DMP use cases are mainly ads-oriented and cookie-based. CDP use cases range across:
- CRM based customer experience
- Communication that is based on PII (Personally identifiable data)
- Customer analytics
In the past, Marketing Service Providers (MSPs) built customer or marketing databases which fulfilled a similar role but only included profile and transaction data. With the evolution of digital marketing, MSPs' highly customized approach and scaled-up database models have become too expensive and clunky when the size of data is at web-scale, and SaaS marketing clouds require modern API integration of customer data.
CDPs have three main pieces of functionality:
- Single view of the customer: integration; cleanse, standardize, dedupe, household etc. customer data in one place across both online and offline sources (POS, Call center, Web, Email etc.), to create a complete single view of the customer. This includes profiles to be connected in real-time to transactions and to events (web, IoT, email, calls etc.).
- Customer analytics and Machine learning: the scale and granularity of atomic level data is important, but marketers need intelligent data. For example, CDPs include LTV calculation of customer based on various metrics. Predictive analytics are also important to recognize patterns in the data and reduce the complexity and noise in the data to amplify the intelligence for marketers.
- Connectivity to customer interaction systems: CDPs either through batch or real-time APIs serve as the intelligent customer data backbone to ensure a customer web browsing event, or a store return or a call center complaint is available for changing customer experience and communication.