Unified Entity Segment Activation in Multi-Tenant Systems
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Solution Overview
Problem
Existing cloud platform systems face inefficiencies in segmenting and distributing content to related entities, as they require resource-intensive processing to create separate segments for each entity type, leading to increased overhead and reduced flexibility in content distribution.
Innovation Solution
The system utilizes predefined relationships within a data model to identify and extend segments of related entities, allowing for efficient content distribution by leveraging these relationships rather than generating multiple segments, thereby reducing processing and memory overhead while enhancing flexibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate segments are created for each entity type, then content distribution can be performed, but processing overhead and memory usage increase significantly
Solution Approach 1:
The patent merges multiple entity segments into a unified segment structure where related entities are grouped together through relationship definitions. Instead of maintaining separate segments for each entity type (customer segments, account segments, contact segments), the system creates a single segment that can include entities from multiple types by leveraging predefined relationships in the data model, thereby reducing processing overhead while maintaining distribution flexibility
Solution Approach 2:
The patent implements a universal segment structure that can serve multiple entity types simultaneously. The segment definition is not tied to a specific entity type but can include entities from different types (customers, accounts, contacts) through relationship-based inclusion. This multi-functional segment approach eliminates the need for separate segment creation for each entity type, reducing complexity while preserving adaptability
2Adaptability or versatility
If multiple segments are generated for related entities, then comprehensive content targeting is achieved, but memory overhead increases
Solution Approach 1:
The patent combines multiple entity segments into a single unified segment structure. Instead of creating separate segments for customers, accounts, and contacts, the system creates one segment that can include entities from all these types by leveraging relationship definitions in the data model. This merging approach maintains comprehensive content targeting capability while significantly reducing the memory overhead associated with managing multiple separate segments
Solution Approach 2:
The patent implements a nested segment structure where related entities are nested within a parent segment through relationship definitions. The segment hierarchy allows parent entities to contain child entities from different types, creating a nested organization that reduces memory overhead by avoiding duplicate entity listings across multiple segments while preserving comprehensive targeting capability
3Manufacturing precision
If resource-intensive processing is used to create segments, then accurate entity segmentation is achieved, but processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary action by pre-defining relationships between entity types in the data model before segment creation. The relationship definitions (parent-child relationships, associated entities) are established in advance, allowing the segment generation process to simply query these pre-defined relationships rather than computing entity relationships from scratch. This preliminary setup maintains accurate entity segmentation while significantly improving content distribution efficiency by reducing computational overhead
Solution Approach 2:
The patent implements self-service by allowing the data model's predefined relationships to automatically determine segment membership without requiring complex processing. The relationships between entities (customers, accounts, contacts) are self-descriptive in the data model, enabling the system to automatically generate accurate segments by simply following these pre-established relationships, thereby maintaining segmentation accuracy while improving distribution efficiency
Data Source
AI summary
A method for data processing includes identifying, for communication of a content object, a segment of entities including entities of a first entity class of a plurality of entity classes defined by a data model that is configured for a tenant of a multi-tenant system, where the data model defines relationships between entity classes of the plurality of entity classes. The method may further include activating for selection at a user interface at least one second entity class that is related to the first entity class based on the relationships and identifying a set of additional entities of the second entity class from the remaining entities that are related to the segment of entities as defined by the data model. The method may include transmitting to a content communication system an indication of the plurality of entity identifiers corresponding to a modified segment of entities that includes the additional entities.