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.
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.
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.