Improve user experience with machine learning
Machine learning is actively used in business, reducing financial investments and improving user experience. Its techniques can be applied to any application, from the e-commerce niche to healthcare and education. As such, this technology can be implemented in a variety of industries and has tremendous potential to deliver truly impressive results in terms of marketing and sales.
Benefits of using machine learning to
improve user experience
Examples of implementing machine learning to improve user experience
Customer support via chatbots
Digital assistants (chatbots) use machine learning to provide advanced support. The use of chatbots depends on the specifics of the application. In addition to the obvious customer support, chatbots can help generate leads and make appointments for customers, announce new products and discounts.
New products and services
A new product such as voice search powered by machine learning has become a part of the daily life of many users. Voice assistants help brands to hyper-personalize sentences, and voice analytics allows them to find new solutions to improve UX design and user support.
Website design and UX optimization
Machine learning can help marketers optimize their website designs. It is also used to conduct A/B testing and improve user experience.
User experience (UX) is what the user feels when they connect to, for example, a website, program, application, or gadget. UX is an extremely important metric that many people underestimate. With the rapid advancement of machine learning technology, companies are emerging with new methods to improve UX.
Machine learning uses artificial intelligence technologies to form a system that can automatically learn and perform specific tasks. The combination of machine learning and UX opens up new possibilities for developers and clients. It can be used to perform routine tasks such as resizing images, applying shadows, and even writing code. Intelligent programming created with the simulator allows you to see how a client interacts with a particular program and to hypothesize which capabilities are effective, which mode of action is most widely used, and which key points need to be revised.
Machine learning can be used to gather information about a customer on the Internet, analyze it, and deliver exactly the solutions the customer was looking for. Machine learning allows you to create a system for analyzing reactions to various components of a brand site, elements and content promotion.
Machine learning contributes to the creation of unique customer experiences that will help build loyalty, increase sales and increase customer lifetime value. For example, in an e-commerce application using machine learning, you can suggest new products based on the history of previous purchases and items in the commodity bundle, and in an online cinema, you can recommend movies and TV shows that are more likely to appeal to the user, since these recommendations will be based on the movies watched.
Personalization is also possible in another context – e-mail newsletters, advertising placements. Machine learning helps you create personalized newsletters to increase engagement, segment your audience, and collect data. Mail services also offer to determine the optimal time to send letters, improve the reputation of the sender's domain, and provide other opportunities based on machine learning.
Machine learning can be used successfully in UX configuration. Improvements will make the work of planners much more skilled and the client experience will be personalized. Looking at even a small part of the benefits that machine learning provides, we can safely say that it is already beginning to change UX.