The ninth and final scenario or business use case for Customer Data Platform (CDP) technology is Advanced Customer Data Management. (The other scenarios are described here: Scenario 1, Scenario 2, Scenario 3. Scenario 4, Scenario 5, Scenario 6, Scenario 7 and Scenario 8.)
At some level, all CDP tools provide a kind of Master Data Management (MDM), since the foundation of any of any CDP is to “master” customer records. They do this by disambiguating customer and prospect data to create an authoritative “golden” record for each one.
Then to varying degrees a CDP aggregates and persists core data for each customer, independent of any channel or application – i.e., authoritative data that can be applied across whatever platform is consuming these records. So almost any CDP will provide common MDM services like ETL, deduping and reconciliation, and some level of data cleaning.
What are the Advanced Capabilities?
Some CDP vendors, though, target more complex customer / prospect data environments. They differentiate less on marketing activation and more on creating advanced data stores that marketers can then leverage in arbitrary ways. Customers need this scenario when they…
- Anticipate having multiple different datasets (e.g., not just different segments), but all within a single platform
- Need to create a “virtual” data store (as opposed to a physical aggregate) via federation across multiple data repositories
- Have widely divergent data quality and cleanliness across different data sets or attributes and need custom handling for different types of records
- Want to support an unusually broad data model; you should never confuse a CDP with a data lake, but when the number of customer attributes you wish to persist start numbering into the hundreds, you need more advanced back-end and UX services to master them
- Are likely to experience unusual complexity and diverse challenges unifying records in general and reconciling identities in particular
- Need advanced, ongoing data integration and transformation capabilities to apply greater intelligence to the connectors you build, across varying source data formats (not just XML and SQL) and schedules
- Anticipate using the data for non-marketing use-cases
What do Vendors Offer?
Vendors who excel at this scenario put more effort into ingest, transformation, and enrichment services. These might include:
- Advanced identity resolution algorithms
- The ability to support multiple logical data stores and apply different rules to them
- Extensible and rich data models to support different scenarios
- Built-in connectors and capabilities for advanced data transformations
- Ability to plug-in external analytics and machine learning frameworks or algorithms in addition to built-in models
- Ability to carry out complex data management and schema changes on an ongoing basis using a graphical interface
RSG can help you with your analysis. If you are a subscriber, you can use our RealQuadrant Shortlist Generator to find out which CDP vendors excel at this scenario. Our rigorous evaluations also call out specific capabilities for this scenario for each vendor.