Harnessing the Power of Machine Learning for User Experience
Machine learning is one of the technologies that is taking the world by storm now. Due to its exceptional and unexpected capabilities that no one thought were possible, all fields and industries are rushing to make use of them. One of the main industries that is eager to take advantage of every capability of machine learning is the mobile app industry. In this article, we will explore the capabilities of machine learning and how it impacts apps and makes the user experience better.
What is Machine Learning
Imagination time! The year is 3000, and you are now very old. However, thanks to the great advancements, you still look the same. You are having a conversation with your favorite companion, who is, of course, nothing but a very advanced mobile device. I mean, it is 3000; who needs human friends? They live underwater now. Anyway, you are having a lovely conversation and realize that this device knows everything about you; it knows all your preferences, habits, and needs. It helps you with all your daily tasks in the way you prefer, without even asking. You stay quiet for a bit and remember how far machine learning has come. The technology that was just brand new and started finding its way into everything in our lives is now our companion.
Now, back to 2023, you still have your real friends; the world is not directed by Spike Jonze anymore. However, machine learning is still evolving and becoming more powerful. Machine learning is the ability of a machine to pick up and identify any user behavior, pattern, or preference. It is the technology behind many capabilities that makes our lives much easier.
According to many statistics and surveys, over 67% of businesses now incorporate machine learning into other operations. There are expectations for this rate to reach 90% in the future. So, there is no doubt that machine learning is now a vital thing to implement in all fields and industries
Machine learning and Artificial intelligence
ML + AI = forever! Machine learning and artificial intelligence are great companions. Both technologies complement each other and operate in great harmony. Businesses usually use them both simultaneously, as one enhances the other’s functions. For instance, machine learning provides artificial intelligence with user input or data and all the patterns it identifies. On the other hand, artificial intelligence, using natural language processing, can now communicate with users in the way they prefer and provide an exceptional experience.
Another thing to consider is that machine learning is only a part of artificial intelligence. However, it is very significant. So, you can pretty much say that artificial intelligence is a great, broad concept that carries many sub-technologies, like machine learning, underneath. Thus, we can state that both are inseparable.
The Impact of Machine Learning on Apps
The impact that machine learning has on apps is immaculate and exceptional. Machine learning helped developers explore new perspectives and unveil capabilities that apps had never had before. A generation of very advanced and smart mobile apps is now rising to simplify users’ lives and offer a one-of-a-kind experience. Machine learning is now embedded in many features to make them function better. It also creates a window of communication between users and apps, which, back in the day, sounded completely fictional. To make it clear, let us demonstrate the ways that developers use machine learning to enhance the user experience, with a use case for each one.
Ways to Enhance Your App User Experience with Machine Learning
Personalized experience and content are two ways in which machine learning can enhance the user experience. Machine learning algorithms can personalize recommendations for each user by assessing their past actions and interests. As a result, not only is the user experience enhanced, but so are the chances of loyalty and continued engagement.
The use case for this one is news apps. Many news apps now incorporate machine learning for all users. It allows the app to personalize the whole app for users and offer an exceptional experience. Machine learning identifies how the user engages with the app through behavior and patterns. For instance, the user is more interested in news about movies and music. Thus, machine learning capabilities would pick up that he usually accesses news about media more than any other type of news. This way, it could start displaying this type of news first and personalize the whole feed according to his preferences.
Personalized recommendations are one of the most common ways that machine learning is put to use to enhance the user experience. Machine learning algorithms can determine a user’s likely interest in a given product, service, or piece of content by evaluating their past behaviors and responses.
The user case for providing better recommendations is, of course, media streaming services. Media streaming services incorporate and make use of machine learning in a really smart way. Apps like Netflix use such technology to collect data and information about users’ preferences, habits, and even regions and start giving out better and more personalized recommendations. If you ever open Netflix after watching many drama movies, you will most probably find recommendations that relate to each and every drama movie you have watched. This has proven to be a very effective way to improve user experience, retention, and satisfaction rates.
Improved User Support
Improved user support is another area where machine learning could make a difference. By using machine learning algorithms, support chatbots can rapidly and reliably answer users’ questions, freeing up human agents’ time. A better user experience can be achieved through the use of machine learning to monitor user comments and behavior and identify areas in which help can be enhanced.
The use case in this way is food delivery apps. Since food delivery apps rely significantly on customer support channels to address any customer inquiry, they might as well incorporate an advanced and smart one. In this case, machine learning unites with its best companion, artificial intelligence, to provide an exceptional customer support channel. Instead of providing customers with automated responses that lack sympathy and transparency, machine learning identifies the tone and behavior of the user and sends out all the information for artificial intelligence to tailor responses accordingly. Machine learning can also learn from past interactions, so each time a customer returns for a second inquiry, it will most likely be able to recall the user’s information.
Online transaction fraud can also be detected and prevented with the use of machine learning. Machine learning algorithms can detect potentially fraudulent conduct by examining trends and behaviors and notifying the responsible authorities. This not only prevents financial loss for the company but also improves the user experience by offering a safe and reliable channel for financial dealings.
In this case, machine learning’s fraud detection is any financial app’s knight in shining armor. Fraud is, unfortunately, very likely to happen, no matter how secure and safe the environment of the app is. Hackers and fraudsters would always find any vulnerability to breach users’ data. However, the past is in the past with machine learning. By incorporating machine learning into financial apps, it can gather all the necessary information about users that is enough to understand their patterns and behavior inside the app. Once, machine learning detected any unusual pattern or activity, it would immediately alert developers of a possible breach.
Voice and Image Recognition
The use of voice and picture recognition is another way in which machine learning definitely enhances the user experience. The ability of machine learning algorithms to recognize and interpret human commands and images is made possible by their use of natural language processing and object recognition.
Some people can’t possibly function without voice-based assistance like Siri and Alexa. Both apps help streamline and remove the burden of redundant daily tasks that are difficult to deal with. Additionally, machine learning allows these apps to understand their users. Ever wonder how an app like Siri always remembers your name, your favorite songs, and your likes, and dislikes? Yes, it is machine learning. All these capabilities take the user experience to a whole new level and leave users eager for more.
Challenges and Concerns Regarding Machine Learning
People get very skeptical when something is perfect. Machine learning came as a genie in a bottle, but with more than three wishes to grant. How can possibly something make everything better? At this point, users and experts expressed some concerns about machine learning.
The major concerns were definitely about data and information privacy. As we stated before, machine learning technology is all about gathering data to understand user behavior. This has somewhat made people raise many concerns about what is done with all this data afterward. Keep in mind that this is all very sensitive information. Do other companies buy this data to use it? Are they used for future research? These and more questions were asked by many and had no answers. However, we can say that this depends on the data and privacy policies that each app and company have.