Social Network Conversation Objects for Multi-Tenant Support Databases
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Solution Overview
Problem
Existing multi-tenant database systems (MTS) lack efficient methods to integrate and manage information from social networks like Twitter and Yammer, limiting customer support representatives' ability to utilize this valuable data for enhanced productivity.
Innovation Solution
A system and method for integrating social network information into MTS by retrieving, processing, and storing social media messages as conversation objects, enabling filtering, searching, and taking actions based on this data, using templates, and storing it in a knowledge base.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If social network information is integrated into multi-tenant database systems, then customer support productivity is enhanced, but system complexity increases
Solution Approach 1:
The patent introduces conversation objects as intermediary entities that bridge social network information and the multi-tenant database system. These conversation objects serve as a standardized interface layer, allowing social media messages to be processed and stored without directly complicating the core database architecture. The conversation objects act as mediators that translate diverse social network data into a unified format suitable for customer support operations.
Solution Approach 2:
The integration system is segmented into distinct functional components: information retrieval modules that harvest social network data, processing modules that transform the data into conversation objects, and storage modules that integrate these objects into the database. This segmentation allows each component to be developed and maintained independently, reducing overall system complexity while enabling productivity enhancements.
2Loss of information
If multiple information sources from social networks are retrieved and processed, then data utility for customer support increases, but information processing complexity increases
Solution Approach 1:
The patent applies homogeneity by transforming diverse social network information from multiple sources into a unified conversation object structure. All incoming social media messages, regardless of their original format or source, are standardized into consistent conversation objects with uniform attributes. This homogenization preserves the utility of information from multiple sources while simplifying processing by eliminating the need to handle each source differently.
3Ease of operation
If social network messages are stored as conversation objects in the database, then accessibility and manageability improve, but storage and retrieval overhead increases
Solution Approach 1:
The patent creates conversation objects as standardized copies or representations of social network messages. Instead of storing raw social media data in its original complex format, the system creates simplified copy structures (conversation objects) that contain only the essential information needed for customer support. This copying approach improves accessibility and manageability while reducing storage overhead by eliminating redundant or unnecessary data elements.
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.