The Problem with Customer Data Platforms (CDPs)
The top 9 data problems that existing Customer Data Platforms (CDPs) don't actually solve for.
The top 9 data problems that existing Customer Data Platforms (CDPs) don't actually solve for:
Limited integrations with common CX data sources (CCaaS, Conversational AI, on-premise systems, WFM, etc.)
Lack of built-in analytics and reporting capabilities, requiring additional tools for data analysis and visualization.
Limited support for real-time data processing and streaming.
Limited ability to handle unstructured data, such as call transcripts and IVA interactions.
Lack of data governance and compliance features, which is critical in most environments.
Difficulty in providing a unified view of customer and operational data across multiple channels and sources.
Still requires other data management systems, such as data lakes or data warehouses.
Limited support for advanced data modeling to support machine learning, predictive analytics or AI applications.
Lack of user-friendly interfaces for non-technical users, which makes it difficult for managers or other business users to access and use the data.
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