- 22nd March 2023 |
- 5 minutes
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Benefits to Person-level Audience Measurement
Person-level and single-source cross-media audience measurement is a combined method that can help advertisers and marketers use to measure the effectiveness of their campaigns and understand their target audience.
This method differs from traditional household advertising measurement in a few key ways and offers some unique advantages that make them valuable tools for advertisers. One of the key distinctions of person-level, single-source cross-media audience measurement is the level of granularity that it provides. Traditional household advertising measurement typically relies on data from large panels of households that have been selected to represent the general population. This data can be useful for understanding overall trends and making broad-brush assumptions about consumer behavior, but it doesn’t provide much detail about individual consumers.
The Granularity of Person-Level Single-Source Cross-Media Audience Measurement.
Target specific demographics and groups with person-level single-source cross-media audience measurement.
In contrast, the person-level single-source cross-media audience measurement method uses data from individual consumers to provide a more detailed and accurate picture of consumer behavior. This data can include information about what types of media content individual consumers are consuming, when and where they are consuming it, and how long they are spending on each piece of content. This level of detail can be incredibly valuable for advertisers and marketers, as it allows them to better understand their target audience and tailor their campaigns to reach the right people at the right time.
Direct Data Collection with Person-Level Single-Source Cross-Media Audience Measurement.
Industry shift: Welcome deterministic ad exposure measurement. Goodbye recall-based probabilistic measurement.
Another key difference between person-level single-source cross-media audience measurement and traditional household advertising measurement is the way that the data is collected. Traditional household advertising measurement relies on panels of households that are recruited to provide data on their media consumption habits. These panels are typically self-reported, which means that the data they provide is subject to potential biases and errors.
In contrast, person-level single-source cross-media audience measurement methods use data that is collected directly from individual consumers, and, it bases its analysis on deterministic data measurement rather than probabilistic approaches. This data is typically collected through passive mobile ACR measurement apps, online surveys, or other digital tools that allow consumers to provide information about their media consumption habits. Because this data is collected directly from individual consumers, it is generally considered to be more reliable and accurate than data from household advertising measurement panels.
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Household-level probabilistic data measurement is no longer the answer.
Another advantage of person-level single-source cross-media audience measurement is that it allows advertisers to track the effectiveness of their campaigns in real-time. Traditional household advertising measurement methods can provide useful information about the overall impact of a campaign but don’t provide detailed information about how individual consumers are responding to specific messages or offers. With person-level single-source cross-media audience measurement, advertisers can now monitor the response to their campaigns in real-time and make adjustments as needed to improve their effectiveness.
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Person-level cross-media measurement and passive automatic content recognition (ACR) panels are considered to be better than household-level panels for TV ad attribution because they provide a more detailed and accurate picture of individual consumer behavior. Traditional household-level panels rely on data from a group of households that are selected to represent the general population, but this data is subject to potential biases and errors because it is self-reported.
As mentioned above, one of the main flaws of household-level panels for TV ad attribution is that they do not provide detailed information about individual consumers. This can make it difficult for advertisers and marketers to understand how specific groups of consumers are responding to their campaigns, and to make adjustments as needed to improve their effectiveness.
Additionally, household-level panels are typically based on self-reported data, which can be subject to biases and errors. This means that the data they provide may not be representative of the true behavior of individual consumers, and may not accurately reflect the impact of TV ads on consumer behavior.
Overall, person-level cross-media measurement and passive ACR panels offer a more detailed and accurate picture of consumer behavior, and are considered to be better than household-level panels for TV ad attribution. These methods can provide valuable insights that can help advertisers and marketers better understand their audience and improve the effectiveness of their campaigns.
By Ian Alastair Hobkirk
Digital Marketing Manager
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