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UX for AI: 10 Tips for Perfecting AI Product Metrics

UX for AI: 10 Tips for Perfecting AI Product Metrics

Product design
8 min read
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Did you know that today, 35% of businesses use AI, and 90% of leading enterprises invest in AI technologies? But we at Arounda noticed (as UX/UI experts) that many companies focus mostly on technical aspects and forget about the human factor. The true measure of an AI product's impact depends on its power to connect with users, solve their problems, and integrate perfectly into their lives or work environments. Here is where UX for AI becomes a game changer. We have created 170+ successful projects and have much to share with you to influence the results of your product. 

In this article: 

  • Learn about the importance of well-designed UI/UX for AI products.
  • Discover strategies to influence the results of AI products through UX design.
  • Take a look at our Arounda ideas and tips on how to create a powerful UX for AI. 

Why UX is Crucial for AI Product Success

When developing AI products, the biggest accent is on machine learning models, data pipelines, automation capabilities, etc. But if people don't understand what to do and how to use these features, they get frustrated and quit. As a result, you'll get a high churn rate, right? That's why UX is crucial for success. 

We want to show you the main benefits of UX design for AI products: 

  1. It simplifies complex AI products with intuitive interfaces, clear visualizations, and thoughtful interactions. 
  2. Sometimes, artificial intelligence systems can be very complicated for users. A well-designed UX provides transparency in decision-making and data usage.
  3. UX design demonstrates functionality in a pleasant and understandable way to attract and retain users.
  4. Good UX design clearly shows the value and makes sure that the product is functional and meets the user's needs. 

The Role of User Interface in AI Products

Imagine you have a recipe for a complicated dish. It tells you how to cook, but how you present the dish will differentiate it from the competition. You can serve the same meal simply and unattractively or like a 3-star Michelin restaurant. This is what the UI does, turning a technically complex product into a fantastic tool that users admire. With a well-designed UI, you can add real value to your product and increase engagement. Arounda experts highlight the following key aspects of UI design for AI products.

Usability

A user-friendly interface allows people to achieve their goals efficiently and enjoyably and speaks the user's language. This is the basis of UI design. For example, Google Analytics (Google's AI tool) has very complex data processes running in the background. But thanks to a great UI, it presents information in an easy-to-understand format: clear graphs, easy navigation, and concise summaries.

An excellent feature for improving usability is a guided onboarding process that includes step-by-step interactive tutorials, gamification, videos, etc. If you are interested in creating the perfect user onboarding, welcome to our course.

Familiarity

UI familiarity means using common patterns and design elements that users already know. Reduce cognitive load and make the transition to new AI technologies without problems! You can use familiar icons, layouts, and navigation patterns, such as prominent search, to make your AI product intuitive. Users won't spend time learning new UI paradigms because they want to focus on the AI functionality. Keep in mind that 94% of first impressions of a product's UI are related to design.

Accessibility

Your AI product should be accessible to everyone, regardless of their abilities or disabilities. This is an accessible design! 

Did you know that more than 1 billion people in the world have some form of disability (according to the World Health Organization)? That's why digital businesses must meet specific accessibility standards. For example, the European Accessibility Act emphasizes that all digital companies must have accessible interfaces by 2025; otherwise, there will be legal and financial consequences. And while this is a barrier for some companies, it is a new market opportunity for others.

Branding

Your product's UI is a powerful expression of your brand identity. Each element (color palette, logos, typography, etc.) should match your brand values and message. Customizable UI elements create a consistent and recognizable UX and reflect a reputation for reliability. To show you an example, our Arounda team has branded a fintech project Klasha. Welcome to our case study to see how we did it!

Retention

Retention is another reason to invest in UI design. Bain & Company researched that a 5% increase in customer retention can boost profits by 25% to 95%. A well-designed UI attracts users, keeps them loyal, and fosters long-term engagement. 

How to increase retention? We recommend using gamification elements (progress tracking, badges, or rewards). But the main accent is personalization! For example, Spotify uses AI to create personalized playlists and suggestions. The app has a flawless UI design that is visually very engaging. 

For a better user understanding, we offer to talk about the evolution of human interaction. Ready?

Evolution of Human Interaction

The relationship between humans and technology has evolved significantly. The focus has shifted from functionality to user experience. 

Initially, the CLI provided interaction through text commands. It required specialized knowledge. Then, a GUI made the technology more accessible to the general public so that non-experts could navigate complex systems. Today, the development of AI makes this interaction more dynamic, personalized, and context-aware. 

AI can predict user needs, adapt to individual preferences, and learn from each cooperation. However, only thoughtful UX design for AI can realize this potential. The challenge is to make AI products natural, intuitive, and even human. At Arounda, we take the following principles in mind:

  • Voice interfaces and natural language processing (like Siri, Alexa, and Google Assistant).
  • Context-aware systems (e.g., a smart home system that can learn the user's daily routine and adjust the environment accordingly).
  • Emotional AI (systems that can detect and respond to human emotions, facial expressions, or voice tone).
  • Adaptive interfaces (personalized content, offers, and even changing the layout or functionality based on user preferences).
  • Data-driven UX (analyzing user behavior to make informed design decisions, optimize user flows, and identify real-time pain points).

The simplest tip nowadays is to do everything with the user in mind!

Adapting UX to New User Behaviors

UX for AI products requires a deep understanding of user behavior. Our experts have researched how UX design adapts to changes and have used this information in our work, and now we want to share it with you. 

  1. Users expect AI to understand their preferences, predict actions, and offer relevant suggestions without explicit instructions. 

What to do? Focus on creating personalized and intelligent experiences. For example, at Arounda we include predictive text, smart search, customized dashboards, etc.

  1. Users want to know how AI uses their data. 

What to do? Everything should be transparent and clear! People need to understand how AI decisions are made. This can include clear explanations, data management tools, and the ability to customize AI behavior. 

  1. Users want to have a seamless multimodal experience.

What to do? Create interfaces consistent with different input methods (voice, text, touch, and even gestures) and provide a smooth transition between them.

  1. Users often don't know how to use new AI features or find existing training methods difficult to understand.

What to do? Create interactive tutorials, tips, gamified instruction, and just-in-time learning prompts. Our designers always make learning a natural part of the user journey.

  1. Users prioritize ethical considerations.

What to do? Integrate features that promote the ethical use of AI (bias alerts, privacy controls, and consent mechanisms). You should design these tools as user-centered to help navigate complex ethical issues and reinforce a company's commitment to responsible AI development.

Which AI Product KPIs Can Design Improve?

Key performance indicators (KPIs) measure the success of an AI product and reflect its impact on users and businesses. Of course, AI technology, its features, and market demand play key roles, but UX can significantly influence these indicators. Here's a look at some of the key AI product KPIs that thoughtful design can improve.

  1. User engagement (time spent on the platform, frequency of interactions, or the number of features used per session).
  2. User retention (churn rate, monthly active users, or customer lifetime value).
  3. Conversion rates (signup conversion rate, free-to-paid conversion rate, or purchase rate).
  4. User satisfaction (net promoter score, customer satisfaction score, or star ratings in app stores).
  5. Efficiency and productivity (task completion time, error reduction, or output quality increase).
  6. Adoption and usage rates (daily active users, new user signups, or feature adoption rates).

Now we have the complete puzzle, and we are ready to answer the main question: "What UX strategies influence the results of your AI product?". Let's go!

Strategies to Impact AI Product Results Through UX Design

If you thought AI product development was just about coding, you were wrong. It's also about creating unique experiences that deeply engage with users to achieve powerful results. The following strategies will maximize your product's impact if you're working on UX for machine learning, UX for generative AI, or broader UX for AI.

Align the AI's Personality with User Expectations

Adapt the AI's communication style to the context and target audience. First, conduct thorough user research to create the right AI personality. Then, think about the style. For example, a friendly, conversational tone is ideal for generative AI. But the design of machine learning tools needs a more formal, professional tone. The main task is to know your users!

Design User-Centric Interfaces

We recommend designing a simple and clear UI/UX to help users navigate difficult functions without confusion. Remember that AI is a complex technology, and your task is to make it an intuitive tool. 

Learn more about how we craft a user-oriented design for AI products.  

Incorporate Personalization and Flexibility

Use AI power to personalize content, recommendations, and UI. For example, you can create customized content generators and templates. Users will love this because it saves them time and gives them a feeling of uniqueness. Offer flexibility in interaction modes (guided and manual modes) for people of different skill levels.

Facilitate Continuous User Feedback

Regular feedback loops help to identify problems early in the process, provide more targeted and effective updates, and guide ongoing improvements. Our team recommends integrating feedback mechanisms directly into the product. What works well: in-app surveys, feedback buttons, or user forums.

Implement Explainable AI (XAI) Principles

Create interfaces that clearly explain AI processes and solutions. Why? Because users want to understand how decisions are made, and XAI principles help build trust and confidence. For example, look at the financial and healthcare industries, where decisions can have significant consequences. UX should be well-thought-out with detailed explanations. Otherwise, it costs a lot of money or human lives.

Ensure High-Quality Data Collection

Nowadays, information is money. The data quality of AI systems directly affects the existence of your product. People use a lot of resources to check it. Therefore, design UX features that make it easier to collect accurate and relevant data. For example, user-friendly forms, clear instructions, and data validation. Users want to easily enter clean data and use tools to pre-process data. UX design here helps significantly increase the efficiency of AI.

Prioritize Ethical Design and Data Privacy

AI systems process increasing amounts of personal data. That's why ethical considerations and data privacy are very important. The UX for artificial intelligence products requires transparency and user control to ensure trust in creating personalized content. We recommend implementing clear privacy and consent controls in the UI. 

Use A/B Testing for UX Optimization

A/B testing optimizes UX design by comparing different versions of interface elements to see which performs better. Conduct A/B tests regularly on key UI elements, such as layout, color schemes, or button placements. From our experience, it really helps increase user interaction and satisfaction.

Measure UX Impact and Iterate

Even if you're doing great, don't forget to use analytics tools to collect information about how design shifts affect engagement, satisfaction, and other KPIs. After all, there is no constant user behavior, and everything can change. Regular improvements based on user feedback and performance data keep the product evolving to meet user needs.  

Handle Errors

No AI system is perfect, and errors will happen. How should the error handling process look to keep users' trust or frustrate them? 

Create clear error messages that help users solve problems, avoid technical jargon, and provide practical steps. The system should offer an easy way to fix or report the error and provide suggestions for troubleshooting or automatic corrections to recover quickly. Remember, the design must be well thought out!

Final Thoughts

It's no secret that artificial intelligence has become a friend to users and businesses. And its power will become stronger and stronger. Therefore, the success of AI products depends not only on the genius of algorithms but also on the quality of user experience. UX design for AI is a bridge that connects advanced technologies with people who use them. The main question is: how do you design this bridge? 

The strategies we've described in this article are important steps toward designing intuitive, engaging, and effective experiences. They help create interfaces that adapt to new user behaviors, are flexible enough to grow with user needs, and robust enough to handle the complexities of AI. 

We know that staying on top of design is challenging and time-consuming, so our Arounda team will be happy to be your caring partner and perfect the AI future together! Contact us to find out how our UX/UI design services can help push your product to success. 

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