5 Ways AI can Enhance User Experience
Making a mark with impactful user experiences has become an extremely critical aspect of any kind of service offering. Organizations are now trying to improve user experiences with the help of machine learning and artificial intelligence, which have shown immense potential in transforming the customer experience.
The evolution of artificial intelligence and machine learning use cases have not only impacted the end consumers but raised the bar on experiences and under-the-hood efficiency. User experience, which pivots on both, is one area where AI and ML can offer the necessary edge to products and services.
Why is a Good User Experience Important?
In this customer-centric landscape, a good user experience helps project your brand values, which in turn, builds brand loyalty. Carefully curated customer experiences drive noticeably higher engagement and brand recall with the customers. Your service or product may boast of several advanced features; however, your user experience seals the deal for customer loyalty and product/service success.
Role of AI in Design
A study by Pfeiffer revealed that 50% of creative professionals are keen to understand and explore AI and ML while 62% believe artificial intelligence and machine learning will be very important to their creative roles. 74% of survey respondents shared that more than half of their working time is spent on repetitive and uncreative tasks. This is important to note because this is where AI and ML can help. These technologies will thus have an impact, not only on creativity but also on productivity. That being said, creative vision will always need a human touch.
5 Ways in Which AI is Transforming UX Design and User Experience
- Decoding the Customer
Design teams rely on customer data (also referred to as training data), which lends them an understanding of customer needs. This data helps them come up with suitable designs.
By unearthing existing patterns and creating new ones, AI can help design teams get deeper insights into user behavior. AI and ML-based analytics systems are able to source data from websites, apps, and other digital services seamlessly and look for patterns. They also help bring all this data in a form that can be used and consumed meaningfully by the designers. The resulting design is therefore far more superior as compared to one based on basic customer research.
- Hyper-Personalized Customer Experience
Besides identifying patterns and user types AI-based platforms can recommend personalized workflows tailored to each user. While non-AI-based data analytics does identify broad patterns, AI systems can dig deeper and provide insights for several more use cases and scenarios. This is when user experience becomes hyper-personalized.
Ever wondered how Netflix provides the most accurate movie and series recommendations? Not just recommendations, it personalizes the images that go on the program banner of each title to user preferences. This beautiful bit of forethought is a result of Netflix’s AI engine based on user engagement tracking data. Google translate is another example. Several personal finance apps are also creating innovative ways of personalization. Such hyper-personalized experiences go a long way in driving user conversion and retention.
- Offering Few but Most Suitable Options to the Users
Simplicity is one of the most important tenets of user experience. If the user has to expend efforts on “decoding” the interface, it indicates a bad customer experience. While most products and services will need the user to choose alternative paths and options, too many options make it harder for the users. Your product may have a hundred cool features, but they will only bog down your individual user if he or she has to navigate through all of it.
This is where AI and ML help. These technologies help narrow down these options based on the demographics and past experiences of the user and present the most likely options to them. Decision-making is thus faster, better, and hassle-free for the end-user.
- Testing Multiple Prototypes of Design
AI and ML make the A/B testing of products as easy as pushing a few buttons. From converting freehand sketches to wireframes, and wireframes to code, designers can test out several design prototypes over multiple devices at a much faster speed with the help of Artificial intelligence and machine learning algorithms.
These systems can even suggest design changes based on sentiment analysis and retroactive analysis on the training data that is fed to them.
Identifying and handling edge cases is also greatly simplified thanks to AI.
By enabling design teams to test out multiple design prototypes, AI assures the best user experience your product can offer.
- Making User Experience More Interactive
Apart from working behind the scenes, Artificial Intelligence is also being utilized in a big way to make the user experience more interactive. Conversational AI, i.e. chatbots and virtual assistants are commonplace now. Similarly, new services and products have been launched that use computer vision, augmented reality, natural language processing, text recognition, speech-to-text conversion, drones, and robots. All these solutions are powered by artificial intelligence and machine learning and come under applications of AI. The user experience will benefit from an empathetic context that can be built into the UX design with the help of such innovative AI solutions.
Thanks to AI, we can finally have products that suggest design changes and optimize themselves. From speeding the design process, especially the testing and analysis of a vast amount of data intelligently, AI greatly simplifies and improves the UX design process. The relationship between the consumers and the brand can thus strengthen significantly due to the possibilities that AI and ML bring to the table.
If you are looking to offer impactful user experiences using AI, get in touch with our AI experts today.