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June 03, 2013

Taptica's 'Multi-Arm Bandit' Drives Mobile User Acquisition

Taptica, a provider of mobile user acquisition solutions, has announced what it calls its proprietary “multi-arm bandit” algorithm, combining optimization of direct media publishers with real-time bidding exchanges.

"Mobile user acquisition has progressed in leaps and bounds and we're proud to be a part of it. We're taking the technology forward and into the future," Taptica president Kobi Marenko said. "We believe that this added ability will give advertisers solutions that support diverse campaigns and help them better achieve their goals.”

Taptica’s algorithm offers machine-to-machine buying in addition to event-based tracking. Advertisers can get the best traffic faster by using this method than they could by using a manual campaign manager.

They can also track how people are actually using an app, looking at things like how many people have completed a tutorial, or reached certain levels in a game, as well as in-app purchases.

This allows advertisers to run a variety of campaigns, ranging from wider campaigns to more specific campaigns targeting specific types of users.

Taptica offers a number of mobile advertising solutions, including video, full page ads, app store SEO and real-time optimization.

The company has recently released a solution that allows advertisers to run video ads on mobile devices.

“We have noticed a tremendous shift in our platform recently whereby both advertisers and publishers are finding video and full page ads more lucrative" Marenko said. "Enabling different ad creatives on our SDK allows us to create a seamless synergy between advertiser and publisher resulting in much more effective campaigns for both sides.”

Taptica claimed that 90 percent of users who had come to an app from a video ad completed a game tutorial, compared to 50 percent of users who had come from other types of ads.

Taptica’s SDK lets advertisers place full-screen and video ads where they’re most user-friendly and can generate long term value.




Edited by Rory J. Thompson


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