Effective Machine Learning Ideas to Improve User Experience on Apps

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Machine learning is a buzzword used to describe much of today’s technological innovations. Many top-ranked companies are adopting machine learning. This blog talks about useful machine learning ideas to improve user experience on apps.

Today, rapid technological advancements have reshaped our world in ways that were once thought to be impossible. Machine learning is an example of one of these technological advancements ML has been making waves by enhancing the user experience on apps for years now. Let’s dive deeper into the following stats to know more about machine-learning:

What Is Machine Learning?

Have you ever wondered how Netflix recommends the shows you must watch? How does YouTube recommend videos based on your viewing history? How do e-commerce websites suggest to buy similar stuff based on your search history or your previous purchases? Who sends these recommendations? Machine learning!

Machine learning is a subset of artificial intelligence (AI) that allows systems to learn and improve from experience without being explicitly programmed automatically.

Benefits of Implementing Machine Learning in Apps

  • ML technology can predict user behavior, optimize processes, lead up-sell, and cross-sell.
  • Half of the enterprises are employing machine learning ideas to design better UX/UI that grabs the users attention.

Machine Learning Ideas in Apps to Improve User Experience

Personalized User Experience

Machine-learning-based personalization provides a more scalable and reliable way to achieve unique user experiences. The most fitting example of ML is the suggestions of ‘people you may know’ on social media and ‘buying of products’ recommendations on e-commerce platforms. To enhance the user experience, you can integrate machine-learning in apps.

In business, machine-learning helps group users with similar interests and collect their information to decide on what content the app displays. Companies use machine learning to know the following:

Who are their potential customers?
What is the customer’s need?
What are their preferences?
What is the choice of the words of users to search for products?
And more…

By using advanced algorithms and predictive analytics, ML app developers can create a machine-learning-based app that leads to smart user experience.

Advanced Search

Right now, search engines are evolving machine learning. ML allows customers to optimize their search. By incorporating ML in apps, users can. With its unique algorithms in advanced search, machine learning takes data from previous searches and prioritizes the results based on their interests.

DIY videos, frequently asked questions, articles, scripts, and others are the apt example of ML integrated for advanced search. Also, enabling voice search and spelling corrections in advanced search for your app can improve the user experience substantially.

Automation

Machine learning has helped improve automation which has enhanced the services offered in a variety of industries. As per Forbes, Amazon attributes 35% of its revenues to personalized product recommendations, which are regularly updated and optimized for each user.

Consulting an app development company that holds expertise in ML integration is a smart move for your business. The automation mentioned above allows you to optimize the experience of individual customers and keeps customers coming back.

Relevant Ads

Showing the right ads to the right group of audiences at the right time can do wonders for your app. As Michael Griffin (founder of Adlucent) stated, “As brands continue to battle for consumer dollars, it’s clear that the way to win is through personalization. Consumers expect content that is both useful and contextually relevant ‒ the right information served at the right time”.

Machine learning presents ads and personalized messages accurately to the different audiences by using its algorithms that improve the brand reputation and user experience of your app as well.

Improved Security

Machine learning allows users to authenticate critical data with the use of their biometric information such as fingerprint or face detection with high-end security. It can be a smart decision to use machine learning in the app to help improving user experience with the best possible security.

Also, machine learning opens access to a variety of features such as image recognition, shipping cost estimation, product tagging automation, wallet management, and many more with its valuable secured methods.

Conclusion

Integrating machine learning technology in your app not only improves user experience but also helps businesses to grow swiftly.

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