John Owen Prince
Horacio Alberto Melo Torres
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Mysterio is solving the iOS app discovery problem by building a shopping experience that surfaces quality apps using proprietary machine learning algorithms. Good relevant apps are difficult to find on the App Store. The store contains over 500000 apps and 25000 are added each month. Apps are ranked by downloads not relevance or quality. As a result there is a thriving business in selling top positions by driving incentivized installs. Our solution is an iOS app that allows customers to shop for apps where every app they see has been machine curated. Our app talks to our Discovery Engine via a network connection. The Discovery Engine analyzes apps scoring them on quality genre and other metrics. This lets us determine quality independent of download count or star rating. The engine also determines genres of apps within Apple’s broad categories. Eighteen billion apps have been downloaded since 2008; the download rate exceeds 1 billion per month. Apple has generated $3.9 billion in app revenue since 2008, nearly 20% of that ($650m) earned since June 2011. Our Discovery Engine involves heavy engineering work and is not easily replicated. Our service is delivered in an app on the device where most purchases are made rather than on the web where most of our competitors focus. Finally our business model is based on affiliate revenue rather than incentivized installs. Our strongest competitor (AppsFire) pushes low quality incentivized apps at their customers while we only present quality apps and should gain trust and consequently traction from customers. Apple has long-established affiliate programs and we earn 5% commission for each sale we send to the App Store and on any additional purchases that customer makes for 48 hours afterwards. Our app will be distributed for free to help us reach the most customers.