Correcting Systematic Defects in Set Top Box Tuning Volume Data
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Solution Overview
Problem
Audience measurement entities face inaccuracies in tuning volume data collected from set top boxes due to systematic defects, such as incorrect reporting of set top box states and power outages, which are not currently corrected in conventional media monitoring techniques.
Innovation Solution
The implementation of a method to identify and correct systematic tuning data defects by comparing raw tuning volume data from return path data with monitored data, flagging suspect time windows and modifying specific return path data entries using statistical models to ensure accurate representation of set top box behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional media monitoring techniques are used to collect tuning volume data from set top boxes, then data collection is simple and does not require additional hardware, but the data contains systematic defects such as incorrect reporting of set top box states and power outages
Solution Approach 1:
The system performs preliminary identification of suspect time windows by comparing return path data with monitoring data before final data correction. This preliminary action flags problematic periods for targeted correction, improving accuracy without processing entire datasets unnecessarily.
Solution Approach 2:
The system introduces monitoring data as an intermediary reference to identify and correct defects in return path data. By comparing return path data with independent monitoring data, the system detects systematic defects and uses the monitoring data as a basis for correction without requiring additional hardware at the set top box level.
2Ease of manufacture
If return path data is used for audience measurement, then no additional hardware installation is required, but systematic tuning defects remain uncorrected
Solution Approach 1:
The system uses monitoring data as feedback to identify systematic defects in return path data. By continuously comparing return path data with monitoring data and identifying suspect time windows, the system creates a feedback loop that enables automatic detection and correction of reliability issues without changing the data collection method.
3Measurement precision
If statistical models are used to correct return path data entries, then accuracy of tuning volume data improves, but processing time and computational resources increase
Solution Approach 1:
The system segments the correction process into distinct phases: identifying suspect time windows, selecting return path data entries within those windows, and applying statistical models only to selected entries. This segmentation reduces the overall processing time by limiting statistical model application to only the data that requires correction.
Solution Approach 2:
The system applies statistical correction only to specific return path data entries that fall within suspect time windows, rather than correcting all data uniformly. This partial action approach maintains high accuracy for problematic data while minimizing unnecessary processing of already-reliable data.
Data Source
AI summary
Apparatus, systems, articles of manufacture, and methods are disclosed for correcting systematic tuning defects. An example apparatus includes a defect analyzer to identify a suspect time window in tuning volume data of return path data reported by set top boxes. The example apparatus further includes a return path data transformer to identify a first return path data entry indicating a first set top box reported a first transition to an off state at a first time during the suspect time window and to modify the first return path data entry to (1) eliminate the first transition to the off state at the first time and (2) assign the first return path data entry a first duration to remain in an on state after the first time, where the first duration is determined based on monitoring data reported from media device meters monitoring media presentation devices.