How Contextual Data and Analytics are helping Shape Mobile App Development?

The developers must track the emerging trends in mobile app development to keep their applications popular and profitable in the longer run. According to several surveys, contextual data and analytics are currently among hottest trends in mobile application development. Contextual data help the mobile app to deliver personalized experience to each user by understanding his preferences and immediate needs. Likewise, analytics help enterprises to analyze the contextual data collected through the mobile apps effectively to take most appropriate decisions.

Hence, the developers must include specific features in the mobile application to collect a wide range of contextual data including the user’s current location, previous transactions and device type. The use sensors included in mobile devices to capture physical contextual information like time of the day, temperature, humidity percentage, and motion data. At the same time, they must include advanced analytics help enterprises to analyze the contextual data efficiently to facilitate decision making. So both contextual data and analytics have become an integral part of modern mobile app development.

Impact of Contextual Data and Analytics on Mobile App Development

Cloud Technologies: Most companies nowadays rely on cloud computing the store large volumes of contextual data from various mobile devices, and analyze the information efficiently. Cloud storage options further help businesses to monitor and manage a large number of data points across different mobile devices. At the same time, an enterprise can also boost the mobile app’s user experience by sending actionable information to the user through cloud-based technologies. Hence, modern mobile apps need to be integrated with cloud-based technologies, along with taking advantages of cloud data analytics services.

Collection of Metrics: The mobile apps can be used for collecting a lot of data and a variety of user activities. So the users often find it daunting to organize and aggregate the contextual data according to their relevance. The developers need to focus on a variety of metrics to aggregate and sort all data effectively before storage. For instance, they must use business-related metrics to assess the performance of the mobile app, according to business requirements, based on conversion, engagement, and retention rate. Likewise, app performance metrics help users to assess the app’s user experience, along with identifying its strengths and shortcomings. At the same time, the developers also need to use low-level metrics to gather information about the crash, bugs or bad behavior in the mobile app.

Social Media Analysis: Within a shorter amount of time, social media has become an inseparable part of modern lifestyle. Most businesses nowadays use social listening as a tool to keep track of the choices of customers and emerging trends. But the developers have to keep in mind various aspects of qualitative social analysis while developing a mobile app. They need to use the right APIs to make the apps collect contextual data from popular social networking platforms. Also, the programmers must focus on various aspects of social media conversations to monitor the emerging trends continuously. At the same time, it is also important for the developers to combine the social media data and context to facilitate decision making.

Visualization of Historical Data: Each business must assess the historical data accurately and efficiently to take the right decisions. The data visualization techniques make it easier for managers to convey and analyze the contextual data collected from various sources. Hence, the developers need to build mobile apps using the right data visualization technique. For instance, they can use context analytics to decide the graphs that can be merged and send concise information to the system. The visualization technique further reduces the number of data points and simplifies the graph.

Real-Time Analytics: It is also important for the developers to create mobile apps that support real-time analytics. The real-time analytics help enterprises to store and categorize the information effectively at the time of collection. For instance, an organization can use real-time analytics to decide if the new data need to be stores separately or added to an existing or identical entity. A business can take advantage of the real-time data analytics to organize the contextual data based on their relevance, and keep track of the emerging trends efficiently.

Tools to Measure Mobile Analytics: Many enterprises nowadays use specialized tools to analyze the data collected through a wide variety of connected devices and mobile apps. Each business also has option to measure mobile analytics using various tools including TestFlight, Segment.io, Google Analytics, Localytics and Geckpboard. So the developers need to ensure that the mobile app support the mobile analytics tools selected by their client. They further need to integrate the mobile analytics tool seamlessly into the mobile app to optimize the data collection and analysis process. The programmers can also need special features in the app to customize the contextual data collection and analysis according to specific requirements of the client.

Repairing App Issues: The performance of a mobile app directly impacts the number of downloads. So the developers must monitor an app’s performance consistently and repair all issues immediately to get higher returns. They can easily analyze the mobile analytics to assess the performance of the mobile application, and identify all performance issues. For instance, the developers can use mobile analytics to assess the quality of source code and identify issues like device fragmentation. Also, the analytics help programmers to understand the factors affecting the end-to-end visibility and performance of mobile apps negatively. Hence, the developers can always take advantage of mobile analytics to boost the application’s performance and user experience consistently.

However, the mobile app developers must remember that the contextual data and analytics vary according to specific business requirements and nature of individual mobile apps. So they need to understand the business requirements clearly to include the right features in the mobile app to collect and analyze the relevant contextual data quickly and efficiently.