MediaPost: What About TV Attention? Q&A With TVision's Luke McGuinness

By Charlene Weisler, MediaPost

Attention is a challenge for many forms of visual media. How do we really know if a piece of content is seen? “IPG recognized that the industry had never effectively measured TV attention,” explained Luke McGuinness, president of TVision. “Ads are bought and sold on the assumption of 100% attention — but that assumption is false.” He should know, since his company tracks a range of television consumption behavior. 

IPG MAGNA recently released a TV attention study using TVision data. The study noted that regardless of device, attention indicates whether an ad has the opportunity to be seen but it does not guarantee that a viewer has actually seen the ad or whether that ad is effective.

Charlene Weisler: What prompted the study?

Luke McGuinness: More than $59 billion will be spent on TV ads in 2019, without knowing if the ads are viewable. IPG sought to quantify TV attention so that TV advertising could be measured in a manner similar to digital.  

Weisler: What are its implications?

McGuinness: The study from IPG Media Labs, using TVision data, found that 29% of all TV ads are not viewable. That means they air to an empty room. When we think about the $59 billion (or more depending on the source), ads that air to an empty room are costing advertisers quite a large sum. By evaluating TV for attention, advertisers can determine what is working, what is not, and optimize for better performance, and therefore substantially reduce ad waste.

Weisler: Please give me an overview of the methodology.

McGuinness: IPG reviewed six months of TVision data, tracking 5,388 individuals in a nationally representative panel, tracking 39,464 hours of ads for households, 2,992,414 unique ads, 5,961,757 impressions, persons 2+ and C3. Programming and ads were captured via ACR (automatic content recognition). Participants opted to install TV attention detection technology in their household. Attention were measured by using computer vision algorithms.

Weisler: Would you say that the results show that TV and digital are comparable in delivering ad messaging? What are the differences that you found?

McGuinness: The fact that the size of the attention issue for TV very closely mirrors digital video shows that the two face similar (29% for TV; 31% for digital video) challenges in delivering ad messaging, but there are some natural differences in attention for TV and digital. And these differences are rooted in the fact that digital video on PC and mobile are inherently different experiences. 

With digital, it is presumed that the consumer is there because of the nature of the medium. Someone just clicked to watch a video. As we all know, TV is very different. People leave the room or even leave the home with the TV on.  

Weisler: What is your recommended course of action to improve ad delivery and consumption?

McGuinness: The best step forward for brands is to measure what’s working or not for their historical TV advertising, benchmark versus competitors’ performance, plan a more effective strategy along with their existing planning tools, and measure and optimize on an ongoing basis. By using TVision attention and attention data, combined with other data such as cost and ratings data, brands can identify higher performing opportunities. For example, the study suggests that brands can find value by buying ad spots outside of prime, and outside of the first spot in the pod. 

Weisler: What about pod position?

McGuinness: In general, the first position in an ad pod may not be worth a premium. Ads appearing first in a pod had 72.2% attention. Ads in the middle of the pod had 70.3% and those at the end of the pod had 69.9%. Longer ads have higher attention but doubling the length of an ad does not double the attention, so the cost of longer ads must be considered.

Weisler: What are next steps?

McGuinness: The immediate next steps are for advertisers and networks to incorporate attention into their ad buying and selling — and many have already started to do so. They can do this by analyzing their historical performance for attention, analyzing their competitors’ performance, and learning from that. 

Read the full article in MediaPost.