AI and UX are two key trends that are redefining the digital world.
Although they are used for different purposes, the aim of both entities is the same—to enhance user experience. Both are driven by predictive analytics.
Whereas UX enhances the user experience of a virtual product, such as web design, AI can execute tasks mainly associated with human intelligence, like decision making, visual perception, translating languages and speech recognition.
What if AI is used in UX? The outcome will be amazing. Isn’t it?
For example, Netflix uses certain algorithms to create graphics, such as click-through thumbnails or movie posters for multi-devices. The online streaming giant has used thousands of video frames from an existing movie or show as a starting point for thumbnail creation. It annotates and ranks these images according to their highest likelihood of resulting in your click.
For example, people are more likely to click on a thumbnail with specific visual elements or characteristics of that genre or an image of their favorite actor.
Netflix might show you the flick Stranger Things in various thumbnails, from a huge gothic font, close up of individual actors, and mysterious scenes.
All these metrics are based on what other similar users have clicked on. It makes a recommendation of TV shows and movies based on the user’s history of watching.
One of the easiest ways to deploy an AI on your webpage design is a chatbot. It answers simple questions, arranges schedules and book meetings.
However, the combination of AI and UX hasn’t become that mainstream norm yet.
Because of the different industries these two things have, it’s usual to see UX designers and AI experts work in their separate zone even though they are working for enhancing user experience. After all, experts from both fields are not acquainted with each other tools and methods, making them unable to learn what can be achieved by combining AI with UX.
How Can AI Improve UX Design?
- AI can track user experience with web design. For example, it can process info about site visitors, then applies or shows changes to the model to optimize it for future use.
- Machine learning is useful to analyze various UX factors, such as device users, location of users, session time, session length, pages visited, bounce rates and exit pages. This way, these key metrics give a clear picture of user behavior with your design.
- AI can also eliminate bias in testing or any subjective approaches to A/B testing. And it’s important to report impartial views on split testing. AI can play an important role here as it is based on cold hard data.
- AI systems can also test multiple design variations and then produce alternatives. This can be useful in many stages of UX design, such as developing buttons on a webpage, or images in a mobile app.
How to Combine AI with UX
The vision of the product, concerns, and goals are required to be shared and understood by both teams. Therefore, a common language is required so that they can share their concepts.
UX designers and AI experts should team up to develop a common product blueprint that covers both interfaces and data pipelines. This co-created blueprint will be the foundation of product planning and decisions. Both experts have to work in the same space side-by-side.
Secondly, there is a need to focus on the user experience and business goal you are looking to achieve. For example, if you are developing a news app, the user experience designers and machine learning experts should together create and design the actual use flow of the app. This lets the whole team identify the key points where AI could improve user experience and vice versa. Solid designs, including suggestions from data engineers, data scientists, and designers can help set realistic expectations and goals for the iteration of the product.
The next step is to combine qualitative and quantitative data. To determine the effects of the partnership of UX design and machine learning, both qualitative and quantitative data are essential. Qualitative research can include questionnaires, user testing, and user interviews to determine the user experience with your product. Qualitative data helps determine how users think and feel and quantitative data shows how people behave with the product.
AI is the right partner for UX as it enhances the basic norm of the latter—to improve user experience. It is all about making the design simpler, easier and convenient.
Again, AI and UX are two worlds apart with different methodologies, environments, skill sets and tools. So, as I have told you earlier, common language, co-created blueprint and data is required to make the perfect combination of AI and UX.