How to Use Predictive Analytics for Mobile App Development

Closeup of graphs and chart analyzed by business people

How to Use Predictive Analytics for Mobile App Development

Data collection plays a key role in business success today and leveraging the insights from data is what most companies are looking for to make informed decisions. Be it any industry, leveraging data insight is super important to improve business processes and performance. 

Whether you are running a test or using any project management suite or compiling the source code, you are generating data. The data then can be turned to data sets. 

What if you could turn these data sets into useful insights for identifying patterns and predicting future outcomes?

What is predictive analytics

Predictive Analytics utilizes the help of statistical techniques of data, algorithm, and machine learning (AI) to analyze current and historical data for making predictions about future outcomes and trends. 

Predictive Analytics Market Size, Opportunities and Forecast

As per MarketsandMarkets, the Predictive Analytics market size is expected to grow from USD 4.6 billion in 2017 to USD 12.4 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 22.17% during the forecast period.

Predictive Analytics Market Size

Though this buzzword has been around for decades, it is brand-new to software development, especially mobile app development. Leveraging the potential benefits of Preventive Analytics will help mobile app developers to develop applications that are futuristic and high performing.

How predictive analytics can improve app performance

With Predictive Analytics in mobile app development, you can optimize the app delivery pipeline with optimal estimates of time, effort, and cost; identify risks and opportunities; eliminate bottlenecks, and increase the quality and relevance of the app.  With this approach, any mobile app development company can improve the quality of the application and, simultaneously save time. 

The application of Predictive Analytics in mobile app development is termed as “Predictive Delivery”, which enables developers to deliver high-quality applications quickly with limited risk and ambiguity. 

How to use Predictive Analytics for mobile app development

Predictive Analytics will help you predict the future behavior of the data such as hours required for the app development lifecycle, amount of testing needed to produce a minimum viable product, or expected bugs on the testing line to expedite the app development and ensure app quality before delivery.  

A predictive model often uses known results to create a model based on testing, validation, and evaluation to make predictions through a given set of input data. It is reusable and developed using trained algorithms from the data set. When you want to reuse it, instead of analyzing the historical data, you can directly use the trained algorithm for the modeling.

Benefits of using Predictive Analytics in mobile app development

  • Amplify personalized marketing
  • Utilize customer behavior data
  • Enhance user engagement
  • Improve customer retention
  • Leverage future trends
  • Minimize the risk
  • Improve RoI

How to get started with Predictive Analytics

Getting started with Predictive Analytics is no rocket science. 

Here is a 4-step process to jump-start your program.

  1. Analyze– Why do you need to know about the future based on the past data? What do you need to predict and understand? What actions will be taken at the end?
  2. Collect– Both structured and unstructured data (inputs) are to be cleansed and prepared for predictive modeling.
  3. Deploy– Refine your model in a way that it works on the chosen inputs. At the end of the process, you will arrive at a result (output).
  4. Achieve– To turn analysis into real business results, you need an executive sponsor who can understand and manage both analytics and business.  

Predictive analytics is used in companies to identify risks, explore new opportunities, increase customer engagement, analyze market trends, manage supply-chain, measure consumer behavior, and empower customers. Now the same process is being used effectively in app development. These mobile apps will play a critical role in industries like Manufacturing, Healthcare, etc. to improve customer experience. 

Though the outcome of Predictive Analytics is seemingly a sequence of numbers, they make sense when they are put into a context. Remember, Predictive Analytics is a continuous process and you have to constantly work on the model to get accurate predictions. Get started with your mobile app development using Predictive Analytics to understand customers better and improve RoI.