The app ecosystem has exploded over the last few years; creating inefficiencies for app discovery. Great for the platform vendors but not for the developers (or users), there have been numerous attempts to improve this, some of the obvious ones listed below (ignoring marketing tactics such as free-app-a-day):
- Vertical and specialised app stores (Amazon, Samsung, Sony, …)
- Cross promotional networks
- Review sites
- Increased categories
- Improved recommendations
- Third party apps (e.g. AppFlow, Appreciate, …)
This inefficiency is one major reason why Just-in-Time Interactions makes sense, especially as the app model extends to other platforms (desktop, TV, SmartWatchers, …).
Haven been faced this with question many times (how to market a mobile app) I thought I would have an attempt in making app discovery more relevant.
My prototype will be based on scalable word-of-mouth – the hypothesis is that your friends (social network) are most likely to be similar to yourself (similar interests, tastes, behaviours). One approach could be relying on explicit recommendations (not scalable), the other (and my approach) is to filter your friends on those who are most similar. From this sub-set, recommend the difference i.e. recommend those apps that you don’t have (apps are weighted based on factors such as how often they’re used, last opened, rating). Obviously for this to work you’ll need mass adoption of the service and a decently sized social network.