Ethnographic Research In UX

There's something almost nobody is talking about in AI - but it affects everything from asking ChatGPT for advice to companies deploying AI globally. A fascinating study tested major AI Models - the foundations powering tools millions use daily - against cultural values from 107 countries worldwide. The result? Each one reflected the same assumptions - those of English-speaking, Western European societies. None aligned with how people in Africa, Latin America, or the Middle East actually build trust, show respect, or resolve conflicts. Why does this matter? Imagine you're a global company rolling out AI customer service. Your system learns "best practice": when customers complain about late orders, "apologise briefly, offer a discount, and focus on quick resolution". In Germany, the direct, efficient approach works perfectly. Customer satisfied. But in Japan, that brief apology violates meiwaku - the cultural need to deeply acknowledge when you've caused someone inconvenience. Your "efficient" response feels dismissive and damages customer relationships. And in the UAE, the discount offer backfires completely. It feels like charity rather than respect. One AI system, similar contexts, completely different cultural outcomes. This isn't intentional though - it's inevitable. LLMs absorb embedded patterns about communication from their training data, and most of that data comes from billions of English web pages and content. The result? AI systems that, unless thoughtfully shaped, are blind to the diversity of human interaction. Klarna, the global payments company, made headlines in 2024 when they introduced an AI system that "did the work of 700 customer service reps", handled 2.5 million conversations in 35 languages, and cut response time by 82%. Technical triumph. 14 months later: "Klarna reverses AI strategy and is hiring humans again". Their CEO admitted it had led to "lower quality". Some reports said they'd seen a 20%+ decrease in customer satisfaction. What I think really happened: Klarna optimised for 35 languages while completely missing 35 different ways humans expect to be treated. The challenge? Most companies are focusing on technical integration and completely missing cultural intelligence. We measure response time and cost savings, but never ask, "which human complexities are we overlooking?" The goal isn't neutrality though - that's impossible and undesirable. It's conscious awareness. Understanding that the output from AI models is filtered through a specific cultural lens. For companies building AI strategies, key questions worth asking: * Which cultural assumptions are embedded in our AI systems? * How do we test cultural intelligence alongside technical performance? * Who provides this expertise in our AI teams? The individuals and organisations that develop this conscious awareness will make better decisions, while others unknowingly apply one-size-fits-all approaches to beautifully diverse human contexts.

Your tech solutions might be universal, but business cultures rarely are. For founders expanding globally, understanding cultural nuances can make a world of difference. I've seen so many brilliant construction tech solutions face unexpected challenges internationally not because of product issues, but because of cultural cues that were hiding in plain sight. What works smoothly in your home market frequently encounters unexpected barriers abroad. In our latest Practical Nerds episode, Shubhankar and I explored three cultural patterns we've observed that often create unexpected challenges for founders expanding internationally: 1/ Trust deficit can kill deals in Asia before you realize what happened. Asian markets require relationships BEFORE transactions. That mid-deal silence? It's not disinterest—it's a fundamental lack of trust. When things stall, don't send another "just checking in" email. Request a direct call: "Hey, can we get on a call? I'd just like to hear from you." 2/ Europeans want facts, not hype. Your high-energy American pitch style? It can be "overcompensating" to Europeans. They're engineering-minded—lead with observations, not judgments. And remember: Europeans minimize downside before maximizing upside. Frame your solution as risk mitigation first, opportunity second. 3/ Middle East surprisingly loves American tech but demands in-person presence. Virtual meetings barely register as "meetings" at all. And forget the org chart—decisions flow through specific gatekeepers who might not even appear in formal hierarchies. What seems to work well for many companies in global expansion? Maintaining consistent products and channels while building localized teams who can navigate the nuances of each market's business culture. 👇 Dive deeper into our full analysis of global construction tech expansion below. #ConstructionTech #GlobalExpansion #BusinessCulture

The real threat isn't malware. It's silence. We had the tools. We had the budget. But we still got breached. That line came from a client years ago in Southeast Asia, and it stuck with me. After 15 years in cybersecurity, one lesson stands out clearly across the Asia Pacific: Technology rarely fails first. People do. When you operate across countries like Singapore, Thailand, Malaysia, Indonesia, and the Philippines, you start to see deeper patterns. Not technical ones. Behavioural ones. In some markets, staff members hesitate to report incidents for fear of being blamed. In others, there is a strong culture of hierarchy, which makes it hard for junior employees to challenge suspicious activity. Sometimes, the biggest obstacle is not the attacker outside. It is the silence inside. We often treat cybersecurity as a technical challenge. But adoption is driven by trust, context, and cultural relevance. That is why the same selling approach that works in the US has a low chance of working in Southeast Asia. It is not because people do not care. It is because the framing does not fit the environment. Over time, I have learnt to approach cyber selling like market development: → Start with empathy → Speak the local language, not just linguistically but emotionally and socially → Focus on behaviours, not just knowledge Cybersecurity in Asia is not just about rolling out tools. It's about building a culture where people feel safe speaking up, slowing down, and making informed decisions under pressure. If we want real resilience, we need to stop selling fear and start shaping habits. What cultural or behavioural barriers have you seen when it comes to cyber awareness in your region? I would love to hear your stories. #alvinsratwork ✦ #BusinessTechnologist ✦ #ExecutiveDirector

Last week, I coached a product team through a user interview debrief. They were excited! Users had shown enthusiasm for a new feature! 🎉 But when I asked, ��What problem does this solve for them?” the room went quiet. 🫣 This happens more often than we’d like to admit. 🧠 The Trap: Mistaking Enthusiasm for Validation When users say, “That sounds great!” we often interpret it as validation. But here's the catch: - Users want to be polite. - They might not fully understand their own needs. - As product teams, we may hear what we want. This is why relying solely on user enthusiasm can lead us astray. 🔍 The Solution: Semi-Structured Interviews We need to dig deeper to understand our users truly. Semi-structured interviews strike the right balance between guidance and flexibility. Key practices include: - Start with hypotheses: Identify what you believe to be true. - Ask open-ended questions: Encourage users to share experiences, not just opinions. - Listen actively: Pay attention to what’s said—and what’s not. - Probe for underlying needs: Seek to understand the 'why' behind their behaviours. This approach helps uncover genuine insights, leading to solutions that truly resonate. 🌟 Imagine the Impact By adopting this method: - Teams build products that solve real problems. - User satisfaction increases. - Resources are invested wisely, reducing wasted effort. It's not just about building features—it's about delivering value. 🦾 Take Action Next time you're planning user interviews: - Prepare a set of hypotheses. - Design questions that explore user experiences. - Remain open to unexpected insights. Remember, the goal is to understand your users, not just confirm your assumptions deeply.

Let's face it: most user interviews are a waste of time and resources. Teams conduct hours of interviews yet still build features nobody uses. Stakeholders sit through research readouts but continue to make decisions based on their gut instincts. Researchers themselves often struggle to extract actionable insights from their conversation transcripts. Here's why traditional user interviews so often fail to deliver value: 1. They're built on a faulty premise The conventional interview assumes users can accurately report their own behaviors, preferences, and needs. People are notoriously bad at understanding their own decision-making processes and predicting their future actions. 2. They collect opinions, not evidence "What do you think about this feature?" "Would you use this?" "How important is this to you?" These standard interview questions generate opinions, not evidence. Opinions (even from your target users) are not reliable predictors of actual behavior. 3. They're plagued by cognitive biases From social desirability bias to overweighting recent experiences to confirmation bias, interviews are a minefield of cognitive distortions. 4. They're often conducted too late Many teams turn to user interviews after the core product decisions have already been made. They become performative exercises to validate existing plans rather than tools for genuine discovery. 5. They're frequently disconnected from business metrics Even when interviews yield interesting insights, they often fail to connect directly to the metrics that drive business decisions, making it easy for stakeholders to dismiss the findings. 👉 Here's how to transform them from opinion-collection exercises into powerful insight generators: 1. Focus on behaviors, not preferences Instead of asking what users want, focus on what they actually do. Have users demonstrate their current workflows, complete tasks while thinking aloud, and walk through their existing solutions. 2. Use concrete artifacts and scenarios Abstract questions yield abstract answers. Ground your interviews in specific artifacts. Have users react to tangible options rather than imagining hypothetical features. 3. Triangulate across methods Pair qualitative insights with behavioral data, & other sources of evidence. When you find contradictions, dig deeper to understand why users' stated preferences don't match their actual behaviors. 4. Apply framework-based synthesis Move beyond simply highlighting interesting quotes. Apply structured frameworks to your analysis. 5. Directly connect findings to decisions For each research insight, explicitly identify what product decisions it should influence and how success will be measured. This makes it much harder for stakeholders to ignore your recommendations. What's your experience with user interviews? Have you found ways to make them more effective? Or have you discovered other methods that deliver deeper user insights?

How do you and your teams synthesise and select which customer needs or pains to progress in your #product, #design, or #innovation projects? Imagine you've just completed some great customer discovery research, including observing, interviewing and being the customer. You've built some good empathy for who your customers are, what is important to them, what pains them, and what delights them. Then you unpack your findings into some form of empathy map, and you've got 100s of sticky notes everywhere. You've then started to narrow them down to the most promising and interesting observations, but this still leaves you with a sizeable collection and you want to add some rigour to your intuition on which ones to take forward first. Well, here are 3 different methods that I’ve used and iterated over the years: Number One – The Opportunity Scale This first one is the simplest and is inspired by how Alexander Osterwalder et al rank jobs, pains and gains in their book Value Proposition Design, 2014. As a team, you take your short list of observations from your empathy map and rank them from how insignificant/moderate to how important/extreme the need/pain is for the customer with the most important/extreme being prioritised to explore further first. Number two – The Opportunity Matrix A The opportunity matrix increases the rigour and confidence of your prioritizing by adding ‘strength of evidence’ as another dimension. Strength of evidence at this stage of journey can be determined by the number and type of data points. For example, if you heard from several customers that a pain point was extremely painful then you could be more confident this was worth solving than one highlighted by only one customer. Likewise, observing customers do something provides stronger evidence than customers saying they do something. Here you prioritise the most important needs with the strongest evidence first. Something to watch out for is when your team selects an observation that has strong evidence but isn’t that important of a need or pain to customers. Teams can be blinkered by numbers and end up over-investing in time wasting-opportunities. Number three – The Opportunity Matrix B The third method swaps out evidence for fulfilment of the need - how satisfied are customers with their ability to fulfil the need/solve the pain with the solutions they use today? By matching this with the importance of the need/pain we can select those observations that we understand to be the most important and unmet for our customers. You can then overlay the strength of evidence across this ranking to make your final selection even more robust. And to take it to a whole new level and really de-risk your selection you can test your prioritised observations, written as need statements, in quantitative research with customers. This is something that Antony Ulwick shares in his book Jobs To Be Done, 2016. I hope you find these methods useful. #designthinking #humancentreddesign

💡 Mapping user research techniques to levels of knowledge about users When doing user research, it's important to choose the right methods and tools to uncover valuable insights about user behavior. It's possible to identify 3 layers of user behavior, feelings, and thoughts: 1️⃣ Surface level - Say & Think This level captures what users say in conversations, interviews, or surveys and what they think about a product, feature, or experience. It reflects their stated opinions, thoughts, and intentions. Example: "I prefer simple products" or "I think this app is easy to use." Methods: Interviews, Questionnaires. These methods capture stated thoughts and opinions. However, insights may be influenced by social norms or biases. 2️⃣ Mid-level - Do & Use This level reflects what users actually do when interacting with a product or service. It emphasizes actions, usage patterns, and observed behaviors, revealing insights that may differ from what users say. Example: Users may claim they enjoy customizing app settings, but data shows they rarely change default options. Methods: Usability Testing, Observation. Observation helps to reveal gaps between what people say and what they actually do. 3️⃣ Deep level - Know, Feel and Dream This level uncovers deep motivations, emotions, desires, and aspirations that users may not be consciously aware of or may struggle to articulate. It also includes tacit knowledge—things people know intuitively but find hard to express. Example: A user might not realize that their preference for a minimalist design comes from the information overload of a current design. Methods: Probes (e.g., participatory design, diary studies). Insights collected using these methods will uncover implicit and emotional drivers influencing behavior. 📕 Practical recommendations for mapping ✅ Triangulate insights by using multiple methods. What people say (interviews/surveys) may differ from what they do (observations) and feel. That's why it's essential to interpret these results in context. For example, start with interviews to learn what users say. Follow up with usability testing to observe real behavior. Use probes for long-term or emotional insights. ✅ Align research with business goals. For product improvements, focus on usability testing to catch interaction issues. For innovation, use probes to generate new ideas from user insights. ✅ Practice iterative learning. Apply surface techniques (like surveys) early to refine assumptions and guide more in-depth research later. Use deep techniques (like probes) for strategic decisions and to foster innovation in long-term projects. 🖼️ UX Research methods by Maze #ux #uxresearch #design #productdesign #uxdesign #ui #uidesign

If Behaviors Drive Culture... what drives behavior then? We all know that culture shapes what feels expected, what gets rewarded, and what people learn to avoid in an organization, but how do we get to the root cause of it all? If we want to change or evolve culture, we can’t just stop at naming the behaviors we’d like to see more of, we also have to understand what’s making those behaviors hard or misaligned with how things currently work. I took this simple culture map, and added a few examples to help illustrate how it works. This isn't a template to copy, because of course it is incomplete, but I like to show things so they are visual and easy to understand. This mapping or canvas becomes useful, because it helps your team see what’s underneath the behavior... think beliefs norms, expectations, structures, and feedback loops that quietly shape what people do, even when no one is looking. This is the part that most people get wrong... because they go from what’s visible to what they think is a solution, without understanding what kind of barrier they’re dealing with. This is where real behavioral change needs to become operational! You need a way to classify what’s going on - you need models and frameworks to help answer: • Is it a lack of skill or knowledge? • A belief that’s outdated but persistent? • A social norm no one questions? • A structural constraint that makes the behavior impractical? •An identity issue, where doing the new behavior would mean not being seen as a “good colleague” or “strong leader”? If you can’t distinguish these nuances, then any solution you design is essentially a guess because you are working with intuition and not evidence. This is the most important part to get right and where most of my clients ask me to work with them on, because In every project we run, whether it’s cultural alignment, policy redesign, or transformation strategy, we build this kind of behavioral mapping in from the start. 1) We identify the behaviors that matter. 2) We map what’s reinforcing or blocking them. 3) We use models like COM-B, TDF, and BNOS to analyze the patterns. 4) We match techniques to the actual barrier so the solution fits the mechanism, not just the symptoms. Most of my careers, I used to go straight from behavior to idea, without doing the work in the middle, but once I learned how to build this kind of analysis into the process, things started working more consistently and more systemically. In the end, if you want to change behavior, you have to understand what holds it in place and If you want to evolve culture, that’s where you start. What’s quietly holding your current behaviors in place, even when everyone says they want change? (Canvas adapted from - Dave Grey/Strategyzer)

Two quiet team members. Two different reasons. Vietnamese culture or who they are? If you're guessing, your leadership shows it. You can't tell the difference. That's the problem. You read that "Vietnamese people value harmony." So you assume Minh won't disagree because he's Vietnamese. That's not cultural intelligence. That's generalization. Culture gives you the pattern. The person shows you where they stand on it. Yes, in Vietnam, direct disagreement with a senior leader is often avoided. That's the cultural pattern. But Minh: he's more direct than most. That's the person. If you assume he'll never push back, you'll miss his subtle signals completely. You'll think he agrees when he's actually disengaging. You need both layers: The cultural lens tells you what's common. The individual understanding tells you what's true for this person. That's cross-cultural leadership. Without the cultural lens, you misread everything. Without the individual lens, you stereotype everyone. Why this matters more than you think: When you get it wrong, your leadership doesn't land. Your feedback feels like an attack. Your delegation feels like distrust. Your praise feels empty. Your team don't bring you ideas. They don't take initiative. They smile, nod, and wait for you to leave. You're leading, but nothing's moving. That silence you're hearing: It's not agreement. It's distance. The expat leaders I work with master both layers. They understand the deep cultural patterns that shape Vietnamese workplaces. Then they see each person clearly within that context. They stop guessing. They stop assuming. They influence ad have impact. If this hits close to home, let’s talk.