Context Server for Cross-Channel Interaction Data Integration
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Solution Overview
Problem
Existing multi-channel interaction systems often fail to provide a seamless user experience due to the lack of integration across different interaction channels, requiring users to repeat information and steps, and service providers struggle to identify relevant user history across channels.
Innovation Solution
A system and method for processing context data across multiple interaction sessions, using a context server to detect interaction sessions, obtain and select relevant context data from other sessions, and provide it for facilitating new interactions, thereby enhancing user experience and service efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple interaction channels are provided to increase coverage and convenience, then user accessibility is improved, but system complexity increases and integration becomes difficult
Solution Approach 1:
A context server is introduced as an intermediary component that sits between multiple interaction channels (web, mobile, telephone, social media) and user profiles. This server collects, stores, and manages context data from all channels, allowing each channel to access relevant user information without requiring direct integration between channels themselves, thus reducing overall system complexity while maintaining versatility.
Solution Approach 2:
The context server performs multiple functions: collecting context data from various channels, storing it in a centralized database, retrieving it for specific interaction sessions, and filtering relevant information. This multi-functional design consolidates what would otherwise require separate systems in each channel, reducing complexity while supporting multiple interaction modes.
2Ease of operation
If context data from multiple interaction sessions is collected to provide seamless experience, then user experience is improved, but data processing complexity increases
Solution Approach 1:
The system extracts only the necessary context data from multiple interaction sessions and stores it in a structured format in the context database. When a new interaction session starts, the system queries and retrieves only the relevant extracted data, avoiding the complexity of processing all historical data at once. This extraction approach simplifies data management while enabling personalized experiences.
Solution Approach 2:
Context data is collected and pre-processed in advance during interaction sessions, storing it in the context database before it is needed. This preliminary action allows the system to quickly retrieve and filter relevant information when a new session starts, rather than processing all historical data in real-time, thus reducing processing complexity while maintaining comprehensive user context.
3Loss of information
If all interaction session data is stored to enable comprehensive analysis, then information availability is improved, but data management burden increases
Solution Approach 1:
The context database stores context data with specific metadata tags indicating relevance to different interaction channels and session types. The system retrieves and processes only the locally relevant data for each specific interaction session rather than managing all historical data uniformly. This localized approach reduces data management burden while ensuring comprehensive information availability when needed.
Solution Approach 2:
The system collects and stores comprehensive context data from all interaction sessions (excessive action), but implements efficient filtering and retrieval mechanisms that access only the necessary partial data for each specific interaction session. This approach ensures information availability while managing data through structured organization and targeted queries, reducing the practical data management burden.
Data Source
AI summary
A method and system are provided for processing context data for interaction sessions. The method includes detecting a first interaction session using a first interaction channel between a request initiator and a request service provider and obtaining context data of a plurality of other interaction sessions between the request initiator and the request service provider. The context data is related to activity of the request initiator, and at least one of the plurality of other interaction sessions and the first interaction session use different types of interaction channels between the request initiator and the request service provider. The method also includes selecting a subset of the context data of the plurality of other interaction sessions that are related to the activity. The method also includes providing the subset of the context data for the first interaction session.