How data analytics has always been around

Data analytics - older than we think!

Use of data analytics in business has recently hit the mainstream with a lot of tech startups adopting various tools to improve their business. But there is a lesser-known side to this story which is easily ignored – analytics has always been around! Scientists, for example, have been using it all this while. It’s just that they didn’t give a fancy name for it. For them, it was simply science. Some companies have also been doing analytics for several years now, but mainstream adoption among conventional businesses and startups has been fairly recent.

A good example of the use of analytics in science is in medicine. Vast data repositories and reports of uni and bivariate data are used to assess patient conditions. Predictive analytics has played a huge role in knowing the outcomes in many scenarios to an astonishing degree of accuracy. Prescriptive analytics is giving scientists insights into early stage drug development and helping doctors choose the best medical approach and practices.

Another popular and recent example is the use of advanced data analytics in the Large Hadron Collider(LHC) near Geneva, Switzerland. The particle collider is not just the largest of its kind, it’s also the largest single machine ever built by man. In June this year, IDT successfully ported CERN’s root framework to a more advanced RapidIO framework. The LHC produces millions of collisions every second in each detector, generating approximately one petabyte of data per second. Data analytics carried out on such large datasets are what allow the scientists working at CERN to understand the results and find answers to the creation of the universe.

All this and more, is not very different from how businesses are employing analytics today. They have large datasets containing customer data, sales data, and various other data points. Analytics helps them make sense of all of it. During the process, they observe trends and obtain information that will drive business change and support sustained business practices.

App businesses have started to understand the importance of user retention as opposed to user acquisition. Spending a big chunk of the budget on finding new users has finally caught up with many startups. Raj Aggarwal, CEO of Localytics said in an interview that 25% of apps are used only once and almost 58% of users churn in the first 30 days of using an app.

Due to this shift in focus to user retention, the app analytics world is buzzing about the need to track user behavior. This would enable app owners to provide their users with a more personalised experience.  Here are some of the common data points which are being collected as part of this analytical exercise:

  • Total number of screens seen per session
  • Order in which screens are viewed
  • Number of technical errors, including app crashes
  • How long individual app elements take to load

There is one thing that needs to be kept in mind while using these insights. This information is based on how users are interacting with the app. Your users cannot tell you how to scale your business. Neither can they predict which feature would be the next best thing to have. Risks still have to be taken and product owners must not dump their business roadmap just because of the data analytics. The insights should help you make adjustments to the plan and make sure the decisions are made more accurately.

Pravir Ramasundaram is our in-house content writer here at ContractIQ. Keep coming back to read more from him on mobility, outsourcing & analytics!

Building an app? Tell us about your project

We'll connect you with the right team for your project, for free!