As we continue into 2022, we’re going to see many B2B marketers contemplating whether, and how best, a customer data platform (CDP) might fit into their tech stack. As CDPs infiltrate the B2B world, they will likely create confusion regarding what capabilities they can take over from existing marketing automation platforms (MAPs) and account-based marketing (ABM) platforms. There lies the potential for significant disruption. So, what are the essential requirements for B2B CDPs if they want to achieve true sustainable disruption?
By understanding individual engagements, organizations can better gauge interest from buyers by either incorporating that data within the account or speaking to a prospect directly through individualized audience segmentation as opposed to holistic account segmentation. For example, if a manager is looking at your solution, but the senior director is the VP, you can market to both based on the manager’s activity since they are both under the same account. Further, CDPs can support better attribution models through accurate time-stamped events. Model next best actions or product recommendations based on this full picture of account engagements. These recommendations should be fed to a sales engine/system to ensure that your teams are fully informed on important information through the sales journey. For example, this could allow your call center team to receive in-line recommendations for relevant offers during their conversations. CDPs can help better align sales and marketing teams’ efforts by understanding how the CDP can be used to predict “hot” prospects and feed that to your sales tools.
Simply adopting a CDP will not magically solve your organization’s challenges, nor will your organization become more customer centric overnight. To drive value and ROI from this investment, your entire organization structure and mindset will need to evolve too. By aligning teams around your desired use cases and goals as opposed to specific channels or department-level outcomes, you will be able to incorporate the CDP into your organization to gain return on investment faster. This will also allow the CDP to not just be your hub for data and audience building but for customer experience collaboration across teams in one central place.
A successful B2B CDP needs to support identity. B2B organizations sometimes have complex identity matching rules and logic needs and therefore, they may have already created robust business rules and processes around creating contacts and accounts internally. Therefore, the CDP shouldn’t look to replace all identity resolution functionality, but rather enhance the components, like streaming digital IDs, supplementary probabilistic matching capabilities, and real-time third-party data appends.
Further, CDPs must support both anonymous and known profiles through the common ABM (account-based-marketing) 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—across marketing, sales, service, and beyond.
Over time, successful B2B CDPs will become the central hub for organizations’ audiences. But MAPs, ABM platforms, and others won’t go away overnight. So, CDPs must play nicely with other ecosystems. That includes, but isn’t limited to:
A big part of this is supporting data ingestion from other environments, but it can’t be just a one-way setup. A strong B2B CDP will also need to permit organizations to export insights for use in analytics and data activation.
The overarching goal: data unification. To get data unification right, a CDP will need to solve for data quality by cleansing dirty first-party data and maintaining that cleanliness as the following additional types of data are brought in:
A B2B CDP must be third-party data friendly, by whatever approach is needed. They may provide their own proprietary data, enable usage through established partnerships, include pre-built integrations, or support brands who want to bring their own data.