Time-Slot Sampling for Content Effectiveness Measurement
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Solution Overview
Problem
Current marketing research methods fail to accurately measure the causation between advertising content and business results in retail environments due to confounding variables, leading to unreliable data and delayed actionable insights.
Innovation Solution
A system and method for generating time-slot samples to assign and measure the effectiveness of communication content by controlling the timing and location of its distribution, using a processor to determine viewer visit duration and time intervals, and algorithmically scheduling content to eliminate confounds and ensure true experimental design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional marketing research methods are used, then marketing spending can continue at current levels, but the ability to measure causation between content and business results deteriorates
Solution Approach 1:
The patent segments the continuous time period into discrete time slots, each assigned to specific content variants. This segmentation allows for controlled comparison between different content versions by isolating their effects in distinct time periods, thereby improving measurement precision and reliability of causation assessment.
Solution Approach 2:
The patent implements preliminary actions by pre-assigning content variants to specific time slots before the measurement period begins. This pre-planned assignment ensures that confounding variables are controlled from the outset, enabling more reliable measurement of content effectiveness without the need for post-hoc adjustments.
2Productivity
If traditional marketing research methods are used, then existing marketing processes can be maintained, but the speed of obtaining actionable insights deteriorates
Solution Approach 1:
The patent establishes continuous measurement by systematically collecting data across multiple time slots with different content assignments. This continuous data collection process eliminates gaps in measurement and enables real-time assessment of content effectiveness, significantly improving the speed of obtaining actionable insights.
Solution Approach 2:
The patent employs periodic content assignment across repeated time slots, allowing for multiple measurements of content effectiveness under controlled conditions. This periodic structure enables faster validation of results through repeated observation, reducing the time needed to demonstrate statistically significant effects.
3Measurement precision
If content is distributed without controlled timing, then distribution flexibility is maintained, but the ability to eliminate confounding variables deteriorates
Solution Approach 1:
The patent introduces dynamic content assignment where content variants are systematically rotated across different time slots based on pre-defined schedules. This dynamic approach maintains distribution flexibility while implementing rigorous control over confounding variables, as the system can adapt content timing without requiring complex manual intervention.
Solution Approach 2:
The patent controls confounding variables by systematically changing the parameter of time slot assignment across different content variants. By varying the temporal parameter in a controlled manner, the system isolates content effects from other influences, improving causation measurement precision without requiring complex structural changes to the distribution system.
Data Source
AI summary
Systems and methods provide for generating time-slot samples to which content may be assigned for measuring effects of the assigned content. Systems and methods provide for receiving viewer visit duration (VVD) that target viewers spend at a location where content is to be presented and receiving time intervals (TI) for data collection for data streams of interest that target viewers can affect during their visit to the location. A time-slot sample duration (TSSD) is determined using VVD and TI. Time-slot samples are generated that have a duration defined by the TSSD and a data collection period defined for at least a portion of the TSSD.