CDPs Can Disrupt The B2B Space – Here’s How

Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Craig Howard, chief solution architect for Merkle B2B.

The customer data platform (CDP) market for B2B organizations has lagged behind the B2C space to date. But, at last, it’s starting to take shape. Going into 2022, we’re going to see a lot of B2B marketers contemplating whether – and how – a CDP might fit into their tech stack. Therein lies the potential for significant disruption.

As CDPs infiltrate the B2B world, they’re going to create a good deal of confusion regarding existing marketing automation platform (MAP) and account-based marketing (ABM) platform implementations. To be successful, CDPs will have to displace these platforms as B2B organizations’ top marketing technology priority. They’ll also need to absorb most, if not all, of their capabilities. That’s no small task, and it won’t happen overnight.

CDPs in the B2B space have the opportunity to avoid many of the pitfalls that their B2C counterparts encountered, many of which sparked confusion and buyer’s remorse by disrupting but not fully replacing other platforms. What are the essential requirements for a CDP if B2Bs want to achieve true sustainable disruption?

Let’s take a look.

Business-to-human (B2H) technology

To be successful, B2B CDPs need to be truly people-based systems designed to spark meaningful conversations with real people. And by people, we mean all the people of interest to a B2B organization: customers (contacts), prospects (leads) and pretty much anyone who might someday become a customer (suspects). 

Another B2H requirement is the ability to create a holistic view of a person’s interactions with an organization. That includes not only its marketing efforts, but also its sales and service functions – essentially, anytime customers and prospects are interacting with humans within the organization.

Data flexibility

When it comes to identity, there are a number of complexities that a successful B2B CDP will need to support. For one, it has to provide the flexibility to create custom relationships and hierarchies in your data. It might be a geographic view, a view that replicates account structure or a group of contacts that represent a decision-making unit. A good CDP enables organizations to use data that makes the most sense for their efforts at a contact, account or buying-group level. 

Going further with identity, CDPs need to support both anonymous and known profiles. This can be accomplished through the common ABM capability of reverse IP lookups for account associations. They should also allow organizations to configure their identity graph, and the number of signals that feed it, to support multiple use cases – marketing, sales, service and beyond. 

Comprehensive data unification and orchestration

B2H systems and identity tools layer up to an overarching goal: data unification. And to get data unification right, a CDP will need to solve for data quality by cleansing dirty first-party data and maintaining that cleanliness.

Being third-party data friendly is another key characteristic of B2B CDPs. They may provide their own proprietary data, enable usage through established partnerships, include pre-built integrations, as well as support brands that want to bring in their own data, such as industry-specific data assets.

CDPs must also support integrating engagement data from all touch points, since it represents first-party intent and offers organizations a rich approach to scoring engagement at multiple levels (i.e., by campaign, business unit, solution, contact, account, etc.). 

A strong B2B CDP will also need to permit organizations to distribute insights for use in analytics and data activation and, most importantly, sales tech environments. 

Unique, granular targeting 

Finally, CDPs need to support organizations as they put their data and insights into action for targeting, both by deriving initial lists of target accounts and then through look-alike modeling based on high-value customer accounts. Companies need to be able to define audiences at the contact and account level, as well as merge those audiences at different entity levels. In addition, the CDP must enable the aggregation of behavior at multiple levels – such as contact, account and buying groups.

Multichannel orchestration is also essential. A successful B2B CDP will enable all channel-specific platforms and allow companies to distribute their audiences and profiles where they need to go.

A combination of all of the above is a formidable ask from a CDP. But that’s what it’s going to take for true disruption of the B2B data landscape. After all, B2B companies don’t need more complexity and systems. They need simplicity based on the right systems. 

Follow Craig Howard (@CHowardMerkle) and AdExchanger (@adexchanger) on Twitter.

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