Optimize Digital Experience With UX Research

In a recent Applause webinar, titled Stop Guessing, Start Knowing: Leveraging UX Research to Optimize Digital Experiences, industry experts Celeste Buckhalter, Senior Director of UX Research at Applause, and Inge De Bleecker, AI UX consultant at outriderUX, shared insights into how businesses can leverage user experience (UX) research to enhance digital experiences. The session offered a look into the methodologies, strategies and real-world applications of UX research, with a particular emphasis on how these approaches can be integrated throughout the product development lifecycle to create truly user-centered products and experiences.

Introduction to UX Research: Testing Early and Often

Buckhalter kicked off the discussion highlighting the fundamental principle of UX research: the importance of testing early and often. She introduced two primary research approaches — generative UX research and evaluative UX research — each crucial at different stages of the product development process.

• Generative UX research – With exploration at its core, organizations use generative research in the early stages of development to understand user expectations, behaviors and pain points. With generative research, researchers might conduct one-on-one interviews, or observe people in their natural environments to uncover these insights. You don’t need to have a design. In fact, it often works best if you don’t have a design to put in front of the participants. Findings from this type of research can help generate ideas for future design.
• Evaluative UX research – Once the design process is underway, evaluative research becomes essential, and is often used iteratively. It’s used to test prototypes, wireframes, even fully developed products with participants who represent real users to identify usability issues and areas for improvement. Users will complete specific tasks to allow researchers to assess how they interact with the design. Researchers might observe and ask questions as the participants complete these tasks to learn more about the overall usability and UX of these designs. This type of research is used to evaluate a design and uncover underlying problems that may be impeding the user’s ability to complete a task.

Key Research Methodologies

Buckhalter outlined several specific research methodologies that UX teams can use to gain deeper insights into user experiences:

1. Inclusive UX studies – With inclusive studies, we incorporate people with disabilities (PWD) within our research studies. They may make up the total number of participants of the study or a portion. Involving PWD in both generative and evaluative research is important to understand how their overall UX might be different. With inclusive UX studies, organizations gain insights into what to consider when building for this market. They can better understand why adoption or retention rates might be lower for PWD. In addition, teams learn if the current design works fine as is for PWD, or if and how it should be adjusted to ensure better overall usability.
2. In-market research – Products designed for one market might not perform well in another due to cultural differences. With in-market insights, Applause researchers add an extra layer on top of a traditional UX study. Beyond evaluating the overall usability of a product, researchers dive deeper to understand how user needs and expectations may be different in a specific market and why. Applause uses researchers who live and work within these markets outside of the United States to provide that layer of expertise and insight. With in-market insights, we learn why adoption and retention rates might be lower in a particular region or market. We uncover cultural differences and insight to consider when designing for this particular region. In addition, researchers can learn if the current design can stand alone as it is now or if teams need to make adjustments to ensure that it’s viable.
3. Mixed methods – Many times, it makes sense to combine qualitative and quantitative research methods. With quantitative methods, involving large-scale studies with large numbers of participants, we answer the questions such as What is happening here? What issues are impacting the largest number of people? Blending in qualitative methods, researchers get deeper into the reasons why a given issue is impacting so many people and how and when people are experiencing this issue. Merging these methods brings a more holistic picture of what to address and what improvements might lead to a better UX, thereby leading to higher adoption and retention rates.

Read more about the various types of UX research methods in this blog. 

Webinar​

Real-World Applications and Case Studies

The webinar also provided several real-world examples to illustrate the practical application of UX research:

1. Generative research for Gen AI in the workplace – A client wanted to understand if workers would adopt generative AI (Gen AI) in their workflows. The research revealed that younger workers were more comfortable with Gen AI, but even experienced workers were open to using it if it effectively solved specific problems, such as helping to remember to do season-specific tasks. This insight guided the client’s design process, focusing on areas where Gen AI could be most beneficial.
2. Evaluative research for a luxury e-commerce site – The site allowed users to make appointments to try on clothes in-store but lacked clear stock availability labels to allow users to know if the clothing would be available when they went to the store. Evaluative research identified this as a significant usability issue, leading to the recommendation of adding “In Stock” or “Low Stock” labels, which would enhance user confidence and improve the overall experience.
3. Inclusive UX study for a health app – A mobile app designed for diabetics was evaluated with participants who had disabilities related to their condition. The study revealed that medical jargon and poor visual presentation were major barriers, prompting a redesign to make the app more accessible and user-friendly.
4. In-market insights for an online grocery service – A US-based online grocery service intended to launch in India faced challenges due to cultural differences. Research uncovered that Indian users were not accustomed to using smart speakers, a key component of the service. The findings led to a redesign that accounted for local shopping habits and cultural nuances, ensuring better adoption in the new market.
5. Mixed methods for a global digital platform – A client wanted to understand how their digital platform was performing across four key markets: Spain, Germany, the UK and France. While customers in Spain, Germany, and the UK were satisfied, those in France felt the platform lacked a “French feel,” as it used robotic, automatically translated language. By combining quantitative data on user satisfaction with qualitative insights into cultural preferences, the company could tailor their platform to better meet the expectations of their French users.

UX Research for AI Products

Inge De Bleecker added to the session with insights into UX research specifically for AI products, a rapidly evolving field. She emphasized that while the methodologies for AI UX research mirror traditional UX research, AI’s novelty requires a focus on user expectations and concerns, particularly around trust and privacy.

• Discoverability and usability of AI features – One common issue is that users often struggle to find or understand how to use new AI features. Ensuring these features are intuitive and easy to locate is crucial for user adoption.
• Utility and trust in AI – It’s important to evaluate whether an AI feature is genuinely useful to users. If a feature is perceived as unnecessary or intrusive, it risks being ignored or mistrusted. Ongoing research helps teams refine AI functionalities to better align with user needs and expectations.
• Transitioning from AI assistants to AI agents – De Bleeker explained the difference between AI assistants, which require user input to complete tasks, and AI agents, which can autonomously execute tasks based on historical data and user behavior. This shift increases the need for UX research to map out typical user steps and inform AI development effectively.

For example, De Bleeker described how an AI agent might schedule a meeting by using historical data to fill in missing details, such as the time and location, without needing to ask the user for this information. However, UX research is still crucial to ensure that users can easily interact with the AI agent, make adjustments and trust the decisions it makes on their behalf.

Key Takeaways

The webinar underscored the vital role of UX research in developing successful digital products. Key takeaways include:

• Early and frequent testing – Begin UX research as early as possible and continue testing throughout the product lifecycle to ensure that designs meet user needs and expectations.
• Inclusivity and diversity – Incorporate a wide range of user perspectives, including those with disabilities and users from different cultural backgrounds to create more universally accessible and effective products.
• Mixed methods for comprehensive insights – Use both qualitative and quantitative research methods to gain a full understanding of user behavior and identify areas for improvement.
• UX research in AI – As AI technologies evolve, UX research will remain crucial in ensuring that these innovations are user-friendly, trustworthy and valuable.