Today’s world, which primarily relies on intelligent technology to obtain data over vast distances, has accepted mobile apps on a large scale. Most apps are native, meaning they can access data even if there is no internet connection. According to the users’ needs, this paper discusses how the creation of native mobile applications necessitates the incorporation of numerous analytical contexts. To determine the contexts for developing native mobile apps, we empirically analyzed numerous publications based on ubiquitous systems and mobile apps. The mobile contexts include device, user, mobility, and social contexts. Our research shows that each mobile context’s overall weight can be empirically determined. A process model for mobile application development is built by incorporating these contexts, which pass through different phases such as requirement specification, requirement analysis, design, coding, testing, and validation. Different mobile e-commerce applications, such as Amazon, Nykaa, Flipkart, Make My Trip, etc., have been taken, and customer feedback has also been taken. We have analyzed customer feedback based on customer reviews. The accuracy of these mobile apps is determined based on customer ratings. Different datasets have been generated among customer ratings and other mobile app contexts. We have determined the accuracy of each mobile application to conclude which app is more accurate based on mobile app contexts.