Customer Data Platform (CDP) is an AI-driven, enterprise-grade CDP with real-time capabilities and scalability. It seamlessly connects all domain data, precisely unifies profiles through OneID technology, transforms fragmented data into actionable customer insights, and provides an intelligent data foundation for future-oriented enterprise applications.
Main Features
Data Assets
The system builds a precise 360° profile for each customer based on customer attributes, customer journeys, customer labels, and audience membership. It also supports visualizing statistics on overall customer assets and core applications within the current system through rich graphical representations, helping business personnel clearly and intuitively understand the global status of data assets.
Audience Insights
Based on customer entities, the system describes the distribution of customer groups with different features across multiple dimensions, such as customer attribute dimensions, customer label dimensions, and customer behavior dimensions. Leveraging the Tencent data ecosystem, the system calculates and mines multi-dimensional audience label content for specific customer groups, including demographic attributes, geographic distribution, and application preferences. It then presents the analysis results through intuitive charts to visualize group profile features and support business decision-making.
Segment Targeting
Segment customers across multiple dimensions by using attributes, behavioral events, labels, and other dimensions as combined conditions. Customize AND/OR logic to perform refined customer circling, segmentation, and packaging, enabling marketing campaigns to precisely reach the right customer groups. Use audience packages to execute a series of subsequent refined operational actions.
Label Creation
The label engine supports 10+ label creation methods, such as preference labels, computed labels, RFM labels, and SQL labels, enabling rapid construction of customer and entity label systems.
Metadata Management
The system centrally manages metadata for customers, customer behavior logs, and core business entities under the enterprise (such as orders, products, and stores), and supports extending custom entities (such as vouchers and campaigns).
OneID Integration
A unified OneID data processing service that identifies and associates the same customer across different platforms and applications, enriches customer profiles, accumulates full-lifecycle customer data assets, and breaks down enterprise data silos.
Data Access
The multi-platform data collection SDKs for Android, iOS, mini programs, and Web collect and apply data legally and compliantly based on customer authorization.
Strengths
Domain-Wide Data Integration and OneID
Collect multi-platform data in real time, identify and associate the same user through OneID technology, break down enterprise data silos, and accumulate high-quality data assets.
Smart Labeling and 360° Profiles
Build a highly flexible label system and generate 360° customer profiles that include attributes, behaviors, and preferences, providing precise support for personalized marketing.
AI Insights and Smart Segmentation
Integrate business models (such as RFM/AIPL) with AI algorithms to support low-barrier audience package generation through natural language, and predict user value and churn risk.
Use Cases
Data-Driven Precision Marketing
Identify high-potential customers based on precise label profiles, concentrate marketing resources on audiences most likely to convert, significantly improve conversion rates, and reduce customer acquisition costs.
Fine-Grained Operations Throughout the Lifecycle
Build complete profiles based on rich multi-dimensional data, and accurately identify and classify customers at each stage of the customer lifecycle. Use this as a data foundation to seamlessly support automated marketing, improve retention through precise interactions, and maximize customer lifetime value.
Omnichannel Correlation of People, Products, and Places
It not only manages customer data but also associates entities such as products and stores. By analyzing the interactions between consumers, products, and channels, it optimizes product-customer matching efficiency and offline store performance.