initiatives across marketing, sales, and support. Other systems and processes can use the trusted data to inform marketing segmentation, personalization, and next best actions. For a closer look at next-gen CDPs, read our blog.
Here are a few things you can do with an enterprise CDP:
The roots of CDPs extend back to the 1990s, when customer relationship management (CRM) systems emerged as tools that promised to help organizations keep track of information about their known customers. In the 2000s, the mushrooming volume of digital interactions and data sparked the introduction of data management platforms (DMPs) in AdTech. These systems allowed organizations to enrich their data with third-party sources and create customer models based on unknown customers to inform and drive digital ad campaigns.
CDPs emerged in the mid-2010s as a way to combine both customer (CRM) and context (DMP), incorporating features such as multichannel campaign management, tag management, and data integration into a single solution.
Although CDPs have existed as a defined technology for a relatively short time, they’ve already caught the attention of analysts. Gartner notes that “The CDP helps marketers integrate and activate their first-party data. As the market matures, CDPs have the potential to become a system of record, transforming marketers’ ability to deliver consistent, targeted, contextually relevant experiences across channels.”¹ (Gartner named Informatica a leader in five Magic Quadrant Reports.² See why.)
Moving beyond marketing and delivering that ideal mix of customer and context requires CDPs that can interact with a variety of existing systems that capture customer data, such as Adobe, Oracle, and Salesforce, without requiring vendor lock-in. CDPs are also starting to extend into other areas such as service, sales, and product data. That makes it imperative to choose a CDP that is capable of supporting enterprise requirements and use cases.
It’s simple business sense to focus on customer experience: According to a PwC study, customers would pay up to a 16% premium on products and services if they get a great customer experience—but 32% of all customers would stop doing business with a brand they loved after one bad experience.
With a customer data platform strategy, you can perform advanced analytics on your combined customer information and use the results to predict the next best action for any customer in any context, from marketing campaigns to customer service. That means a better and more satisfying experience for your customer, which can turn into greater loyalty, an expanded relationship, and ultimately more sales and business opportunities.
A CDP supports marketing and analytics use cases that help to drive micro-segmentation, hyper-personalized offers and communications, next best action or offer, and superior customer experience. A CDP creates valuable context at enterprise scale so teams across your organization can develop and answer complex questions about your customers. And as a result, you can deliver the most timely, relevant, engaging experience to customers and prospects across every touchpoint and channel.
By using customer behavior and relationship data to proactively identify areas of potential friction, you can avoid missteps that could cost you a customer's loyalty—and possibly their business. For example, banks don’t want to waste time offering home refinancing to customers who don’t have mortgages with them. A CDP allows the bank to identify specific customers who already have mortgages, as well as:
As data privacy regulations proliferate worldwide, data privacy and consent management has become an intrinsic component of customer experience. However, this can create a point of friction between departments, as consent management requests must be addressed in a timely manner and any changes applied to all instances of that customer's data. As a central collection of trusted customer data, CDPs are poised to support this effort. An intelligent CDP can help you quickly locate a customer’s data and take action on it—a key component of maintaining cost-effective compliance with the CCPA data privacy regulations. Because CDPs are still evolving, data privacy components are not yet standard functionality; several vendors explicitly expect you to manage the anonymity of your own data. If you’re considering a CDP as part of your customer data strategy, be sure to check for the ability to understand who customers are and their data usage content information.
¹ Gartner, Hype Cycle for Digital Marketing and Advertising, 2019, Mike McGuire, Colin Reid, 12 July 2019.
² Gartner, Magic Quadrant for Enterprise Integration Platform as a Service, Eric Thoo, Massimo Pezzini, Keith Guttridge, Bindi Bhullar, Shameen Pillai, Abhishek Singh, 21 September 2020; Magic Quadrant for Data Integration Tools, Ehtisham Zaidi, Eric Thoo, Nick Heudecker, Sharat Menon, Robert Thanaraj, 18 August 2020; Magic Quadrant for Data Quality Tools, Melody Chien, and Ankush Jain, 27 July 2020; Magic Quadrant for Master Data Management Solutions, Simon Walker, Alan Dayley, Sally Parker, Malcolm Hawker, 13 January 2020; Magic Quadrant for Metadata Management Solutions, Guido De Simoni, Mark Beyer, Ankush Jain, 16 October 2019. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.