Vdopia Drives Mobile Video Viewability With “Inview” Format

Vdopia Drives Mobile Video Viewability With “Inview” Format

Video advertising platform Vdopia launched its native video ad format InView in Australia today. Launched in the US in June 2015, InView enables advertisers to place brand video ads inline within content on mobile sites, not only delivering a non-obtrusive ad experience for the viewer, but also delivering important viewability measures for the brand advertiser.

InView technology is designed to play video ads only when on-screen and in-view of the mobile user. If the user scrolls to where less than 50 per cent of the ad container is viewable, the video will pause. The video will then resume where it left off once the ad container is at least 50 per cent on-screen and in-view for the user once again.

“By 2019, mobile’s share of total digital video ad market will reach nearly 50 per cent. This significant shift is being driven by brand advertisers simply wanting to be where consumers are – on mobile video,” said Saurabh Bhatia, cofounder and CEO of Vdopia. “Through InView, we can offer those advertisers scale, view-ability and transparency, while also offering publishers non-intrusive ad experiences and the best monetization.”

Yahoo7, one of Australia’s digital publishers, is the first to integrate Vdopia’s InView technology, in response to growing demand for mobile video inventory in the Australia/New Zealand market.

Venessa Hunt, mobile strategy manager, Yahoo7 said: “The industry is focused on innovative ways to use video in mobile advertising, Vdopia’s InView format offers Yahoo7 an additional creative solution that shows our commitment to video and mobile and supports our clients needs.”

Vdopia is rolling out a number of additional InView partnerships in the region in the coming months. InView ads are compliant with IAB’s Video Ad Serving Template (VAST) and are offered with 3rd party tracking from industry-leading, accredited partner MOAT, as well as viewability measures from InView itself.

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EMMA data John Zeigler

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