Conversion Measurement Diagnostics via Unified Signal Pipeline
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems struggle with generating reliable, standardized conversion measurement diagnostics across multiple applications due to separate processing of feature data, leading to redundancy, inconsistency, and difficulty in tracking data age and implementing updates, making it challenging to manage diagnostic signals effectively.
Innovation Solution
A system that processes feature data from multiple sources through a single pipeline, storing diagnostic signals with timestamps in a common data layer, and providing a unified user interface for applications, allowing for standardized and reliable diagnostic signal generation and management across applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate pipelines are used to process feature data for each application, then each application can have customized diagnostic processing, but diagnostic signals are redundantly computed and difficult to share between applications
Solution Approach 1:
The patent merges multiple separate diagnostic pipelines into a single unified pipeline that processes feature data once and generates diagnostic signals that can be shared across multiple applications. The system consolidates the processing of offline conversion data, tag-based conversion data, and consent choice data into one centralized pipeline, eliminating redundant computation while maintaining the ability to serve different applications with customized diagnostic needs through a common data layer.
2Ease of manufacture
If separate pipelines are used for each application, then each application can be independently maintained, but updates must be separately implemented in each pipeline
Solution Approach 1:
The unified pipeline is designed with multi-functionality to serve multiple applications simultaneously. By creating a single pipeline that can generate diagnostic signals for various applications through a common data layer, the system allows updates to be implemented in one location rather than separately in multiple pipelines. The universal pipeline structure maintains independence for each application's diagnostic needs while centralizing the processing logic for easier maintenance and updates.
3Speed
If feature data is pushed ad hoc from features, then data can be collected in real-time, but it is difficult to track the age of the data
Solution Approach 1:
The system implements preliminary action by assigning timestamps to feature data at the point of collection in the unified pipeline. By pre-tagging data with timestamp information during the initial processing stage, the system enables easy tracking of data age throughout the diagnostic signal generation process. This preliminary timestamping action occurs before data is distributed to various applications, ensuring that data freshness information is preserved and accessible without requiring additional tracking mechanisms.
4Adaptability or versatility
If multiple separate pipelines are used, then each application can have dedicated processing, but diagnostic signals are generated in different data formats and not easily shareable
Solution Approach 1:
The unified pipeline implements homogeneity by generating all diagnostic signals in a standardized data format within a common data layer. This standardized structure allows diagnostic signals from different feature types (offline conversion, tag-based conversion, consent choice) to be consistently formatted and easily shared across multiple applications. The homogeneous data format eliminates the need for separate format handling that would be required with multiple pipelines, while still allowing each application to access and process the data according to its specific needs.
Data Source
AI summary
A method for generating conversion measurement diagnostics for different content applications based on feature data from multiple features includes requesting the feature data associated with a particular account at a configured interval, processing the received feature data to generate diagnostic signals according to predetermined logic for each of a plurality of available diagnostics for a plurality of applications, then storing the diagnostic signals with timestamps within a common data layer. When a diagnostic status request associated with the particular account is received via a first application, first diagnostic signals are retrieved from the common data layer, where each of the first diagnostic signals is associated with first diagnostics enabled for the first application. Then, a user interface for the first application is provided to display a separate interface element for each of the first diagnostics, each interface element indicating corresponding ones of the first diagnostic signals.