『The Mobile App Business with Fexingo: iOS, Android, and Consumer App Companies』のカバーアート

The Mobile App Business with Fexingo: iOS, Android, and Consumer App Companies

The Mobile App Business with Fexingo: iOS, Android, and Consumer App Companies

著者： Fexingo
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The mobile app economy is a multi-trillion-dollar market, yet most apps fail within 30 days. Lucas and Luna dissect the strategies behind the hits and the graveyard of misses. They explore iOS vs. Android monetization models, from subscription fatigue to the rise of super apps in Asia. They analyze the economics of user acquisition, the psychology of retention, and the pivot of legacy companies like Microsoft into mobile-first design. Each episode takes a specific app category — health, gaming, fintech — and a specific company inside it: how did Strava build a social moat? Why did Snapchat survive while others faded? What does the EU's Digital Markets Act mean for indie developers? Lucas brings data on install-to-pay conversion rates and ad revenue benchmarks; Luna challenges assumptions about UX and market timing. They talk about the craft of the product, the business of the store, and the tension between growth and profitability. This is not a 'how to code your app' show. It is for product managers, founders, and investors who want to understand the mobile app business as a business — its unit economics, its platform risks, and its next frontiers. Can an app survive without venture capital? What separates a feature from a company? #MobileAppBusiness #IOS #Android #AppStoreOptimization #Freemium #SubscriptionModel #UserAcquisition #RetentionStrategy #SuperApps #FintechApps #HealthTech #GamingIndustry #DMAAct #Business #FexingoBusiness #BusinessPodcast #Technology #ProductLedGrowth Keep every episode free: buymeacoffee.com/fexingo© 2026 Fexingo. All rights reserved. 経済学
エピソード
  • How Mobile Apps Use On-Device Machine Learning

    How Mobile Apps Use On-Device Machine Learning
    2026/06/07
    Lucas and Luna explore how mobile apps are moving AI inference from the cloud to the device itself. They dissect Apple's Neural Engine, Google's TensorFlow Lite, and real-world examples from Snapchat's on-device lenses to offline language translation. The episode explains why on-device ML cuts latency, preserves privacy, and reduces server costs — and why it's becoming a competitive advantage for consumer apps. They also discuss the trade-offs: model size limits, battery drain, and the challenge of updating models on millions of devices. By the end, you'll understand why the future of mobile AI is staying on your phone, not the cloud. #OnDeviceML #MobileApps #MachineLearning #AppleNeuralEngine #TensorFlowLite #Snapchat #Privacy #EdgeAI #iOSDevelopment #AndroidDevelopment #AppPerformance #UserExperience #Technology #Business #FexingoBusiness #BusinessPodcast #MobileAppBusiness #AIInference Keep every episode free: buymeacoffee.com/fexingo
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    9 分
  • How Mobile Apps Use AI to Predict Churn Before It Happens

    How Mobile Apps Use AI to Predict Churn Before It Happens
    2026/06/07
    In this episode of The Mobile App Business, Lucas and Luna explore how leading consumer apps are using machine learning to predict user churn before users even think about leaving. Lucas breaks down a real case: a popular meditation app that built a churn-prediction model using session length, completion rate, and notification opt-in data. The model flagged users at risk of churning in the next seven days with 78 percent precision. The app then tested two interventions — a personalized coaching message versus a discount offer — and found that the coaching message reduced churn by 14 percent, while the discount only reduced it by 6 percent. Luna pushes back on the ethical implications of predictive targeting and whether users know their behavior is being modeled. The conversation drills into the trade-off between retention and trust, and how the best apps use prediction to serve users, not just retain them. #ChurnPrediction #MobileApps #MachineLearning #UserRetention #AppBusiness #PredictiveAnalytics #MeditationApp #Personalization #Ethics #AI #ConsumerApps #ProductStrategy #Growth #DataScience #FexingoBusiness #BusinessPodcast #BusinessAndTechnology #AppMonetization Keep every episode free: buymeacoffee.com/fexingo
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    10 分
  • How Mobile Apps Use Silent Notifications to Win Back Users

    How Mobile Apps Use Silent Notifications to Win Back Users
    2026/06/06
    Episode 35 of The Mobile App Business digs into silent push notifications—the background data pings that apps use to preload content and re-engage users without a single sound or banner. Lucas and Luna break down how this technical trick works, why it's different from spammy alerts, and which app categories are seeing 20–30% higher re-engagement rates by using it. They walk through a specific case: a fitness app that used silent notifications to update step counts in the background, then saw daily opens jump from 18% to 41% within two weeks. The episode also covers the privacy trade-offs, iOS and Android quirks, and why getting silent notification timing wrong can actually hurt retention. If you build or market a mobile app, this is one retention lever you're probably underusing. #MobileAppBusiness #SilentNotifications #PushNotifications #UserRetention #ReEngagement #AppGrowth #iOS #Android #FitnessApp #BackgroundRefresh #UXDesign #AppMarketing #EngagementStrategy #BusinessPodcast #FexingoBusiness #MobileApps #AppDevelopment #NotificationStrategy Keep every episode free: buymeacoffee.com/fexingo
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    12 分
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