Communication Engine for Granular Content Distribution and Tracking
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Solution Overview
Problem
Cloud platforms lack the capability to effectively distribute content to targeted user groups for meaningful interaction tracking, as they do not have a robust collection of user data for categorization and automatic distribution of content variations across different user categories.
Innovation Solution
A communication engine that identifies and distributes content to specific user groups based on target group identifiers, allowing for simultaneous ABn and multivariate testing across various user categories, enabling high-granularity feedback tracking and engagement metrics generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cloud platforms use multi-tenant database systems to store and manage user data, then data storage efficiency and resource utilization are improved, but the capability to track user interactions with different content versions across user categories deteriorates
Solution Approach 1:
The system segments user data into distinct user categories and segments content into different versions. By creating separate tracking mechanisms for each user category-content version combination, the system maintains detailed interaction data without compromising storage efficiency. The multi-tenant database stores segmented user category identifiers and content version identifiers that enable granular tracking while sharing underlying storage infrastructure.
Solution Approach 2:
The system introduces intermediary tracking tables that mediate between the multi-tenant database storage structure and the user interaction tracking requirements. These intermediary structures contain user category identifiers, content version identifiers, and interaction data, enabling the platform to track interactions across different user categories and content versions while maintaining the efficiency of the multi-tenant database architecture.
2Speed
If cloud platforms distribute content to users without robust user categorization, then distribution speed is improved, but the precision of engagement tracking across different user categories deteriorates
Solution Approach 1:
The system performs preliminary user categorization by assigning user category identifiers to users in advance, before content distribution occurs. Content versions are also pre-tagged with target user category identifiers. When distribution occurs, the system quickly matches user identifiers with pre-categorized groups and distributes appropriate content versions, achieving both high speed and precise tracking capability.
3Reliability
If cloud platforms require content creators, managers, and developers to work together to create trackable digital communications, then content tracking capability is improved, but system complexity and operational overhead increase
Solution Approach 1:
The system provides universal content tracking functionality that works across all user categories and content types through a unified mechanism. The same tracking infrastructure handles emails, notifications, advertisements, and web pages uniformly. Content creators can specify target user categories and content versions using standardized identifiers, and the system automatically handles the tracking without requiring different processes for different content types or user groups.
Data Source
AI summary
A communication server supports automatic content receipt and distribution. The communication server receives a set of content objects, where a content object of the set is associated with a set of target group identifiers. A content object of the set may include different versions of content for ABn and/or multivariate testing. The communication server generates target segment identifier combinations and distributes versions of messages proportionally to each user identifier associated with the target segment combinations. The server generates engagement metrics corresponding to interaction by the user identifiers with the messages. The metrics may be generated for each message version, each group of users, and each group combination.