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Using AI to Develop Better App User Experience

App Design

Using AI to Develop Better App User Experience

May 22, 2019

Smartphone usage has gone up significantly across the globe. And with it, so has mobile-based access to the internet. According to an Internet Association study, around 76% of mobile users across the globe today are connected to the internet throughout the day.

This information doesn’t come as a shock. Every single one of us is part of this. The moment we wake up, we’re on our phones browsing social media or the news. This continues throughout the day and many of us are dependent on mobile devices even in our professional lives. There’s an endless list of tasks that we carry out on these platforms.

This increased dependence on mobile devices is good news for app development firms. The more people are dependent on mobile devices, the more apps they’ll need. However, the app market is extremely crowded and setting your software apart from the competition is a Herculean task.

So, how do you do it?

Well, there are several strategies you could use and various technologies you can leverage. One of them is the use of AI or Artificial Intelligence. AI already plays a vital role in digital marketing today. Let’s take the example of machine learning.

Machine learning is a type of AI technology that’s all about getting computers to learn and act on their own without any pre-programming. Go deeper into machine learning and you’ll arrive at deep learning. Deep learning is the automation of predictive analytics.

In machine learning, there are generally 3 kinds of algorithms. We have supervised learning, where data sets are labeled to aid pattern detection and further data labeling. Then there’s unsupervised learning where data sets remain unlabeled and are organized in accordance with similarities and differences. Finally, we have reinforcement learning, where the data sets are unlabeled but the AI system is given feedback after an action is performed.

In this contest, AI refers to a broad concept of machines with the ability to carry out tasks in an intelligent manner. However, machine learning specifically refers to feeding machines with data and allowing them to learn from it.

This is exactly why the data patterns detected by AI and machine learning can go a long way in improving processes or aiding the achievement of objectives such as improved app user experiences.

AI already has a tremendous impact on how user experiences are designed. They are helping developers predict user behavior and offer them critical insights on how to fine tune user experiences in the future.

AI allows the automation of functions, increases accuracy, and delivers measurable advantages.

Wondering how AI can help you develop a more user-focused application?

Well, look no further. Crafted has a fairly robust understanding of AI-based user experience design works. Follow us for more information.

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Application of AI in App User Experiences

One way in which AI is boosting the user experience is via complex data analysis. Up until now, UX teams have relied on tools and methods such as usability testing, usage data, and heat maps to boost user engagement. However, AI is changing it all because it can do more with the same data.

With AI, apps can track user behavior across devices and use the information to synthesize suggestions that allow the user to improve their experience. For instance, e-commerce apps can tell shoppers how to improve their shopping experience. AI can even personalize the experience for each individual user based on the data collected.

Deep learning plays a major role here. It brings together a large amount of data to develop inferences. These systems also learn from the data and alter their behavior in accordance with the insights gained. As a result, developers who leverage AI are more likely to create memorable user experiences at a faster rate.

Apart from data analysis, AI also improves user experience via a deeper human connection. Thanks to the ability of AI to analyze data, it can help apps establish deeper connections with their human users. And we’re already seeing this happen.

For instance, let’s take the example of Apple’s Siri or Amazon’s Alexa. Both solutions have proven their worth over time. Today, many users rely on these digital personal assistants to carry out a wide range of tasks. This can include everything from booking tickets for a show to finding the latest vegan recipes.

These applications can even use the collected to data to make predictions, which lead to accurate suggestions.

Using these applications on a daily basis causes the user to develop an interdependent relationship with them. That’s the final objective. The user uses the app and the AI collects data, learns from it, and offers useful suggestions.

As it gathers more and more data, it becomes more and accurate with its predictions, solutions, and suggestions. This way, the user and the app become deeply connected.

Finally, AI allows the user to have greater control over things. There seems to be a misconception that AI influences user behavior. This is complete nonsense. AI, in actuality, compliments the user’s habits and is designed to deliver better user experiences. It understands the user’s preferences and provides solutions along those lines. Businesses have been doing exactly this for decades, although manually.

So the truth is that the user actually gains more control over their device. Every time the user executes an action, they allow the app to design an experience that removes previous challenges. In other words, the user is unwittingly teaching the AI.

This means users will begin to trust AI-based apps more than standard applications.

The purpose of user experience design is to show the user how the application works. This mean that the developer is trying to show the user just how the application functions and benefits them. Back in the day, this was achieved by following certain standardized rules.

However, with AI, there are no more standardized rules. User experience design is focused on analyzing complex data and then following a set of rules.

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