Acquisition boosts Vungle’s advertising technology to provide contextual, machine learning-powered recommendations for maximum ROAS and user LTV 

Vungle, the leading mobile ad network and in-app monetization platform, announced the acquisition of AlgoLift, an LTV powered user acquisition automation platform for mobile advertisers. The acquisition adds AlgoLift’s industry-leading algorithms and optimization technology to Vungle’s global, creative-centric advertising network to give advertisers actionable intelligence to optimize performance metrics such as Lifetime Value (LTV) and Return On Ad Spend (ROAS). Additionally, AlgoLift’s probabilistic approach to campaign attribution gives Vungle a privacy-friendly way to target and optimize ad campaigns in compliance with pending iOS-related changes to IDFA.

AlgoLift is the automated ROAS optimization engine for gaming and non-gaming app developers such as Jam City, Take-Two Interactive, Digit and Headspace. Using AlgoLift’s predictive LTV modeling and automation tools, customers are able to scale user acquisition spend significantly while increasing ROAS by up to 150 percent. The combined offering will provide advertisers an automated solution using contextual data to buy against their downstream metrics. AlgoLift relies on anonymized data to deliver a unique solution to Apple’s upcoming iOS-related privacy changes.

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“Our mission is to be the trusted guide for growth and engagement for our developers,” said Jeremy Bondy, Vungle COO. “AlgoLift’s proprietary recommendation technology and  exceptional team, accelerates our transformation, extending the breadth and reach of our platform. As a result, our developers can expect an entirely new level of scale and performance.”

“At AlgoLift, we are very proud to have built an industry-leading LTV and optimization platform to help our clients maximize ROAS and operate at the cutting-edge of marketing technology,” said Andre Tutundjian and Dmitry Yudovsky, Co-founders of AlgoLift. “We couldn’t be more excited to join Vungle’s team to now bring a joint solution of leading-edge technology to the mobile ecosystem.”

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“The combined offering will enable Vungle to deliver machine advanced automation technology and contextual-level targeting recommendations to help global advertisers scale campaigns, improve real-time optimization and streamline workload,” said Martin Price, Vice President of Product at Vungle. “We are looking forward to integrating AlgoLift’s technology into our products to offer clients an automated, privacy-centric solution to buy against metrics such as ROAS.”

“Over the last few years, the AlgoLift team has been developing cutting-edge predictive models that tackle the hardest questions in the digital marketing space,” said Sinan Aral, Director of the MIT Initiative on the Digital Economy. “With this acquisition, the additional resources and reach made available to the team will help unlock their ability to materially elevate the standards of digital advertising, attribution and performance marketing.”

“Vungle’s acquisition of AlgoLift is the most intriguing development in the mobile advertising space in the aftermath of Apple’s decision to deprecate the IDFA,” said Eric Seufert, Media Strategist and Founder of MobileDevMemo, a mobile advertising and freemium monetization trade blog. “AlgoLift was one of the companies best poised to deal with the industry shift away from device identifiers and toward probabilistic and inferential targeting. By acquiring AlgoLift, Vungle is empowering itself to thrive in the new non-deterministic, privacy-centric advertising environment. Equipped with AlgoLift’s impressive measurement models and probabilistic attribution methodologies, Vungle will be well positioned as the mobile advertising industry undertakes this privacy-centric evolution.”

AlgoLift co-founders Andre Tutundjian and Dmitry Yudovsky, as well as the entire AlgoLift team will join the Vungle organization. The team will continue to operate out of the company’s offices in Los Angeles, providing a beachhead for Vungle in Southern California.

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