The European VR industry has officially backed a metric that tracks how long users are staring at ads.
Dubbed the "Gaze-At-Ratio" or GAR, the algorithm determines the value of a user’s gaze in relation to a digital ad by factoring distance, duration, and depth of a user's gaze as the object (advertisement) enters and exits their field of vision.
The metrics was first suggested by EUVR, a European non-profit dedicated to the VR industry. The GAR metrics was part of a broader measure to ensure AR/VR doesn't one day become a tangled dystopia with in-experience ads.
While EUVR wants to create better digital experiences, it’s also wanting to bring advertisers into the mixed reality world.
"Any solution that helps to accelerate VR monetization is welcomed by everyone, and in Europe, standardization is extremely popular," said Juan Bossicard, co-founder of the EUVR. "It’s the stepping stone to fostering a sustainable ecosystem, and the time for it is now."
The authors who introduced GAR in October 2017, wanted to establish a VR ad metric that is fueled by user attention. The authors are developing it side-by-side with the community to help standardize the single metric.
With the lack of progress in establishing monetization models that suit the emerging medium and allow the industry to scale, the conception and development of the GAR was inspired out of frustration in the VR creator community.
Before GAR was introduced, content creators and publishers were acting on their own to approach monetization problems on VR/AR. This is because traditional methods of calculating value, like cost per impression, is obsolete and can't be implemented into mixed reality of VR and AR.
This lack of solidarity is said to stall the industry. Both publishers and prospective advertisers were reluctant to fully step into the space until the landscape and its technology mature.
In the initial demo, ad-objects were scattered throughout a AR/VR environment. The GAR rate accelerates as a user approaches the object, when it enters user's line of sight or ‘direct gaze’, and whether the user interacts with the object, like picking it up.
The idea of GAR is to know whether objects in the space are either absorbing a user’s attention, or not. The GAR algorithm can calculate all of that with precision and determine a value.
