Clickstream Data Extraction for Hidden Organic Search Keywords
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Solution Overview
Problem
Commercial off-the-shelf (COTS) web analytics platforms require website owners to install software and create accounts to receive data directly, limiting their ability to analyze clickstream data comprehensively, especially for organic search keywords and e-commerce events, which are often hidden as 'not provided' metrics.
Innovation Solution
A process is developed to retrieve clickstream data from panelists' browsers, analyze it for page views, action events, and e-commerce activities, and convert 'not provided' organic search data into usable metrics by examining user histories and resource streams, allowing for the creation of payloads that can be forwarded to analytics platforms for deeper analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If COTS web analytics platforms receive data directly from websites through installed software, then they can provide comprehensive web analytics capabilities, but they cannot access hidden data such as organic search keywords and e-commerce events that are marked as 'not provided'
Solution Approach 1:
The system performs preliminary actions by collecting and storing complete clickstream data including organic search keywords and e-commerce events before they are processed or anonymized. By capturing the raw data first and maintaining it in an accessible format, the system enables later retrieval and analysis of information that would otherwise be lost or marked as 'not provided' by COTS platforms.
Solution Approach 2:
The patent introduces an intermediary data processing layer between the clickstream data source and the COTS web analytics platform. This intermediary system parses clickstream data, extracts hidden information such as organic search keywords and e-commerce events, and transforms it into a format compatible with COTS platforms while preserving the original data's analytical value.
2Adaptability or versatility
If COTS web analytics platforms require direct website integration through installed software, then they can provide deep analysis capabilities, but they lack the ability to analyze clickstream data from external sources comprehensively
Solution Approach 1:
The system is designed with multi-functionality to handle multiple data sources and formats. It can process clickstream data from various external sources, parse different data structures, and extract relevant analytics information regardless of the original source format, thereby providing versatile data collection while maintaining analytical precision.
Solution Approach 2:
The patent employs parameter changes by transforming external clickstream data into the standardized format required by COTS web analytics platforms. Through data parsing, normalization, and parameter mapping, the system adapts diverse external data sources to match the expected input parameters of analytics platforms, enabling comprehensive analysis without direct website integration.
3Ease of operation
If external tools use clickstream data to provide high-level web analytics, then they can offer analytics without website integration, but they lack the depth and functionality of COTS web analytics platforms
Solution Approach 1:
The system extracts specific valuable information from clickstream data such as organic search keywords, e-commerce events, and conversion metrics. By selectively extracting and isolating these key data elements from the broader clickstream dataset, the system provides detailed conversion metrics and analytical depth that were previously unavailable in external clickstream analysis tools.
Data Source
AI summary
The present invention relates generally to a novel and improved method of loading clickstream data into a web analytics platform, and, a commercial off the shelf (COTS) web analytics platform. The process of loading traffic into COTS Web Analytics platform from clickstream data relates to: (1) the process of discovering ecommerce sales by looking for specific tracking beacons in clickstream or resource stream and loading them into a COTS web analytics platform; (2) a process of discovering website “goals” by looking for clusters of tracking “beacon” activity in clickstream or resource stream data; and (3) a process of unlocking the search term that a website visitor typed into a search engine immediately prior to visiting that website when web analytics platforms can't see that data for many searches (99%+) having all of the features described above.