AI and user experience

During a conference on the use of AI and its ability to bring companies and their users closer together, the UI/UX Business Community by Beelix looked at user research. Antoine Pezé–UX and Product Management specialist for over ten years–shared his experience and introduced Synopsis, the solution he co-created to make customer data analysis easier.    

A BRIEF INTRODUCTION: WHAT IS UX?

UX, or user experience, refers to all interactions users have with a company, its services and products. It’s a very broad concept, that can be divided in 2 complementary aspects:

• User research: the goal is to synthesize collected data to better understand users’ needs and expectations.
• Design: to create useful and usable solutions.

Nowadays, there are two main types of UX professionals. Product Designers design the necessary modules while keeping an eye on users’ needs. UX researchers focus purely on user research.

User research is based on both qualitative and quantitative data collected at several levels and through various departments (marketing, customer service, sales, social media): there is a lot of information but it is very fragmented.

Usually easier to collect and analyze, quantitative data are taking the spotlight at the expense of qualitative data–for instance, customer feedback. What role do these data play? How to make the most of the thousands of user messages and feedback at our fingertips? This is the major challenge for UX Research today, as the practice spreads across all organizations, and begins to rely on AI to overcome existing limitations.    

UX RESEARCH: WORKING WITH USERS TO DEVELOP USEFUL AND USABLE PROJECTS

Let’s go back to the basics of user research: its aim is to confirm as early as possible the usefulness (Does this project solve a major problem?) and usability (Is the interface user-friendly?) of a project.

Investing in user research ahead of project design is key and presents many advantages:

• Securing the designing process. Fixing pain points after a module has been developed costs on average 100 times more than resolving them beforehand. (Clare-Marie Karat, IBM Research, 2009).
• Converting website visitors into customers. Websites with stunning user experience turn 400 times more visitors into clients. (Forester, 2016)
• Identifying problems quickly and easily. Tests with 5 users can reveal 85% of usability problems. (NNGroup, 2000)
• Speeding up development cycles. Investing in UX right from the design stage can cut module development time by up to 50%. (Interaction Design Foundation, 2020).

Afterwards, UX research is used to collect customer feedback through usability testing, to correct or improve the design.

Bear in mind that user research is most useful if the project is not too far along, and if the specifications are not yet very detailed. Examples: Give access to new features. Improve a department's accounting.    

IN PRACTICE: HOW DOES IT WORK?

There are several ways to gather users' expectations, needs and feedback: user interviews, surveys, user and usability testing, workshops and so on. The best approach is to start by turning directly to the people concerned: users are usually happy to answer questions, particularly if they have a problem to report.

The next step is to analyze and synthesize the information, whether by creating a persona (a typical user–age, personality and interests) or by drawing up numerical reports.

New ways of handling collected data are constantly being introduced: Atomic Research is one of them. This method draws on actual experiments to deduce objective facts and provide research insights that help either approve or reject a design idea.

Implementing user research is tricky, but with tools like Dovetail or even Notion, it's possible to display important UX elements and correlate them with quantitative data. Even though the results are conclusive, this task remains hard work, and is considered to bring little value as it involves a lot of manual processes for verbatim tagging. As a result, it is often overlooked in comparison with quantitative data.    

AI: THE SOLUTION TO USER RESEARCH

AI seems to be the answer, allowing us to maximize qualitative data. Time-consuming and tedious tasks are handed over to computers, and user feedback regains its relevance in the face of quantitative data.

ChatGPT is a popular tool, but is not quite up to the task of data analysis. Taking user research even further, Synopsis automatically processes and synthesizes all existing customer feedback, resulting in products and services that are highly useful and effective. The purpose of such a tool is to bridge the gap between companies and their users, by making syntheses accessible to all. Implementing this type of solution will prompt more organizations to engage with their customers.

By automating processes and analyzing signals from a wide range of content, AI has become an invaluable tool for UX professionals. Customer feedback, an essential piece of data, will then recover its rightful place and help make better-informed decisions.

This event was created as part of a Happy Talk by Beelix, a company specializing in user experience and part of Extia’s ecosystem. For more information, go to beelix.fr.