Additive Reach Adjustment for Unmeasured Audience Tuning
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Solution Overview
Problem
Existing audience measurement systems fail to accurately account for unmeasured tuning data, leading to underestimation of media reach due to unrecognized content by automatic content recognition (ACR) devices.
Innovation Solution
The implementation of an additive reach adjustment circuitry that determines an additive reach adjustment factor by calculating the probability of unmeasured tuning and incorporating it into the reach calculation, thereby accounting for missing impressions from unmeasured stations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic content recognition (ACR) devices are used to collect tuning data, then data collection efficiency is improved, but measurement precision deteriorates due to unrecognized content leading to unmeasured tuning data
Solution Approach 1:
The patent introduces an intermediary calculation process that uses panel data as a mediator to estimate unmeasured tuning. The system calculates station tuning factors from panel data and applies these factors to big data to derive an additive reach adjustment, thereby bridging the gap between ACR device limitations and accurate reach measurement.
Solution Approach 2:
The system uses available panel data and big data to self-correct for the deficiencies in ACR device recognition. By calculating station tuning factors from panel data and applying them to adjust big data reach measurements, the system compensates for unrecognized content without requiring additional external measurement resources.
2Measurement precision
If station-based tuning factors are applied to adjust reach calculations, then measurement precision is improved, but device complexity increases due to additional calculation requirements
Solution Approach 1:
The patent performs preliminary calculations of station tuning factors using panel data before applying them to big data reach measurements. This preliminary action allows the system to pre-determine adjustment factors that can then be systematically applied to correct reach estimates across multiple stations and time periods.
Solution Approach 2:
The system segments the reach adjustment process into distinct components: calculating station-specific tuning factors from panel data, determining unmeasured tuning percentages for each station, and applying these factors as additive adjustments to big data reach measurements. This segmentation makes the complex calculation process more manageable and systematic.
Data Source
AI summary
Methods, apparatus, systems, and articles of manufacture to determine an additive reach adjustment factor for audience measurement are disclosed. An example apparatus for additive reach adjustment includes at least one memory, machine readable instructions, and processor circuitry to execute the machine readable instructions to identify a first probability, the first probability associated with a population tuning to a marketing campaign, the tuning including missing data, identify a second probability, the second probability associated with the population not tuning to the marketing campaign or the tuning including missing data, determine an additive reach adjustment based on a compound probability and a no-tuning probability, the compound probability and the no-tuning probability determined using the first probability and the second probability, and credit a population exposed to the marketing campaign to include missing impressions based on the additive reach adjustment.