User expectations for digital experiences are only getting higher. According to HubSpot, if a website doesn’t load within three seconds, 40% of customers will usually leave. This makes the demand for efficient, high-quality websites imperative.
Not to mention, having a clear hierarchy (order) of webpage headlines on the navigation bar of your website is essential for creating an intuitive user experience.
Here at Psycray, we are a thoughtful, responsible user of AI-driven UX technologies.
For instance, we helped SquareStack improve its user experience by adding an app tracker and app$ tracker dashboard to its site. This helped users navigate the site more easily.
In this blog post, we’ll explain how AI can enhance the user experience by optimizing personalization, accessibility, website performance, and decision-making.
I. What AI Means in the Context of Website UX
For UX audiences, AI involves using machine learning to learn effective website prototypes for top-notch design, natural language processing to distinguish effective copy from poor copy, predictive analytics to learn user preferences, and automation to generate common website elements, such as buttons and CTAs.
While traditional UX optimization involves humans sifting through data and discovering through trial and error what works and what doesn’t, AI can learn the data on its own and generate relevant solutions that correlate with user findings.
Some simple examples of AI-powered UX features include a mock navigation bar, a sample CTA button, or sample product copy.
As we discuss AI’s UX capabilities further, keep in mind that the goal is to augment UX rather than replace it: AI is meant to help designers and product teams do their job better, not take over their human creativity and insight.
II. Personalization at Scale With AI
Personalization is central to modern UX because customers want to feel seen and valued. By prioritizing users’ desires in your navigation bars, web pages, and offers, you can create a UX design that is tailored to the exact products or services your customers are looking for.
While you can personalize UX through “if-then” programs (if the customer clicks the button, they get a thank you email), rule-based programs have limitations. They can’t respond to feedback in real-time, and they may not apply to all user actions.
AI, on the other hand, can respond to real-time feedback. It can provide content recommendations as users read your blog posts, for example. It can also adapt layouts and navigation according to the user’s device needs. Lastly, it can provide personalized CTAs and messaging.
AI can do all of this through behavioral data, intent signals, and contextual data. In return, you’ll likely see increased engagement, along with longer user sessions on your site and higher conversion rates. These signals of increased engagement are positive signs of a satisfying user experience.
It’s important to note that while these tools can be fantastic for reading and responding to your customers, you should be transparent any time you use AI to collect user data. This will help your audience feel more comfortable sharing their data with you.
III. AI-Powered Navigation and Information Discovery
AI can also solve many of the most common challenges UX designers face today. From cluttered menus to cognitive overload, businesses often have more information than users can comfortably absorb, unless that information is properly formatted into distinct, clear webpages.
Thankfully, AI can improve the user’s search experience. Semantic search can glean the contextual meaning of users’ queries. Predictive search suggestions can recommend complete searches for the user as they type, while intent-aware results can use contextual cues to interpret the meaning of the user’s search and provide relevant answers.
For instance, we helped a manufacturing subsidiary refine their library of training videos to contain a search bar where new sales employees could ask questions about the video and receive timestamped answers instantly. This allowed sales employees to train more efficiently.
In addition, AI can offer intelligent navigation features such as smart search and personalized results. It can also produce actionable content as needed by taking data and turning it into practical insights that users can apply. Moreover, it can reduce website issues and improve source findability. Its ability to scour information and interpret it makes it incredibly resourceful. Improving the search experience in these ways benefits first-time and returning users alike.
IV. Conversational Interfaces and Real-Time Assistance
Evolving from static pages to conversational UX can create a more immersive experience for users.
For example, AI chatbots and virtual assistants can offer customers thoughtful responses based on their questions. They can also provide multilingual support and 24/7 availability, which is extremely helpful for short-staffed companies that may not have multilingual staff members or around-the-clock business hours.
Some common use cases of conversational UX include customer support, onboarding, and guided product discovery.
In customer support, conversational UX can answer common questions about product or service features, as well as order and pricing details.
In onboarding, conversational UX can guide the new employee training period. As an example, if a new member of an association wants to learn more about their industry, they can use the chatbot to ask questions about industry terminology and receive instant answers. This helps them learn faster.
In guided product discovery, shoppers can ask chatbots about what products they’re looking for, and the chatbots can provide specific answers about product offerings (likely faster than a human representative on the phone could).
However, it’s important to note that conversational AI should be trained to hand off more complex inquiries to human representatives. This way, customers can receive the exact support they need without the stress of trying to make a chatbot understand the situation.
V. Improving Accessibility and Inclusivity With AI
Accessibility is an essential UX and business requirement. With over 16% of the population having some form of disability, adding accessible enhancements is a crucial part of being inclusive of everyone.
Many enhancements exist to assist with people with auditory, visual, or physical impairments. For example, automated alt-text generation can provide captions of images for people who are blind. Also, voice navigation and speech-to-text features can read text aloud to people who are blind.
Real-time language translation can also assist with accessibility by allowing people who speak almost any language to understand a business’s message — this feature is especially important for international businesses that work with multilingual audiences.
AI can help teams identify accessibility gaps by reading documents and scanning for accessible elements, such as alt text, meta descriptions, and clear formatting, for easy speech-to-text and text-to-speech translation.
At Psycray, we include alt text for images and meta descriptions on every single one of our blog posts. This helps us create accessible content for our audience so that anyone who needs alt text can understand our posts. In addition, adding alt text and meta descriptions improves our SEO performance, which helps us rank higher on Google’s search engine and, in turn, reach more people.
When working on accessibility initiatives, it’s important to balance AI automation with human oversight. AI can assist with many components of accessibility, but it can’t catch every error. Therefore, human quality assurance is imperative for creating content that will make sense to human readers.
In addition, AI can make mistakes, such as including unfair biases about people in their responses. So, companies should also vet AI-generated content for equity and fairness to ensure that all forms of company communication treat people with the respect they deserve.
VI. AI-Driven Performance Optimization and UX Testing
Performance is foundational to UX because, as mentioned previously, people will exit a website fairly quickly if it doesn’t load properly or if they can’t figure out how to navigate it.
To ensure optimal performance, AI can offer load-time optimization, predictive caching, and adaptive content delivery.
To conduct UX testing, use AI to automate A/B testing, predict user behavior modeling, and perform heatmap and session analysis. This can help you understand which website elements are improving performance and which aren’t, as well as which webpages are popular (and for how long they are popular). This information is invaluable for determining which pages users are most interested in, as well as which pages may need improvement.
AI enables faster iteration cycles and data-informed UX decisions by allowing a platform to enter data, test it, and refine prompts as needed. Essentially, you can use AI to “fail faster” until you get the results just right, making it a wonderful tool for experimentation and refinement.
VII. AI UX Ethical Considerations
With all of the advantages of AI in UX being discussed, it’s important to note that poorly implemented AI UX can have serious consequences. These include bias, over-personalization of messages, and privacy concerns.
To combat these potential consequences, each member of your company should be able to explain how the AI works so that they can catch mistakes early. Companies should also be transparent about how and why they use AI with their customers and leads. They should let them know which data AI will collect, how long it will be kept, and where it will go. This will help your audience feel more confident in your business.
Furthermore, users must consent to having their information collected and used by AI, and companies should put data governance systems in place. In context, this can look like providing leads with a survey, asking them permission to collect their data using AI, and establishing written data governance procedures for the company.
By taking data privacy seriously, you can create AI experiences that foster trust. In turn, your responsible use of AI can become a competitive advantage; when used properly, you not only show that you can produce more efficient results, but you also showcase your ability to maintain high ethical standards while using a technology that’s still in its early stages of adoption and effective use.
VIII. Conclusion: Building Better Digital Experiences With AI
In conclusion, AI can enhance UX across personalization, accessibility, navigation, and performance. By testing website elements, experimenting thoroughly, and following ethical policies, you can create a user experience that is safe, efficient, and enjoyable.
Remember: AI is most effective when companies adhere to ethical guidelines. When using AI to build UX, keep a long-term perspective in mind. View it as an opportunity to continuously learn and grow your AI skills, not just a one-off solution.