Web Spike Attribution via Cookie-Optional TV Ad Correlation
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Solution Overview
Problem
Television advertising lacks effective methods for measuring user interactions and conversions due to the absence of tracking mechanisms like cookies, leading to irrelevant and poorly targeted ads.
Innovation Solution
A system and method for web spike attribution that aligns web activity with television viewing events, using algorithms to measure delta web responses without requiring training or parametric assumptions, enabling conversion tracking and targeted advertising.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cookies or IP addresses are used to track user interactions, then conversion tracking is enabled, but television advertising cannot be measured due to lack of tracking mechanisms
Solution Approach 1:
The patent introduces an intermediary approach by using web activity data as a mediator to indirectly measure television advertising effectiveness. Instead of directly tracking TV viewers, the system correlates web activity spikes with TV ad airings, using the web activity as a proxy indicator for ad impact.
Solution Approach 2:
The patent replaces the mechanical cookie-tracking system with a statistical correlation approach. Instead of relying on client-side tracking mechanisms like cookies that don't work for TV, the system uses server-side web activity analysis to infer TV ad effectiveness through pattern recognition and delta response measurement.
2Loss of information
If traditional web tracking methods are applied to television, then user behavior can be measured, but the system complexity increases due to heterogeneous data sources
Solution Approach 1:
The patent extracts only the essential elements needed for measurement: web activity timestamps and TV airing schedules. By focusing on these key data points and ignoring extraneous information, the system reduces complexity while maintaining measurement capability.
Solution Approach 2:
The patent transforms heterogeneous data from different sources into a unified parameter space by converting all data into timestamp-based events. This parameter standardization allows diverse data sources (web logs, TV schedules, ad catalogs) to be integrated through temporal correlation rather than complex data structure merging.
3Productivity
If web activity data is analyzed in real-time, then ad optimization is improved, but processing requirements increase
Solution Approach 1:
The patent applies partial action by analyzing only specific time windows around TV ad airings rather than continuous real-time processing. By focusing computational resources on pre-defined attribution windows (e.g., 30 minutes before and after ad airing), the system achieves timely optimization without sustained high computational load.
Solution Approach 2:
The patent performs preliminary actions by pre-processing and indexing web activity data before ad attribution is needed. Web activity timestamps are collected and organized in advance, allowing rapid query and correlation when ad airings occur, thus reducing real-time processing requirements.
Data Source
AI summary
Systems and methods are disclosed that measure web activity bursts after ad broadcasts that may be sent to multiple persons. One system uses a cookie-less/cookie-optional, anonymous/personal-identification-not-required, method for web-based conversion tracking that will work on broadcast media systems such as television, and could also be applied to measuring spikes from email, radio, and other forms of advertising where an episodic ad event is broadcast to multiple parties, and where responses occur in a batch after the broadcast.