NEW YORK , NY – April 14, 2020 – Bigabid, a data science company that has developed a second-generation optimized DSP for user acquisition & re-engagement, announced today that its proprietary data tool set Deep Categories, has exited beta.
Bigabid’s Deep Categories delivers targeted marketing results to app developers, because it reorganizes the app store using 1000 categories/sub-categories. Apps are more accurately categorized with new and more varied segmentations enabling LTV users to find apps with ease. Developers, such as charter client Gliding Deer (makers of the app Bingo Drive), are finding they are effectively reaching more users via Deep Categories technology.
Since its founding in 2016, Bigabid has evolved into a second-generation DSP, meaning that it offers meaningful scale and precise-targeting mechanisms, all in the same place. By focusing on post-install events, Bigabid helps app developers reach those users with the greatest potential for both engagement and in-app purchases. It is here where Bigabid developed its Deep Categories feature set, which, after a thorough beta testing period, is now ready for full deployment.
“Bigabid helps app developers reach users in multiple ways, with in-app purchases and continued engagement, thereby increasing positive ROI on digital campaigns,” said Ido Raz, President and Co-Founder of Bigabid.” Instead of the traditional few dozen verticals offered in app stores, we have developed a thousand Deep Categories to aid in the acquisition of high LTV users,”. “This technology allows Bigabid to break down the nature of user behavior in an unparalleled, detailed fashion, all without invading people’s privacy.”
Bigabid takes into consideration the functions and types of engagement apps provide, including the type of user activity, how the apps generate revenue, and their typical user demographics. From there, Bigabid determines the personalities of an app’s user base by looking at their users’ behavioral patterns and shared interests, such as the types of other apps they use and when they use them, their usage history and how they react to different types of ads. Once this data is collected, it’s used by Bigabid’s real-time bidding algorithms to determine bidding strategies and efforts, and to achieve the developer’s desired goals.
“Using Deep Categories has helped our team determine new user behavioral patterns, and has also allowed us to better understand the data we already have so that we can know when and where to deliver the most effective ads,” said Daniel Yaron, CEO of Gliding Deer. “We look forward to continuing our relationship with Bigabid to help us increase user acquisition and further grow our app.”
Bigabid is a data science company that has developed a second-generation DSP optimized for user acquisition & re-engagement. It offers exceptional scale and precise-targeting mechanisms, all in the same place. By focusing on post-install events, Bigabid helps app developers reach those users with the greatest potential for both engagement and in-app purchases. Bigabid’s proprietary “Deep Categories,” classifies apps into more than 1000 precise categories compared to the generic few dozen used by the app stores. This enables an unparalleled understanding of users and their behavior while eliminating irrelevant audiences, significantly reducing CPA, and increasing ROAS. Trusted by leading app developers worldwide, Bigabid can be used by any type of app and has a particular focus on casual games, e-Commerce and productivity apps. Its platform serves more than 200 million monthly app recommendations and 10 billion impressions daily based on 1 million predictions per second. Headquartered in New York, Bigabid was founded in 2016 by a team of industry veterans whose mission is to revolutionize the app marketing industry. For more information, visit: https://www.bigabid.com/
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