Atualizado: 4 de jan.
Data is one of the most valuable assets of any organisation. Using data effectively can directly improve business results, and User Experience (UX) design can also make a difference.
UX methods that incorporate data-driven design has proven tangible results. UX design uses research data of various kinds to determine how to provide the best user experience. In fact, Forbes has described some key customer analytics, including customer satisfaction, lifetime value, segmentation, sales channels, web, social media and engagement. This data helps to understand targets, reveal information about customers’ pain points, discover trends and supports the data-driven design.
Designers usually have no background in statistics or information analysis. However, incorporating data into the design process means that they must use numbers and understand how analysis works, to be able to propose bold changes and use data to support their design suggestions.
Data can be the key to finding out how to solve a problem. While examing the data, we often see specific patterns appear, for example, people leaving a website on a particular page, bounce rates or time-on-page metrics.
On other hand, data visualisation is a graphical representation of information or data. People are more visual learners. Using data visualisation tools such as charts, graphs, timelines, and maps provide an accessible way for people to absorb visual information, understand trends and patterns in data. Good visual data can be more attractive to the audience, communicate a more clear message, and help companies to make pass or fail decisions.
UX in analytics applications is also very important. Users need to be confident that they have the right numbers in order to use them effectively in decision-making and business activities. One way to develop this trust and confidence is to ensure that they can see or easily access the context of the information provided. Having a context around data and insights will help to understand and trust the application more and use it confidently.
Another example of how user experience and data connect is customisable interfaces and self-service. Providing the same, consistent interface for different user groups can achieve smoother collaboration, because everyone has the same views, reports, metrics, etc., and it becomes easier to communicate about them. The intuitive interface can reduce or even eliminate the time required for user training to use the application. By reducing the number of tools/platforms/applications that users need to interact with, maximising integration also helps reduce overall training efforts, which further helps provide a positive user experience.
The final key is to provide the right data (and insight) to the right people in the right format at the right time. Aligning with this vision and using it as a "compass" to guide the design and development of analytics applications helps ensure a positive user experience and better results. Finally, both user experience experts and data experts try to understand human behaviour and solve problems, but they use different methods.