How many customer data platform technologies are in your customer data program?
“Customer data platform” has been a very confusing term all along. The CDP acronym would best be taken over by “customer data program” for the organization, with “CDPT” for the technologies utilized to build the program.
Competencies: CDPC are parallel to CDPTC
Whether we call it this or not, the aim in setting up a customer data program is truly to initiate a Customer Data Program COE (Center of Excellence)
This CDP CoE is not a standalone group, but consists of delegated customer-data-concerned parties across the organization. Compliance, engineers, product managers, marketing — everyone.
This CoE includes the individuals who are tasked with aligning on and managing the seven major competency areas as they apply to the internal and external utilization of customer data:
- Data management
- Event data collection
- Identity resolution
- Customer analytics
- Customer profiling
- Customer segmentation
- Orchestrated customer data activation
These individuals would also make decisions on the CDPT, or “customer data platform technologies” to help make these things happen. With this definition in place, any technology that has mastery over at least one of the seven major competencies should qualify as CDPT.
It’s no wonder the CDP space went wild. There ARE technologies out there that DO help across all of these categories to a degree. The catch is that they do not all have what most would consider “mastery” across more than a few areas, even though they have been described as such.
Data management
Separate from the collection of event data, and the resolution of identity — there is data management. Bringing non-event data in, combining data in various ways, archiving/change logging, and other features.
Event data collection
SDKs and tools to collect real-time event data from applications and systems where customers engage or where brand experiences are delivered.
Identity resolution
Configurable methods of joining datasets based on personal identifiers and/or additional attributes to allow resolution of individuals, households, or accounts.
Customer analytics
Advanced analytics and modeling against historic and real-time customer data.
Customer profiling
Abilities to reprofile customers and/or understand audience composition with multiple resolution schemes.
Customer segmentation
Specific application of modeling that operates at the audience/segment level and may include reference datasets as part of the models (e.g. non-customers).
Orchestrated customer data activation
Advanced capabilities in event and batch customer data orchestration.
Would love to hear if this is something that rings true, especially if you’ve faced limitations from a CDP technology after thinking that it did have mastery over an area that it truly did not.
Reach out here or on the LinkedIn!
