Deferred-Schema Analytics Payloads for Cross-Platform Event Consistency
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Solution Overview
Problem
Conventional approaches place the burden of sending client device event data on client devices, leading to inefficiencies such as duplicated logic, increased maintenance overhead, inconsistencies in event property values, and extended development time across multiple platforms.
Innovation Solution
A passthrough analytics payload system using deferred schemas, where the content management module of a server system generates and serializes payloads based on schemas, sending them to the client device for rendering, and the data platform deserializes them using the same schemas to determine user data, thereby decoupling client devices from backend domain models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If client devices gather and derive event data values, then client devices can send event data to server systems, but this results in duplicated logic across client platforms and increased maintenance overhead
Solution Approach 1:
The patent extracts the event data derivation logic from client devices and relocates it to the server system. The server system now receives raw event data from client devices and performs the derivation of event property values server-side, eliminating the need for duplicate derivation logic across multiple client platforms and reducing maintenance overhead.
Solution Approach 2:
The server system acts as an intermediary between client devices and the analytics processing system. Instead of client devices directly deriving and sending processed event data, the server system receives raw data, performs derivation using centralized logic, and then sends the processed event data to analytics systems, simplifying client device functionality.
2Reliability
If client devices derive event property values, then event data can be constructed, but this results in inconsistencies in how event property values are computed across client platforms
Solution Approach 1:
The server system implements a universal derivation logic that serves all client platforms. By centralizing the event property value derivation in the server system, the same logic is applied consistently across all platforms, ensuring reliability and consistency of event data regardless of the originating client platform.
3Adaptability or versatility
If schemas are extended for client event data, then analytics capabilities are enhanced, but this requires increased coordination and development time across multiple components
Solution Approach 1:
The patent extracts schema management from the client device layer and consolidates it at the server system layer. Schema extensions and modifications are now performed centrally in the server system, eliminating the need for coordinated updates across multiple client platforms and reducing development time while maintaining analytics flexibility.
Data Source
AI summary
Systems and methods are disclosed for a passthrough analytics payload system. One method comprises receiving a resource request from a user device, in response to receiving the resource request, retrieving and/or computing one or more analytics payloads, serializing the one or more analytics payloads based on one or more schemas, sending a resource response to the user device, wherein the resource response includes the one or more analytics payloads and one or more resources, receiving an analytics request from the user device, wherein the analytics request includes the one or more analytics payloads and specific user device analytics information, receiving the one or more schemas for the one or more analytics payloads, deserializing the one or more analytics payloads based on the one or more schemas to determine user analytics data, and storing the user analytics data in one or more data stores.