How Machine Learning Improves User Experience in Mobile Apps?

Machine Learning (ML) is expected to bring heavy changes to the world of technology. Machine learning is a subfield of artificial intelligence and computer science that allows software applications to be more accurate in predicting results. The prime objective of machine learning technology is to build algorithms that can get input data and leverage statistical analysis to predict an acceptable output value.

Machine learning defines a new form of software development, where computers, gadgets and other devices that are essential to develop a software don’t need special programming to get done tasks. Instead, they can gather and analyze information that is required to derive relevant outcomes and learn during program performance.

Like humans, machines can learn from previous experience in order to make decisions. The process of learning needs specially built algorithms that would teach machines what exactly they have to do. This is where machine learning companies come into need.

Applications of machine learning in different areas:

Machine learning is a multidisciplinary field, which can be applied in various areas including science, and business.

Machine learning applications in robotics

Robotics is a technology that requires to perfectly integrate mechanisms and cognitive technologies. Today we can see robots that assist people on work in both office and house, as we as take care and entertain them. And people can manage these robots using their smartphone with voice commands or program tool actions.

Machine learning applications in data mining

Data mining is a technology that works on to analyze big data and unearth interesting, non-obvious correlations within a huge set of data. It covers an every area of extracting insights from data, from storage to maintenance and actual analysis. Here machine learning provides a set of tools and the learning algorithm to unearth all possible correlations.

Machine learning applications in finance

In finance, machine learning algorithms are widely used for forecasting future trends, bubbles, and crashes. For example, in an effort of determining the credit rating, AI-powered custom software can analyze all sorts of information about borrowers such as previous transactions and activities on social media.

Machine learning to enhance user experience in mobile apps and websites

Machine learning works on the principles of intellectual learning, which is very similar to human brain. Like human, machines can also learn with past experiences. AI-powered machines are capable to analyze big data, analyze user behaviour through previous activities, and then predict the best solution to the specific user. Machines can use the same formula on apps and websites.

Personalization and Recommendation on Digital Channels

Machine Learning and its algorithms are data-driven technologies. We all have come across the application of ML in the form of Products You may Like in eCommerce websites and People You May Know in Facebook. These approaches can help businesses in a number of ways like:

• Filtering the most appropriate content in accordance to user interest.

• Making app more interactive in accordance to users’ specific taste

• Creating advertisements according to users’ taste, thereby converting it into purchase or lead.

Smart and quicker search

Speed is one of the key elements when it’s about compelling user experience. Today’s mobile apps are clever enough to gather the customer data like search history, click-through and sell-through rate etc. Machine learning helps to turn it into personalized experiences for customers.

Just think about recent Google searches, and how intelligent enough that is. ML is improving user experience, by making the search faster and smarter.

Conclusion

Machine learning has its applications not only in the above mentioned fields but also in fraud detection, security, healthcare and fitness management fields.

If you need help to implement ML into mobile apps, USM will help you.