How to Use AI to Design Memorable Mobile App User Experience?

How to Use AI to Design Memorable Mobile App User Experience?

In recent years, artificial intelligence (AI) has been gaining an incredible response across multiple digital mediums. Will ai in design be able to do what AI does to other several industry vertices?

It makes perfect sense to integrate AI in situations and cases that include massive data. It doesn’t matter whether it’s conversational chatbots, data analytics, or so on, this technology is useful for a variety of purposes given its flexibility and convenience. 

Introduction:

Ai in design, in all different forms, is entirely based on human discretion and driven by significantly keeping the human part of the process at a higher scale than the analytical and data-driven side. 

How does AI enhance the mobile app user experience? Can you really improve the experience of end-users using ai in design? Also, the big concern is how can a developer implement artificial intelligence to improve the user journey?

These are a few major questions we will answer over the next few sections. Keep scrolling!

Related Reading – List of Top Mobile App Development Trends of 2021 & years beyond.

It is not really possible for machines to fully take over designers part, there are many ways the design community can use AI to take along user experience together in their journey of designing interesting mobile apps, like –

  • Sorting time-taking manual tasks like image resizing automated
  • Making designs localized using the AI-based translation
  • Invite system consistency between users and products
  • Provides insights into which elements are users interacting with & gaining more attention

This contribution of the designing industry is witnessing coming in from the AI-driven UI domain is something that is gaining ultimate popularity in the present industry while paving the way across the globe where AI and the future of design are linked predominantly. 

Principles that Align Mobile App Design with Machine Learning:

1. Develop a Shared Language

Major factors like user experience review, product vision, and business goals are required to be deeply understood and shared by the whole team. 

One will be able to create a memorable and truly intelligent user experience if the app design and machine learning development methods are co-linked efficiently. 

These must complement each other through shared concepts and common language and must come together with an aim to set a blueprint guiding the team’s productive planning with users’ reality. 

2. Focus on Use Case

As per the top software developers, the most important consideration while developing a consumer-facing app is not the technology that backs it but the objective and the user experience you plan to achieve. 

And so, it is crucial that you crystallize the use case. By doing so, you can then put your convoluted attention on the user flow that will allow you to identify the major points where machine learning can be integrated to improve the design ai experience.

A clear understanding of the use case also facilitates the development team to determine the right KPI to create the user experience program, which in turn is aligned with machine learning metrics.

3. Mix Quantitative and Qualitative Data

For a true understanding of ai in building design, it is essential that both qualitative and quantitative data are taken into account. You must make optimal use of qualitative research methods like questionnaires, interviews, etc to determine how the users are experiencing your app.

But why are we emphasizing so much on the combination of qualitative and quantitative data? 

The reason is that while designing an app, there is a possibility that you will witness sudden factors impacting machine learning development and user experience. 

These may include the effectiveness of feedback loop, Datapoint capturing user behavior and intentions, which are the main elements of ai in design that can be answered only after a deep consideration of both data types. 

4. Bring Your Combined Data to Real-Life Setting

Now it’s time to make sure that how ai UX design can develop a comprehensible user experience. Probably by setting up an end-to-end solution that shows how AI and user experience complement each other in the real world. 

An MVP methodology (Minimum Viable Product) that contains the working data pipeline along with the machine learning models for product development makes it simpler to iterate the ai in product design.

 It also supports the team to attain direct feedback from the users for a better understanding of the challenges related to the product. 

When both designers and AI experts share an understanding of product design issues, iteration is a productive choice!

5. Be Transparent About Collecting Data

Ai in design needs constant efforts to be absolutely on the mark, it is crucial that you spare extra attention to the data you have collected. You should consider the end-user side in this cycle of data collection – data conversion into information – iterating design. 

Notify users that their data is being used to feed the AI and allow them to alter the collected data in a way that the best results come through. Moreover, you should also give them the option to change what the AI learns – to ensure that the predictions are what the users want. 

While the above guiding principles help in ensuring transparency into how the combined AI and UX design should function, let us take a close look into some popular ai design tools that are backed by the developer’s community to offer a better mobile app user experience.

Related Reading – Also Learn How AI is Transforming the Landscape of Mobile App Development World

Popular AI Design Tools:

Popular AI Design Tools

1. Tailor Brands 

The Tailor Brands logo maker is a well-known product that businesses use for cost-friendly professional logos. The AI designs are based on the inputs entered in form of information that would be used in the logo design. 

2. Adobe Photoshop

Photoshop offers the selected functionality that makes use of ai in design for recalling the shape, and then shifting, altering, and editing them with many conveniences. 

Adobe Photoshop is a tool that works on an internal AI system (called Sensei) that facilitates changing backgrounds by acknowledging the various subjects in the image.

3. Prisma and Deepart

These are the two popular ai design tools to identify the various aspects of videos or images and edit them in a style of your choosing. These tools offer exciting filters and colors to work around. 

4. Lets Enhance

One of the major challenges in the designing industry is poor-quality images. 

Let’s enhance, powered by AI, is a powerful tool that enhances the image quality using three filters – Anti-JPEF, Boring, and Magic

‘Anti-JPEF’ filter converts the image to a high-resolution PNG whereas the ‘Boring’ filter levels up the image to around 4 times without compromising the photo quality. Magic is the third filter that allows you to add detailing inside the photo.

Ai in design or say aligning Artificial Intelligence into the process of App Designing is something that needs to be focused on with extra caution to ensure that UX & UI is intact. This ain’t that easy though!

If you are on your way to making your designs better and smarter, we have a list of some UI patterns that would help you kick start a smart journey:

UI Patterns that add human-friendly AI to your App:

A. Criteria Sliders

Numerous apps use machine learning algorithms to predict results or share recommendations. A criteria slider helps users adjust and then fine-tune recommendations that are based on the criteria they find meaningful. 

B. Like and Dislike Button

The like and dislike button is used for the betterment of the user experience that someone shares inside the mobile app. 

With a simple like and dislike button, you give options to users to not just focus on the recommendation system but also provide real-time feedback on what they don’t like and why.

C. Confidence Inducing Tips

Maximum times users are not well aware of the whole prediction and how AI works. 

When the users are asked to give input or answer questions in return for something – better-matched items choice, next show to follow option, etc. The confidence quotient rises when the users are given great results and options to approve/disapprove as per their choice. 

Doing this automatically instills confidence in the app making.

D. Give them an In and Out Option

Not every user is willing to feed in data for you in the artificially intelligent system or even want to take the smart move. 

So, another tip is to give them the option to opt-in and out of the smart options as and when suitable for them. This would probably fetch a more positive outlook towards the app in the future. 

This is the only way to take care of your business goal: taking care of the users.

Bottom line:

No wonder, Artificial intelligence is one of the hottest trends of the last couple of years that has amazed everyone with its magic. If used the right way, it can improve the overall user experience of your app and reach great heights. 

AI will never stop being in demand. That is why it is important to imply the best AI-driven strategies that’ll not only drive growth but also bring value to the user with more interactive apps entering the market. 

As we are now at the conclusion section, we hope you duly understand how AI affects the mobile app user experience. 

We have understood the various ways ai in design is affecting the app design industry, the guiding principles of aligning mobile app design with AI, ai design tools used by businesses, and the UI patterns that you should consider to make your users familiar with AI. 

Now there is only one last thing you need to do, which is you need to touch base with ai development company to make AI an active part of your mobile app design process. 

Mobcoder has a team of UI/UX designers who can help you with artificial intelligence development services with unparalleled functionality and flexibility to adapt to the ever-changing market dynamics. 

Define, Train, Integrate AI Solutions to meet customer demands today!

Have a project in mind?