This is the first guided project in the "Data Scientist In Python" path on Dataquest.io. It analyzes data on iOS and Android mobile apps to make an app profile recommendataion for a hypothetical company that develops apps for both markets.
Both iOS users and Android users like to use apps with a social/communicative component, and productivity apps like Google Drive are also highly popular among Android users. To make our iOS app idea even more competitive in the Android market, we may want to include a feature that allows users to organize shared content by type of media (e.g. books, music, podcasts), genre, and other categories users may find helpful. In each of the media type domains, there can be an editable "to read" or "to listen" list, wherein users can bookmark media they want to engage with based on other users' recommendations. These feature may cater well to productivity-oriented users who like to stay organized and create/check off goals. For many users, being encouraged to discuss and reflect on media they've interacted with with their friends may enhance the social and educational value they gain from the app. Users' experience could vary greatly depending on the type of media they and their friends choose to share, which would ideally allow the app to attract a large and diverse user base.