25 April 2022|Advertising, Audience, Reach, Research

In an ideal world it should be possible to measure the total audience for a brand’s advertising, across all media, taking into account the varying impact of each medium.

In reality each medium has its own measurement method, and audience measurement for internet advertising can vary from one media owner to the next. Counts of advertising exposure across media are not remotely equal. Figuring out the total net exposure for a brand across all media, its net reach and frequency of exposure, is next to impossible.

The siloed currencies for trading media audiences typically work as follows in most countries:


  • A panel is used to measure TV audiences.
  • A television “viewer” claims to be in a room where a TV set is on. Claimed viewing is recorded by pressing a personal button on a ‘peoplemeter’ when entering or leaving the room where the TV is on. Guest viewing is recorded on the panel’s peoplemeters in the same way.
  • Viewing is measured in homes only, so excludes non-home exposure (eg. in clubs, bars etc).
  • Minute-by-minute recording of presence by the individual is matched to the channel on set.
  • Does not measure eyes on screen for ads or listening to ads.


  • Based on an in-home interview or self-completion questionnaire amongst a sample of the population.
  • A “reader” claims to have read or looked at a publication within its most recent publishing interval.
  • Does not measure readership of specific issues of titles.
  • Does not measure exposure to individual pages.
  • Does not measure exposure to individual ads.


  • Based on a self-completion diary across a week amongst a sample of the population.
  • A radio “listener” claims to have listened to a station for at least five minutes within a quarter hour period.
  • Does not measure exposure to individual radio programmes.
  • Does not measure exposure to individual ads.


  • A poster “viewer” is modelled from a mix of visibility criteria and researched traffic data.
  • Audiences to each poster are modelled from site classification data and the results of traffic research projects. Visibility adjusted impacts are used to estimate the likelihood of a poster being seen.
  • Does not measure exposure to individual ads.


  • Internet audiences are measured using either site data, or panel data, or combinations of both.
  • Calculation of audience reach for ads on sites is typically based on ‘Unique Devices’ sourced from cookie counts, typically for the prior 30 days.
  • The accuracy of audience measurement from site-centric data is subject to a number of issues: a) up to a third of internet users delete their cookies each month, and they do so an average of four times each month. Cookie deletion means that unique visitors may by overstated by several times. b) Additionally, cookies overcount unique visitors because many people use the internet from multiple machines — for example those accessing from work and from home. c) Bots (many fraudulent) result in audience counts that are overstated (not based on human visits). d) Device counts do not provide insight on the users behind them. e) Cookies have been stopped on the Safari and Firefox browsers and will end on Chrome in 2023.
  • The accuracy of audience measurement from panels is also subject to significant issues: due to the very highly fragmented nature of the medium, panels are not large enough to accurately record the audience for most internet ads.

To summarise, here is a comparison of how an opportunity to see or hear an ad is measured by medium:

  • TV — panel claiming presence in a room where a TV set is on.
  • Print — sample claiming to read/look at an average issue of a publication. No ad-specific measurement.
  • Radio — sample claiming to listen to a station for at least five minutes. No ad-specific measurement.
  • Outdoor — modelled by combining visibility criteria with historic traffic research. No ad-specific measurement.
  • Internet — unique device visit counts with no standard industry measure of OTS/OTH for ads.

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By Frank Harrison, Croft Analytics



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