Understanding User Experience In Software Development

Traditional usability tests often treat user experience factors in isolation, as if different factors like usability, trust, and satisfaction are independent of each other. But in reality, they are deeply interconnected. By analyzing each factor separately, we miss the big picture - how these elements interact and shape user behavior. This is where Structural Equation Modeling (SEM) can be incredibly helpful. Instead of looking at single data points, SEM maps out the relationships between key UX variables, showing how they influence each other. It helps UX teams move beyond surface-level insights and truly understand what drives engagement. For example, usability might directly impact trust, which in turn boosts satisfaction and leads to higher engagement. Traditional methods might capture these factors separately, but SEM reveals the full story by quantifying their connections. SEM also enhances predictive modeling. By integrating techniques like Artificial Neural Networks (ANN), it helps forecast how users will react to design changes before they are implemented. Instead of relying on intuition, teams can test different scenarios and choose the most effective approach. Another advantage is mediation and moderation analysis. UX researchers often know that certain factors influence engagement, but SEM explains how and why. Does trust increase retention, or is it satisfaction that plays the bigger role? These insights help prioritize what really matters. Finally, SEM combined with Necessary Condition Analysis (NCA) identifies UX elements that are absolutely essential for engagement. This ensures that teams focus resources on factors that truly move the needle rather than making small, isolated tweaks with minimal impact.

There’s something deeply satisfying about watching a well-run qualitative interview quietly evolve into a sophisticated quantitative model. I always tell my students and collaborators that when done right, a simple conversation can eventually fuel something as complex as Structural Equation Modeling. It might sound like a stretch, but it’s really not. I went through this exact process in a study where we aimed to understand why users trust or reject a new product. Like many applied UX projects, we started with messy assumptions, vague ideas. We knew launching a survey would be premature, so we turned to interviews. We had open but focused (guided) conversations with users. Certain phrases kept surfacing. Some participants talked about feeling “disconnected” from the product, even though they found it useful. Others compared it to brands they already trusted, which clearly shaped their expectations. These comments weren’t dramatic, but they hinted at deeper structures behind user decisions. I worked through the transcripts by reading closely, making notes in the margins, and sketching out connections. There was no formal codebook in the beginning. Instead, I relied on a grounded and intuitive approach shaped by years of dealing with messy real-world data. Over time, themes began to take shape. Emotional tone, familiarity, and social alignment emerged as key ideas. These did not come from forcing responses into predefined buckets, but from how users naturally framed their experiences. It was far from a clean process. I constantly revisited groupings, challenged my own interpretations, and asked whether I was seeing real patterns or just noise. But that back-and-forth reflection is exactly where the model began to form. Once the ideas felt more stable, I started thinking about structure. One pattern stood out. When users described the product’s emotional tone early in the conversation, using words like “cold” or “inviting,” they often brought up trust later on. That sequence did not happen in reverse. It was a small but (almost!) consistent thread, and it became the basis for one of our causal paths. This is something people often overlook. Interviews do more than offer themes; they can reveal directionality. If you listen closely, the order in which ideas appear can show you which concepts come first, which serve as bridges, and how the entire experience unfolds in the user’s mind. Eventually, we translated those themes into measurable constructs and tested the model with survey data. Turning rich, emotional language into structured scale items was not easy. The final SEM model did not just fit the data well. It helped us predict how users would respond to different messaging and revealed emotional drop-off points we might have missed otherwise. All of that came from listening first, not guessing. Interviews are not the soft side of research. They are the foundation that allows your most complex methods to stand on something real.

Look at what they do, not just what they say. User behavior is how users interact with and use software. It includes things like: → how people navigate the interface → which features people use most often → the order in which people perform tasks → how much time people spend on activities → how people react to prompts or feedback Product managers and designers must understand these behaviors. Analyzing user behavior can enhance the user experience, simplify processes, spot issues, and make the software more effective. Discovering the "why" behind user actions is the key to creating great software. In many of my sales discussions with teams, I notice that most rely too heavily on interviews to understand user problems. While interviews are a good starting point, they only cover half of the picture. What’s the benefit of going beyond interviews? → See actual user behavior, not just reported actions → Gain insights into unspoken needs in natural settings → Minimize behavior changes by observing discreetly → Capture genuine interactions for better data → Document detailed behaviors and interactions → Understand the full user journey and hidden pain points → Discover issues and opportunities users miss → Identify outside impacts on user behavior Most people don't think in a hyper-rational way—they're just trying to fit in. That's why when we built Helio, we included task-based activities to learn from users' actions and then provided follow-up questions about their thoughts and feelings. User behaviors aren't always rational. Several factors contribute to this: Cognitive Biases ↳ Users rely on mental shortcuts, often sticking to familiar but inefficient methods. Emotional Influence ↳ Emotions like stress or frustration can lead to hasty or illogical decisions. Habits and Routine ↳ Established habits may cause users to overlook better options or new features. Lack of Understanding ↳ Users may make choices based on limited knowledge, leading to seemingly irrational actions. Contextual Factors ↳ External factors like time pressure or distractions can impact user behavior. Social Influence ↳ Peer pressure or the desire to conform can also drive irrational choices. Observing user behavior, especially in large sample sizes, helps designers see how people naturally use products. This method gives a clearer and more accurate view of user behavior, uncovering hidden needs and issues that might not surface in interviews. #productdesign #productdiscovery #userresearch #uxresearch

I keep hearing "session replays just didn't make it in the priority list." One ritual to make time? Andrew Capland suggests weekly sessions: Andrew was a 2x head of growth. His favorite ritual? — A weekly team meeting called "Fullstory Fridays." Every Friday, the team would come together live with the goal of gaining insights from user experience. An informal setting where there was no pressure to do something just for the sake of it. They would pull out 20 different user interaction sessions, and each team member focused on their area: → Engineers would spot bugs, take notes, and sometimes fix them on the fly... → Designers would see people rage-clicking and sketch ideas to improve the experience... → And beyond this, they often found users translating their app into different languages... (something they hadn’t even considered.) Doing this helped them: → Better understand problems without guessing → Understand their users better → Come up with fresh ideas — I think doing this in an informal session with a team of experts is so powerful: A. It doesn’t feel like a chore Every PM dreads sitting for hours watching users interact with their product. But when you do it together in an informal setting, it’s not boring anymore, especially if you’re having fun along the way. B. Cross-functional alignment Engineers, PMs, and designers gain firsthand exposure to real user problems. And develop a shared understanding of what users are "silently" asking for. C. Better prioritization The team rallies around what truly matters to users.