B2B customer data platforms take center stage

CDP deployment is fast-growing in the B2B sector, but what exactly is driving it and why is it important? David Raab writes

Interest in Customer Data Platforms (CDP) has grown sharply since 2016. Although original deployments were primarily among retail and media companies selling to consumers, the concept has recently attracted great interest among B2B marketers. In fact, the CDP Institute’s latest research shows that 34% of B2B companies plan to start deploying a CDP in the next year, compared with just 19% of B2C companies. Reflecting and leading the change, B2B predictive analytics and data vendors including Radius, Lattice Engines, and Leadspace now position themselves as CDPs.

What’s driving the shift? And, come to think of it, just what is a CDP, anyway?

CDP is still unfamiliar to many B2B marketers, so let’s answer that second question first. Simply put, a CDP is packaged software that collects a company’s customer data, links all information related to each individual or account, and shares the result with other systems. Where things get challenging is that CDP is supposed to collect all data, not just the limited information stored in a CRM or marketing automation system, and it’s supposed to store that data, not just read it from source systems on demand. Those qualifications distinguish CDPs from many other systems which connect only some sources and don’t store their own copy of the data. That copy is needed for the CDP to identify individuals and companies over time, despite changes in their identifiers (such as a new email address or phone number); to perform time-based analysis such as trends, journey tracking, and lifetime value; and to enable real-time completion of complex calculations such as predictive model scores. The value of sharing data with other systems is self-evident – it gives all systems access to complete and consistent data while eliminating duplicate data stores – but it’s another requirement that is often not fully met by marketing clouds or suites that primarily integrate their own components (and often not even those).

Why does CDP matter? 

Few marketers will have trouble answering that question: the problems caused by data spread across multiple systems are all too familiar in most B2B marketing organizations.  Even a small B2B company today has dozens of systems holding different pieces of the customer data puzzle. Assembling those pieces into a complete picture without a CDP is a complicated task that few B2B marketing departments have the resources to complete on their own. Yet a complete picture is essential to understand customer and prospect needs and to deliver the unified, relevant experience they’ve come to expect. So, to answer the original question directly, the shift to CDP is driven by recognition that CDP solves a critical problem that isn’t being solved by anything else.

Circling back to the predictive modeling vendors, they are logical sources of CDP systems because predictive modeling works best when the modeling system has access to a complete customer view.  As a result, the predictive modeling vendors were among the earliest companies to develop the unified view that’s at the center of the CDP. These vendors also quickly recognized that their models would work better if they could assemble business data from the web and other sources. This let them build more complete profiles by connecting identifiers which might otherwise not be recognized as belonging to the same entity and by including company and personal information which their clients were not able to capture for themselves. As it became clear that the unified data could be applied for purposes beyond predictive modeling, the vendors shifted their focus to the database itself – leading them directly into CDP territory.

Some of those key applications include:

  • Customer profiling, to understand your existing customers, identify the characteristics of best customers, and estimate market size.
  • Customer journey analysis, to understand the path that customers follow on the road to purchase and find where non-buyers go astray.
  • Customer journey tracking, to understand the current state of individual customers and prospects, in order to identify risks of lost business, opportunities for new business, and their position in the buying process.
  • Message selection, including the best message and channel for each person at the current moment, data to personalize messages accurately, and orchestration of messages over time and across channels.
  • Account-based sales and marketing support, using the CDP to aggregate information to the account level to provide a more accurate view of each account as a whole.
  • Performance measurement, using the comprehensive CDP data to measure program, channel and content effectiveness.

Most companies will be interested in all of those benefits, but priorities will differ based on your business situation and existing resources. In some cases, the B2B CDP will be a new product added to your existing martech stack; in other situations, the CDP might replace an existing predictive modeling or analytical tool.  What the CDP won’t replace is your CRM, marketing automation, Web CMS, or Data Management Platform (DMP) system: those perform functions that are not built into a typical B2B CDP. Instead, the CDP will integrate with those systems, both to gather data from them and to share the profiles it creates. Some CDPs can go further and use predictive analytics to suggest the best message to deliver in real time or batch. You may or may not be interested in that capability.

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