Multivariate Experimentation via Hierarchical Temporal-Spatial Units
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Solution Overview
Problem
Current methods for measuring the effectiveness of content across various channels, such as digital signage, mobile devices, and IPTV, face challenges in tracking behavior and isolating individual channel impacts due to lack of direct interaction and confounding factors, leading to biased samples and limited cause-and-effect analysis.
Innovation Solution
The system employs Hierarchical Temporal-Spatial Units (HTSUs) to define experimental units based on spatial and temporal reach factors, allowing for the measurement of content effectiveness across multiple channels by assigning content to specific units and controlling confounds through randomization and content pooling, ensuring accurate data collection and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If token creation methods are used to capture content impact on behavior, then individual channel effects can be tracked, but sample size becomes small and biased due to opt-in requirements
Solution Approach 1:
The patent segments the measurement approach by creating distinct experimental units (geographic regions, time periods, content variants) that can be independently analyzed. This allows comprehensive data collection across multiple segments without requiring individual opt-in from each user, thereby maintaining large sample sizes while enabling precise measurement of content effectiveness at different levels.
Solution Approach 2:
The patent introduces geographic regions and time periods as intermediary units between content exposure and behavior measurement. These intermediaries aggregate individual behaviors into population-level data, eliminating the need for direct individual opt-in while preserving measurement precision through controlled experimental design at the intermediary level.
2Quantity of substance
If data mining is used to analyze content impact, then large volumes of data can be processed, but only correlation studies are possible without active cause-and-effect experimentation
Solution Approach 1:
The patent applies preliminary action by pre-defining experimental units, treatment groups, and control groups before data collection begins. This structured approach transforms raw data into experimentally valid observations that can establish cause-and-effect relationships, moving beyond mere correlation while maintaining the ability to process large volumes of data.
Solution Approach 2:
The patent introduces dynamic experimental design where content assignments and measurements are actively controlled and adjusted during the study period. This dynamic approach enables causal inference by actively manipulating content exposure while collecting large volumes of behavioral data, bridging the gap between data mining capacity and experimental rigor.
3Measurement precision
If additional behavior is introduced to link promotion to purchase through token systems, then content effectiveness can be measured, but the within-location experience is altered and complexity increases
Solution Approach 1:
The patent extracts the measurement mechanism from the individual user experience by collecting data at the population level through geographic and temporal aggregation. This removes the need for tokens, coupons, or other intrusive elements that alter individual experience, while maintaining measurement precision through controlled experimental design at the aggregated level.
Solution Approach 2:
The patent enables the system to self-measure content effectiveness through passive collection of behavioral data from existing user activities without requiring additional user actions. The experimental framework automatically tracks and attributes behaviors to content exposure through geographic and temporal matching, eliminating the need for user-participating token systems.
4Area of stationary object
If multiple content distribution channels are used to reach audiences, then content reach is improved, but isolating individual channel impacts becomes difficult due to overlapping spatial and temporal factors
Solution Approach 1:
The patent segments the multi-channel measurement problem by creating distinct experimental units based on geographic regions and time periods for each channel. This segmentation allows independent analysis of each channel's impact while accounting for overlaps, as each channel's experimental units are defined and measured separately, enabling precise isolation of individual channel effects despite broad content reach.
Solution Approach 2:
The patent adds temporal and geographic dimensions to channel measurement by defining experimental units across space and time. This multi-dimensional approach allows differentiation of channel impacts that overlap in the same physical space by separating them through temporal segmentation and geographic boundary definitions, thereby isolating individual channel effects while maintaining comprehensive reach measurement.
Data Source
AI summary
Systems and methods for organizing and controlling the display of content, then measuring the effectiveness of that content in modifying behavior, within a particular temporal and special dimension, so as to minimize or eliminate confounding effects.