Social Network Conversation Objects for Multi-Tenant Support
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Solution Overview
Problem
Existing multi-tenant database systems (MTS) lack the ability to efficiently integrate and manage information from social networks like Twitter, Facebook, and Yammer, limiting their utility in customer support and knowledge management.
Innovation Solution
A system and method for integrating social network messages into MTS by retrieving, processing, and storing them as conversation objects, enabling customer support representatives to manage social networks like any other support channel, using templates to characterize and store harvested information in a knowledge base.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If social network information is integrated into multi-tenant database systems, then customer support capability and information management are improved, but system complexity and integration difficulty increase
Solution Approach 1:
The patent introduces a social network integration module as an intermediary component that bridges social network platforms and the multi-tenant database system. This module handles message retrieval, parsing, and conversion to standardized conversation objects, isolating the complexity of social network protocols from the core database system while enabling versatile customer support capabilities across multiple social platforms
Solution Approach 2:
The integration system is divided into distinct functional segments: message retrieval components for different social networks, message parsing and processing modules, conversation object generation, and knowledge base integration. Each segment handles specific tasks independently, reducing overall system complexity while maintaining comprehensive social network support
2Productivity
If multiple agents access and process social network information, then productivity and response efficiency are improved, but data management complexity and coordination overhead increase
Solution Approach 1:
The conversation object structure and knowledge base are designed as universal interfaces that multiple customer support agents can access simultaneously. The system provides a unified view of social network messages that works across different agent workstations and platforms, enabling consistent data management and coordinated responses without requiring agent-specific configurations or protocols
3Loss of information
If social network messages are stored as conversation objects in the database, then information organization and searchability are improved, but data storage requirements and processing overhead increase
Solution Approach 1:
The system creates structured conversation objects that copy and organize essential information from unstructured social network messages. These conversation objects store only the necessary extracted data (message content, metadata, conversation context) in a standardized format, reducing storage requirements compared to storing complete raw messages while maintaining full searchability and organizational capabilities
Data Source
AI summary
Some embodiments comprise integrating information from a social network into a multi-tenant database system. A plurality of information from the social network is retrieved, using a processor and a network interface of a server computer in the multi-tenant database system, wherein the plurality of information is associated with a message transmitted using the social network. Metadata related to the transmitted message is generated, using the processor. A conversation object is generated, using the processor, based on the plurality of information associated with the transmitted message and the metadata related to the transmitted message. The conversation object is then stored in an entity in the multi-tenant database system, using the processor of the server computer.