With the rapidly changing face of technology, AI has indeed reshaped the digital world. AI has created a positive impact on diverse sectors like finance, healthcare, retail, and more. UX is no exception! But before we delve into how AI and ML are improving UX, let’s have a look at what exactly does UX mean.
What is UX?
User Experience (UX) encompasses all the aspects of the end user’s interaction with the company, its services, products, and overall customer journey. The most crucial requirement for a great UX is meeting the exact customer needs and understanding their behavioral patterns.
With advancing technology, companies are offering more and more services to customers. Moreover, the increasing number of services creates the challenge of maintaining a simple yet elegant design. It is a widely known fact that elegant design with minimal animations and a dash of the perfect color palette makes the ideal recipe for a great UX.
Importance of UX Design
UX has a great impact on how your brand stands out amongst the others, how influential it is, and how you can grow your revenue by honing UX design.
The Term UX has often been interchangeably used with User Interface Design and Usability, but in reality, they both are two separate components.
UX design is a process that inculcates the entire process of acquiring and integrating the product with functionalities like use, functionality, product design, and even branding.
A UX designer is not just concerned with just User interface and Usability but also will have to amalgamate all the processes involved in attaining and assimilating the product. The process of UX starts right from the conception of the product idea and goes on until the user experiences the product. The success of the UX experience goes a long way in assuring the success of the product.
A true user experience (UX) goes far beyond the design and aids customers with additional features that help develop a feasible, viable, and suitable decision about products/services offered by companies.
The latest example of enhanced UX experience could be automated chatbots which help users understand the products/services better and help them throughout their customer journey; right from browsing through selecting items to finally paying for one.
How do AI and Machine Learning Improve UX?
The use of machine learning and AI has made it easy for data to be segregated easily based on demographics, behaviors, patterns, and several other aspects.
The basic idea is to ensure that every user gets an experience based on their behavior that is derived from their previous user history. In this manner, every aspect of human behavior that is fed and sought via these programs is then fed into algorithms, which in turn generates useful patterns.
With the help of an interface, these patterns are then communicated, and later on, get converted into applicable features and services that help companies in enriching their user experience.
Here are some of the benefits of AI and ML in UX:
1. If your algorithms are good and intelligent enough, then the information can be processed about site users/visitors, which will in turn help in keeping the data for future use.
2. The existing models can be changed as per this data so that the information can be used optimally. The algorithm can be changed following the information, and the existing models can be fine-tuned time again to make optimum use of the data.
3. Artificial intelligence professionals can continually use machine-based learning system to keep in sync with various metrics like the location of users, bounce rates, exit pages, and more. In this sense, AI has proved to be a powerful platform to conduct different types of tests.
4. If these metrics are used, it will give the analysts a clear-cut platform to determine the needs and behavior of the users. This data can be used in predicting and taking risks when it comes to running new ideas or bringing about new developments in the products.
5. When deep learning technology can be paired with large sets of data, AI goes a long way in improving UX because AI helps in analyzing thousands of variations in designs and give us alternatives that can be applied in the system.
6. If one suffers from the issue of a biased approach to A/B testing, then this is where AI improves the performance of UX. AI does not indulge in impartiality white running tests. It relies completely on the binary approach that reflects on the actual results.
ML and AI completely rejuvenate UX from a general sense of user information to more specific information by giving a lot of suggestions that can be applied by marketers and advertisers.
ML gears the programmer and the developer to sift piles of data and present relevant information, which will be used by the marketer to create magical products. With the data that is sought as a result of these processes, the companies anticipate needs and accordingly come up with product ideas.
Of course, the data is to a great extent considered reliable, but before launching the product or the service, to ensure that it is the best match for user delight, the company also ensures to take opinions and surveys so that it reconfirms the suggestion made by AI and ML.
Challenges in Implementation of AI and ML in UX
Both AI and ML are highly compatible and friendly with UX; they all share similar principles and goals. But there is more to their actual implementation; designers need to understand the know-how to implement AI and ML in UX.
The product design team needs to break the silos and start with the process based on a few principles as listed below:
1. First, it is important to create a common language, and for this to happen, it is essential to first put across the business goal and the required user experience.If you want to enhance the UX and offer a great customer journey, create a product outing, then all AI with machine learning methods with UX should work in the same language and share the same concepts. AI technical experts and UX designers should interact on a common platform and develop a blueprint that will be tantamount to a great UX experience.
2. These days technology has enabled easy storage of data; even storing historical data has become extremely efficient and feasible. So if the intersection of AI and machine learning with UX happens, the combination of qualitative and quantitative data is essential. Qualitative data can be collected with the help of open-ended methods like questionnaires, user interviews, and testing that will enable the users to highlight features of the product.
3. However, quantitative data, on the other hand, will talk about how the product is used. Hence, with the availability of these types of data, the user experience requirement can be gauged to a great extent, and predictive analysis results are accurate. If the product is highly user-intensive and focuses on the consumer in totality, then the use of technology alone is not enough.
Future of AI and ML in UX
Consumers today are experiencing utter consumer delight, and we can easily guess that it is AI and ML that are doing the trick and refining user experience. According to research by IDC, businesses that harness the power of advanced technology such as AI and ML and leverage predictive analysis are expected to increase their success rate by 65% as compared to those that rely on conventional technologies.
The growth of AI and ML in the UX space is undoubtedly on the cards because every company that has the resources to use data to their benefit will not leave any loose ends to remain abreast of the competitive industry and market space.
Auto-correction and Apple maps suggestions are just the tip of the iceberg, and there is a whole treasure that is hidden which can be explored using AI. Smart home assistants like Alexa are in an ever-evolving stage and are set to become more and more useful with better performance related to voice applications especially.
No other technology can enhance UX the way AI does, and that is a fact. AI has eased out everything not just for companies but also for consumers. In any case, it is a win-win situation for both customers and companies. With more and more people willing to engage themselves and their understanding of the usability of AI & ML in the UX space, it sure has a bright future.
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