Performing Mobile Analytics

  • Post last modified:19 May 2023
  • Reading time:9 mins read
  • Post category:Business Analytics
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Performing Mobile Analytics

Performing mobile analytics involves collecting and analyzing data from mobile devices in order to gain insights into user behavior, app performance, and business metrics.

Steps to Integrate Mobile Analytics With Business Processes

To integrate mobile analytics with business processes, you must perform the following basic steps:

  • Select the appropriate mobile device like a smartphone or tablet.

  • List the objectives of mobile analytics for your business process.

  • Identify the target audience and create a dataset for it.

  • Modify the dataset by adding missing values and removing unnecessary data.

  • Use the dimension-reduction technique and transform data (if possible).

  • Perform some required data mining techniques, like text mining.

  • Select data mining algorithms and do some analysis for mobile mining.

  • Applying data mining algorithm and verify the relationships among the variables.

  • Evaluate the result/interpretation.

Types of Mobile Analytics Based on Database Location

The whole process of mobile communication is done through the client-server method. So, the mobile analytics process can be done either on a mobile device or on the server providing services to the mobile device).

According to the location of data collection, mobile analytics is categorised as follows:

  • Data collection through the mobile device
  • Data collection on the server

Data Collection Through Mobile Device

Data for analysis is collected on the mobile devices and send back to the server for further manipulation. This collection process may be done online as well as offline.

This simply means that some data collection processes require an Internet connection to send collected data to the server but, on the other hand, several applications collect data into spreadsheets and they do not require an Internet connection. Collected data can be stored in various formats.

Data collection through mobile devices has the following benefits:

  • Allows data collection in real time

  • Proves beneficial for field executives

  • Allows data collection to be stored in various formats like text, graphs, images, etc.

  • Allows the location of field executives to be tracked and the management to assign tasks to them according to their location

  • Reduces unnecessary paperwork

  • Prevents data redundancy because the data is collected and shared with the entire team within seconds

Following are some commonly used data collection applications:

  • Numbers: Numbers is a very simple-to-use tool. It can be used to organise data, perform calculations, and manage lists for you with a few taps. It provides various templates for making graphs and charts. Moreover, you can create your own templates too. It has around 250 functions that can perform simple to complex calculations for you. You can create your own formulas through built-in functions and the help feature.

  • HandDBase: It is a relational database management system. It was initially designed to run on Palm PDAs but can run on almost any handheld platform. HandDBase is not as full-featured as Oracle, Sybase, and DB2, but, it still has various other features that make it important for computing. It is simple enough, supports multiple handheld platforms, and provides high security. The company offers a few apps to download free from its website.

  • Statistics Visualiser: It is a tool for iPads and is nicknamed as StatViz. This tool is a perfect statistical data tool for students and researchers. It performs statistical calculations and provides results with detailed explanations. The main feature of this tool is the dynamic graph, which helps you to quickly understand difficult statistical concepts.

Data Collection on Server

As we have studied in the previous section, data collected by a mobile device is ultimately transferred to its server for analysis. A server stores the received data, performs analysis over it and creates reports.

The following are some popular applications that collect data into the server:

  • DataWinners: It is the data collection service design for experts. This application converts paper forms into digital questionnaires. Team members can submit their data through any service like SMS, Web, etc. DataWinners provides an efficient data collection facility that can reduce users’ decision-making time.

  • COMMANDmobile: It is an application that can perform mobile data collection and workforce management services. COMMANDmobile is more accurate and efficient than traditional paper and pencil approaches. The application uploads the data as soon as it is collected. Its response time is very small; thus, it can perform well in emergencies. It gives very good ROI (Return on Investment).

Till now, you have studied various fundamental concepts related to mobile analytics. Now, let us do a practical activity with mobile analytics.

Get ready to analyse a dataset on mobile phones using a mobile application. We have already discussed the key points for analysing data by using mobile phones and tablets.

Now, through this hands-on practice, you will analyse data stored in a given dataset available on a mobile device. You must have an android mobile phone and an Internet connection to do this practical work.

The objective of the activity is as follows:

  • The marketing manager of a company performed an analysis on the listed price of items that his/her company needs to purchase from the company’s peers.

  • He/she wants to present the results of the analysis to the top management of his/her company during a meeting.

  • He/she wants to use graphical techniques to present the analysis results on a tablet that runs on the android Operating System (OS).

  • The marketing manager will use a mobile application, which he/ she needs to download and install on his/her tablet to demonstrate the analysis results. You are going to help him/her download and install the application and create graphs using the application.
Article Source
  • Blokdijk, Gerard (2015). Mobile Analytics – Simple Steps to Win, Insights and Opportunities for Maxing Out Success. Complete Publishing.

  • Harriott, J. S., & Isson, J.P. (2018). Win with Advanced Business Analytics: Creating Business Value from your data. Gildan Media.

  • Han, Sang Pil and Park, Sungho and Oh, Wonseok, Mobile App Analytics: A Multiple Discrete-Continuous Choice Framework (October 20, 2015). Management Information Systems Quarterly (MISQ), Forthcoming, Available at SSRN:

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