16apps.com Picks iPhone Apps Based on Your Social Media Profiles
Alex Covert — August 19, 2009 — Tech
References: 16apps & trendhunter
Don’t have time to sift through 60,000+ apps? Me neither. Sure, I spent the first couple evenings perusing through iTunes, but in the end, I had downloaded a mere 16 apps. That’s it… just 16! Apple’s television commercials had worked - ingraining in me a desire to have virtual bubblewrap and a digital level. If only there were an easier way.
And now there is - 16apps.com. A user simply submits their social media username (e.g. Twitter, FriendFeed, or Last.fm) and 16apps searches through their posts… highlighting aspects of their life and recommending relevant apps with links to the iTunes App Store.
And now there is - 16apps.com. A user simply submits their social media username (e.g. Twitter, FriendFeed, or Last.fm) and 16apps searches through their posts… highlighting aspects of their life and recommending relevant apps with links to the iTunes App Store.
Trend Themes
1. Social Media-based App Recommendations - Developing algorithms that analyze social media profiles to recommend relevant apps presents an opportunity for innovation in the app discovery space.
2. Personalized App Curation - Creating personalized recommendations based on user preferences, interests, and behaviors can improve app discovery and engagement for users.
3. Automated App Suggestions - Using machine learning and AI to analyze user data and suggest new apps without requiring any manual input could revolutionize the app discovery process.
Industry Implications
1. Mobile App Discovery Platforms - Developing platforms that automatically recommend new apps to users based on their social media profiles and behavior represents an opportunity for innovation in the mobile app industry.
2. Personalized Advertising - Leveraging user data to offer personalized app recommendations through targeted advertising could disrupt traditional advertising models.
3. Mobile Analytics and Insights - Using data analytics to understand user behavior and preferences and developing insights to inform app recommendations could be a disruptive innovation in the mobile app industry.
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