Dimensional Path Conversion for Advertising Reporting
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Solution Overview
Problem
Existing advertising management systems face challenges in processing large volumes of user interaction data to provide accurate and reliable performance measures, particularly due to issues like cookie deletion and partial conversion paths, which can lead to biased reporting and incomplete analysis of conversion cycles.
Innovation Solution
The system receives and aggregates conversion paths with dimensional data, prioritizes dimensions to select relevant data, and converts these paths into dimensional paths for reporting, allowing for a more comprehensive analysis of user interactions and conversion cycles by generating reports based on aggregated dimensional data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all available user interaction data is collected and processed to generate performance measures, then the completeness of performance reporting is improved, but the accuracy and reliability of performance measures deteriorate due to biased and incomplete data from cookie deletion and partial conversion paths
Solution Approach 1:
The patent segments conversion paths into dimensional paths by breaking down user interactions into discrete dimensional elements (source, medium, campaign, keyword, etc.). This segmentation allows the system to process and analyze partial conversion paths independently, reconstructing complete performance pictures even when cookie data is incomplete or deleted.
Solution Approach 2:
The patent introduces dimensional paths as an intermediary representation between raw conversion path data and final performance reports. This intermediary layer aggregates data across multiple dimensions and sources, allowing the system to compensate for missing cookie data by inferring conversion information from alternative dimensional elements and aggregated patterns.
2Loss of information
If dimensional data from multiple sources is aggregated to provide comprehensive performance measures, then the completeness of analysis is improved, but the complexity of data processing increases
Solution Approach 1:
The patent creates a universal dimensional path structure that can represent multiple types of user interactions and conversion data through a common framework. This multi-functional representation allows the same data processing pipeline to handle diverse data sources (cookies, server logs, third-party data) without requiring separate complex processing logic for each source.
Solution Approach 2:
The patent transforms raw conversion path data into dimensional paths by changing the parameters of representation from user-action sequences to dimensional element sequences. This parameter transformation simplifies the data structure and enables efficient aggregation operations across large volumes of conversion data from multiple sources.
3Reliability
If conversion paths are tracked using traditional methods to maintain accuracy, then the reliability of conversion tracking is improved, but the ability to handle cookie deletion and partial paths deteriorates
Solution Approach 1:
The patent implements a dynamic conversion path tracking system where dimensional paths can be continuously updated and reconstructed from available data. Instead of relying on static cookie-based tracking, the system dynamically aggregates dimensional elements from multiple sources and time periods, adapting to cookie deletion and partial conversion paths by reconstructing the most likely conversion journey based on available dimensional evidence.
Data Source
AI summary
Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, for providing data related to conversion paths. In one aspect, a plurality of conversion paths are received. Each conversion path includes one or more user interactions that include a plurality of dimensional data. A priority sorted list of dimensions is received and dimensional data is selected from each user interaction based on the sort list of dimensions. Each conversion path is converted into a dimensional path, and each dimensional path includes dimensional elements that corresponds to user interactions of the conversion path. Each dimensional element comprises the selected dimensional data from the corresponding user interaction. The plurality of dimensional paths are aggregated together based upon the number of dimensional elements within each dimensional path and the dimensional data of the dimensional elements. Reports can be generated using the aggregated dimensional data.