Contextually aware apps are able to deliver tailored experiences in the form of timely, relevant and appropriate information, notifications and/or functionality.
Consider the Challenges
Step Five: Get acquainted with the technical challenges and considerations.
CAAs are the next generation of intelligent apps, and while they go beyond personalized, location-based messaging, it is not a bad idea to begin building context data by linking user profiles and demographics with past activities, app behaviors and purchases as a starting point. But there are a few things to keep in mind:
- While lots of effort should go into collecting user information, in the case of privacy-sensitive applications such as HIPAA-compliant medical apps, the user can be de-identified while keeping a record or token that allows the app to still learn personal preferences and provide contextual interactions.
- A smartphone's sensors can be used to receive additional context data. The more context data an app can collect – i.e., Big Data – the more information can be provided to the user. But in order for this data to be useful to the app and the user, the data usually needs to be analyzed in real-time, or risk becoming stale and irrelevant. A Big Data architecture may be required so the app can return useful information quickly.
- Inferred information from context data is another issue to consider in terms of accuracy – what if the information derived from context is so far from reality that the app behaves unexpectedly? What can be done to mitigate such an event, and achieve a reasonable user experience under such risk?
