A common criticism of reach-based measurement is the implication that all views are equal. Viewability metrics aim to filter out impressions that are so small or brief that they’re essentially unviewable. But any ads which clear this low bar are considered essentially interchangeable.
Many argue that what brands really care about isn’t whether an individual was shown an ad, but if they paid attention to an ad. Attention is much harder to both quantify and measure than basic reach, but a raft of companies have developed techniques and metric which aim to capture attention.
While there are nuances in how each individual company does this – where and how data is collected and how attention is interpreted – most share a common goal: to replace commonly used basic reach metrics with true measures of attention.
Here’s a guide to the leaders in the attention measurement space:
Realeyes, the oldest company on this list by a decent margin, measures attention through the lens of emotion, judging whether an individual is actually paying attention to the ad as well as their emotional response.
Realeyes runs an app on opt-in users’ mobile phones, which enables the phone’s camera to constantly analyse the individual’s face to gauge attention and emotions. Some users are paid for participation, others receive feedback on their phone usage (for example, Realeyes’ emotional analysis can help users understand which apps are negatively affecting their emotional state).
This attention data powers two products. One is measurement of specific pieces of creative, whereby Realeyes shows a specific ad to hundreds of users and measures their response, helping brands to optimise their ads to maximise attention.
The second, newer component is media measurement, which measures how much attention a brand’s ads are receiving on a live campaign. Realeyes uses OS-level data on Android devices to judge which ads a user is looking at, and is working on additional partnerships and tech to its ad recognition. This ad data is then paired with its facial tracking data to judge attention scores across live campaigns.
TVision is fairly unique on this list in how it focuses specifically on TV measurement.
TVision monitors both the TV set itself, but also individuals within households using sensor technology. TVision says it can measure both the amount of time that an individual is in a room when a piece of content is playing, and the amount of time that a viewer is actually looking at the screen.
The specific individuals can also be identified, allowing these attention metrics to be combined with demographic data (and TVision says panellists are chosen to be representative of their respective markets: Northeast, South, Midwest, and West).
TVision’s measurement applies across both linear TV and connected TV, and the company uses data including Wi-Fi signals to determine whether content is being played on a streaming service or linear TV.
Amplified Intelligence was founded by Dr Karen Nelson-Field, a former research associate at the Ehrenberg-Bass Institute for Marketing Science, off the back of a project for a large advertiser designed to measure the difference in effectiveness between different platforms.
Amplified Intelligence operates via a smartphone app, which pays users for their participation. Upon using Amplified Intelligence’s app, users are invited to select a few platforms which they would normally use, and engage with them as normal.
The app then uses their smartphone camera to record the individual’s face as they use platforms, tracking whether they’re looking at the ad, looking at the content around the ad, or not engaging with the ad at all. Amplified Intelligence also has code embedded in the ads themselves to measure things like how long the ad is on screen, whether sound is playing, etc.
This software can also be used for other screens – Nelson-Field says an “iPod on a tripod” setup is used for TV measurement.
The company analyses all this data to give an overall view of how much attention users are paying to ads, and maps this data against short-term and long-term business outcomes.
The overall results is a comparative view of attention across different platforms in different markets, helping advertisers allocate spend to media channels where their ads are likely to receive the most attention.
Adelaide Metrics’ offering is centred on its attention-based currency AU (Attention Units), an alternative to mainstays like the CPM.
Since Adelaide isn’t live-tracking whether users are looking at an impression or not, the company says it is measuring the quality of the media placement – that is, the opportunity to get a user’s attention – rather than the attention that an ad actually received.
Adelaide says it’s conducted research to demonstrate that high AU scores correlate with strong business outcomes. And the company has won the support of a number of notable industry figures – its $2 million funding round last year included former GroupM CEO Irwin Gotlieb, MediaLink CEO Michael Kassan, and former Nielsen president of US media Lynda Clarizio.
Playground XYZ currently sits as the attention component of a wider measurement business, having been bought by contextual specialist GumGum last year.
Playground’s ‘Attention Intelligence Platform’ collects eye-tracking data from a custom-built mobile web browser, and combines this with a wider dataset on the impression covering time-on-screen, context, and other relevant data.
The outcome of all of this – an overall measurement of attention time – powers a number of different products. Clients can use Playground’s pre-planning tool which gives attention insights based on the company’s dataset, and can measure attention across their own campaigns as an overall measurement of performance. Playground also runs a marketplace which folds in attention data to optimise bids, as well as optimisation of specific creative, and proprietary ad formats which are based on Playground’s attention data.
Lumen captures eye-tracking data via panels operated in the UK and the US. In the UK, its 1000-strong panel includes 250 desktop users and 750 mobile users, whereas in the US its panel is made up entirely of mobile users.
Lumen uses software installed on the user’s device to get access to either the mobile’s front-facing camera or the laptop’s webcam, which is used to track eye movement and measure where on the screen the user is looking. This is combined with data collected via a browser extension which shows which content is on the screen, allowing overall measurement of attention paid to ads.
This data powers the Lumen Attention Measurement Platform (LAMP), which uses predictive modelling to evaluate how much attention an ad is likely to receive based on publisher, format, and viewability metrics. The LAMP measurement tag can be used for post-campaign reporting, while a DSP plugin uses attention data to optimise campaigns.
Lumen also creates individual attention models for brands, and tests attention to specific creatives. And the company runs attention studies for other types of media, including TV, cinema, and OOH, to enable a form of cross-media attention currency.