User Research For New Markets

⏱️ How To Measure UX (https://lnkd.in/e5ueDtZY), a practical guide on how to use UX benchmarking, SUS, SUPR-Q, UMUX-LITE, CES, UEQ to eliminate bias and gather statistically reliable results — with useful templates and resources. By Roman Videnov. Measuring UX is mostly about showing cause and effect. Of course, management wants to do more of what has already worked — and it typically wants to see ROI > 5%. But the return is more than just increased revenue. It’s also reduced costs, expenses and mitigated risk. And UX is an incredibly affordable yet impactful way to achieve it. Good design decisions are intentional. They aren’t guesses or personal preferences. They are deliberate and measurable. Over the last years, I’ve been setting ups design KPIs in teams to inform and guide design decisions. Here are some examples: 1. Top tasks success > 80% (for critical tasks) 2. Time to complete top tasks < 60s (for critical tasks) 3. Time to first success < 90s (for onboarding) 4. Time to candidates < 120s (nav + filtering in eCommerce) 5. Time to top candidate < 120s (for feature comparison) 6. Time to hit the limit of free tier < 7d (for upgrades) 7. Presets/templates usage > 80% per user (to boost efficiency) 8. Filters used per session > 5 per user (quality of filtering) 9. Feature adoption rate > 80% (usage of a new feature per user) 10. Time to pricing quote < 2 weeks (for B2B systems) 11. Application processing time < 2 weeks (online banking) 12. Default settings correction < 10% (quality of defaults) 13. Search results quality > 80% (for top 100 most popular queries) 14. Service desk inquiries < 35/week (poor design → more inquiries) 15. Form input accuracy ≈ 100% (user input in forms) 16. Time to final price < 45s (for eCommerce) 17. Password recovery frequency < 5% per user (for auth) 18. Fake email frequency < 2% (for email newsletters) 19. First contact resolution < 85% (quality of service desk replies) 20. “Turn-around” score < 1 week (frustrated users → happy users) 21. Environmental impact < 0.3g/page request (sustainability) 22. Frustration score < 5% (AUS + SUS/SUPR-Q + Lighthouse) 23. System Usability Scale > 75 (overall usability) 24. Accessible Usability Scale (AUS) > 75 (accessibility) 25. Core Web Vitals ≈ 100% (performance) Each team works with 3–4 local design KPIs that reflects the impact of their work, and 3–4 global design KPIs mapped against touchpoints in a customer journey. Search team works with search quality score, onboarding team works with time to success, authentication team works with password recovery rate. What gets measured, gets better. And it gives you the data you need to monitor and visualize the impact of your design work. Once it becomes a second nature of your process, not only will you have an easier time for getting buy-in, but also build enough trust to boost UX in a company with low UX maturity. [more in the comments ↓] #ux #metrics

A Behavioural Strategist needs to analyse the world. So we carry multiple lenses in our toolbox. And use them in the right combination to build a microscope or a telescope depending on the context. One of neat lens I have available to me is the idea of Behavioural Segmentation - I borrowed Matt Wallaert's "5 stages" and started using it at 1001 Stories with some modifications. And yes, I asked for his permission. Like I did with Raheel Waqar when I said I love "Kahani, Aasani & Yaad-Dehani" and can I borrow it please? And with Dave Trott when I said I want to borrow his writing style. The idea of Behavioural Segmentation is simple. The group you are trying to understand, analyse and influence can be in one of the 5 cohorts. These two are your 'extreme' cases👇 1. No / Never: I have never done it. I will never do it. 2. Always / Mostly: I more or less do it regularly. These are your 'changed behaviour' cases👇 3. Just Started: I just started doing it. 4. Just Stopped: I recently stopped doing it. And this is the contextual case that where majority will fall👇 5. Sometimes: I do it sometimes. Sometimes I don't. The behaviour we are talking about 'doing' could be anything. Exercising, filing taxes (or filling timesheet) before deadline, using credit cards, ordering food on a delivery app, shopping on e-commerce, spitting / throwing garbage on the road and so on. Combine this segmentation of cohorts with the nature of the behaviour itself: - Is it a one time behaviour (e.g voting or making a will)? - Does it have a start and an end (e.g a 6 weeks diet plan)? - Does it have to be done regularly (e.g. exercise)? And now you will find yourself dancing around in your office room, analysing all your primary and secondary research with your team members. You can now figure out - why Mr. Jijo never skips leg day at gym, - why Miss Ananya switched to UPI from Credit Cards - and what made Mr. Rajeev picked up Diet Coke even though he is a hard core Thums Up fan. Figuring out the triggers, the biases and the hot states mean you can now build better healthcare, financial and retail solutions which have a higher probability of succeeding. Plus you have a way now to evaluate the impact of your behavioural interventions by checking movements of folks to left or right in the cohorts frequency spectrum. PS: This is a high level overview and there are nuances to using it. And yes, please feel free to borrow this and adapt it whichever way you see fit. Let's create better products, brands and people. Cheers~! 1001 Stories | Behavioural Science Club | Diversifi Global | #BehaviouralScience #ContextArchitecture #BehaviouralSegmentation #ToolsOfTheTrade

After mentoring over 800 UX researchers over the past decade, I’ve noticed one clear pattern: The best researchers don’t just gather data, they drive action. They have habits that help them uncover insights, inspire teams, and de-risk decisions. Here are 8 of the most effective habits I’ve seen (and how you can start practicing them): 1. Comfort in ambiguity ↳ Great researchers don’t rush to conclusions. ↳ They embrace the grey areas and let insights emerge. Next time you’re synthesizing data, resist the urge to clean it up. Explore contradictions, which often lead to breakthroughs. 2. Ask the unasked questions ↳ They challenge assumptions and dig deeper. ↳ When everyone’s aligned, they ask, “What if we’re missing something?” Start every project with this question: “What don’t we know that could derail us?” 3. Endlessly curious ↳ Great researchers don’t just ask why, they ask what if? ↳ Curiosity fuels their creativity and problem-solving. Pick one unexpected user behavior from your data this week and explore why it’s happening. 4. Know when to stop ↳ They understand that more data doesn’t always mean better decisions. ↳ They recognize when diminishing returns set in and shift from research to action. Before starting a new study, ask, “What decision are we trying to inform?” If you already have enough data, stop and act. 5. Playful with insights ↳ They treat insights like puzzles, not checkboxes. ↳ The best researchers experiment with how findings are framed and presented. In your next synthesis, frame one insight in three different ways to spark new perspectives. 6. Thrive in collaboration ↳ Effective researchers know insights gain power when shared. ↳ They work closely with designers, PMs, and engineers to co-create solutions. Bring stakeholders's needs into research studies directly, help them make tough decisions and mitigate risk, watch how buy-in skyrockets. 7. Bring discomfort ↳ They don’t settle for validating assumptions—they challenge them. ↳ Insights that spark discomfort often lead to the biggest breakthroughs. If your findings aren’t sparking hard conversations, dig deeper. Research that challenges assumptions often drives transformation. 8. Unafraid to be ignored ↳ Effective researchers understand that not every insight will lead to action—and that’s okay. ↳ They focus on building a culture of evidence-based decision-making over time. Track the outcomes of your research. Revisit findings at the right moment, like a project pivot, a problem resurfaces, or priorities shift. Timing can turn a no into a valuable yes. What habits have made you a better researcher? Share them in the comments // Sick of begging people to listen to your research only to be met with a thumbs up emoji? I share strategies to deliver UXR impact on my Substack: https://lnkd.in/eR5M2geZ

Last week, I was analyzing a new market opportunity when I realized - we often dive into execution without truly understanding the competitive landscape. I studied Porter's Five Forces at Indian Institute of Management, Indore, but, I actually applied it recently and was blown away by the insights. Here's what caught my attention: The framework isn't just about direct competitors. It forced me to think about how easy it would be for new players to enter (threat of new entrants), the power dynamics with suppliers and customers, and even substitute products that could make our offering irrelevant. What fascinated me most? In today's digital age, the bargaining power of customers has dramatically increased. With information at their fingertips, they're more informed than ever. This shift has completely changed how we need to think about competitive advantage. What competitive analysis frameworks do you rely on for strategic decisions? P.S. Thinking of creating a small community for conversations around AI, Marketing & Strategy. DM if interested in joining! #CompetitiveStrategy #BusinessGrowth #StrategicThinking

Your research findings are useless if they don't drive decisions. After watching countless brilliant insights disappear into the void, I developed 5 practical templates I use to transform research into action: 1. Decision-Driven Journey Map Standard journey maps look nice but often collect dust. My Decision-Driven Journey Map directly connects user pain points to specific product decisions with clear ownership. Key components: - User journey stages with actions - Pain points with severity ratings (1-5) - Required product decisions for each pain - Decision owner assignment - Implementation timeline This structure creates immediate accountability and turns abstract user problems into concrete action items. 2. Stakeholder Belief Audit Workshop Many product decisions happen based on untested assumptions. This workshop template helps you document and systematically test stakeholder beliefs about users. The four-step process: - Document stakeholder beliefs + confidence level - Prioritize which beliefs to test (impact vs. confidence) - Select appropriate testing methods - Create an action plan with owners and timelines When stakeholders participate in this process, they're far more likely to act on the results. 3. Insight-Action Workshop Guide Research without decisions is just expensive trivia. This workshop template provides a structured 90-minute framework to turn insights into product decisions. Workshop flow: - Research recap (15min) - Insight mapping (15min) - Decision matrix (15min) - Action planning (30min) - Wrap-up and commitments (15min) The decision matrix helps prioritize actions based on user value and implementation effort, ensuring resources are allocated effectively. 4. Five-Minute Video Insights Stakeholders rarely read full research reports. These bite-sized video templates drive decisions better than documents by making insights impossible to ignore. Video structure: - 30 sec: Key finding - 3 min: Supporting user clips - 1 min: Implications - 30 sec: Recommended next steps Pro tip: Create a library of these videos organized by product area for easy reference during planning sessions. 5. Progressive Disclosure Testing Protocol Standard usability testing tries to cover too much. This protocol focuses on how users process information over time to reveal deeper UX issues. Testing phases: - First 5-second impression - Initial scanning behavior - First meaningful action - Information discovery pattern - Task completion approach This approach reveals how users actually build mental models of your product, leading to more impactful interface decisions. Stop letting your hard-earned research insights collect dust. I’m dropping the first 3 templates below, & I’d love to hear which decision-making hurdle is currently blocking your research from making an impact! (The data in the templates is just an example, let me know in the comments or message me if you’d like the blank versions).

Nations’ capabilities in frontier technologies will drive their fortunes. There is deep danger of this accentuating global wealth polarization, but there is also a real opportunity for developing countries to accelerate faster than the leaders. An excellent UN Trade and Development (UNCTAD) report on frontier technologies globally lays the current state and how we can shape a more inclusive global future. (Link in comments) Some of the key points: 🌍 $16 Trillion Prize, Running Fast Frontier‑tech revenue is set to jump from $2.5 trillion in 2023 to $16.4 trillion by 2033, with AI alone reaching $4.8 trillion and IoT $3.1 trillion. For developing countries, that growth window is large but time‑bound; early adoption can secure export niches before global standards solidify. ⚠️ Innovation Bottleneck Just 100 firms command over 40% of global business R&D, and half of that spend is in the United States. Such dominance skews AI toward capital‑intensive models, risking a loss of labor‑cost advantage for lower‑income economies. 🔧 Three Levers for Catch‑Up UNCTAD highlights a feedback loop: better compute and connectivity enable bigger data sets; richer data improve local algorithms; skilled talent then scales usage, justifying more infrastructure outlays. Grounded national plans should target these levers in parallel, not sequentially. 🤝 Practical Adoption Rules Field cases distil four rules: design for weak infrastructure; mine non‑traditional data; keep user interfaces simple; and form partnerships for expertise and finance. Examples range from offline crop‑diagnosis apps in Colombia to battery‑powered X‑ray units in South Sudan. 🚀 Evidence of Momentum Brazil, China, India and the Philippines already punch above their income class on UNCTAD’s readiness index, while developer numbers in Nigeria, Ghana and Indonesia are growing 30–45 % a year. Coupled with broader calls for inclusive AI governance, these signals show that emerging economies are positioned not just to adopt AI but to help shape its global uptake.

Three developments stood out this week: oil volatility, trade realignment, and asynchronous easing by central banks in emerging markets ⬇️ Oil market disruption and stagflation risk ⛽ The Israel-Iran escalation has jolted energy markets. Brent crude is up nearly 20% since early June, amid fears of disruption to oil flows—especially via the Strait of Hormuz, which handles 20% of global oil and gas shipments. Though Iran’s exports remain sanctioned, broader escalation could drive prices above $100/bbl. A $70–80/bbl range reflects current moderate risk pricing. Strategic reserve releases and OPEC adjustments may help stabilize markets. Trade rerouting under rising US tariffs 🔄 With an effective US tariff rate of 8% in May 2025—below the theoretical 13%—importers still face mounting costs. Frontloading and rerouting are buffering the impact: Taiwanese exports to the US are 63% above trend, while Chinese direct exports are falling. Exports from ASEAN and Latin America are accelerating. Rerouting via ASEAN and India now covers ~40% of China’s shortfall, reshaping global trade flows. Diverging EM monetary paths 💹 While the Fed is expected to cut rates by 100bps through 2026, EM central banks are far from synchronized. Of 32 large EMs (>35% of global GDP), most are easing, but at varied speeds. We identify four clusters with Brazil remaining the exception—still hiking to control inflation: ♦ Leaders (e.g. Mexico, Türkiye) with bold cuts ♦ Moderators (e.g. Czechia, Kenya) slowing due to resurgent inflation ♦ Pre-Fed movers (e.g. Poland, Romania) benefiting from FX strength ♦ Gradualists (e.g. China, India, Vietnam) nearing cycle end. #Geopolitics #OilMarkets #GlobalTrade #EmergingMarkets #CentralBanks #Stagflation #InterestRates #EconomicOutlook #Mexico #Türkiye #Czechia #Kenya #Brazil #Poland #Romani #China #India #Vietnam #Ludonomics #AllianzTrade #Allianz

Recently, I had the opportunity to share my learnings and insights from "Launching Products Globally" with an amazing audience at Plug and Play Tech Center with the presence of global audience including entrepreneurs from HKSTP - Hong Kong Science and Technology Parks Corporation. Here are a few learnings and insights from the evening: 1) You need to "localize" your product & go-to-market strategy: This doesn't only mean just translating or localizing your product. It's a lot more than that. You need to localize your "go-to-market" motion as well. You may have product-market-fit (PMF) locally, in the first country/region you launched, but that doesn't mean you can take the same product and go-to-market strategy to launch in a new country/region. As an example at Fitbit, we learned how the French think about fitness (they count walking to a restaurant to get a glass of wine as their "fitness") is very different than how Americans define workout and fitness. So all our marketing and go-to-market strategies had to align with the way locals will see benefits in our products. 2) Having boots on the ground is essential for successful global expansion: You need to have boots on the ground who truly understand the nuances of how to go-to-market, how to sell, and how to deliver your value proposition to customers in different regions. There are a lot of nuances of how to do business locally that will take outsiders to any market a long time to learn. At Cleo, where we had global customers like Salesforce, Redbull, Pepsi, and Uber, we had to have local health Guides to deliver our services with an intimate understanding of customers needs and approaches in that region. 3) Understanding local, cultural, and social aspects is critical to a global expansion success: Even though at the surface things may seem similar in each region, there are a lot of nuances that make your go-to-market strategy and the way you deliver your services resonate with the local customers or not. At Teladoc, we've learned that people in different countries think about their mental health and how to get support for that "very differently" than each other. Huge thank you to my hosts Rahim Amidi, Dr. Yahya Tabesh, Amir Amidi, Ahmadreza Masrour, and Akvile Gustaite, and HKSTP leaders, Albert Wong & Pheona Kan, who are interested in continuing these conversations. It was awesome to meet great entrepreneurs and see old friends: Reza Moghtaderi Esfahani, Daniel Lo, Houman Homayoun, Wayne Chang, Golnaz (Naz) Moeini. #product #gotomarket #globallaunch #globalbusiness

Imagine this: you’re filling out a survey and come across a question instructing you to answer 1 for Yes and 0 for No. As if that wasn't bad enough, the instructions are at the top of the page, and when you scroll to answer some of the questions, you’ve lost sight of what 1 and 0 means. Why is this an accessibility fail? Memory Burden: Not everyone can remember instructions after scrolling, especially those with cognitive disabilities or short-term memory challenges. Screen Readers: For people using assistive technologies, the separation between the instructions and the input field creates confusion. By the time they navigate to the input, the context might be lost. Universal Design: It’s frustrating and time-consuming to repeatedly scroll up and down to confirm what the numbers mean. You can improve this type of survey by: 1. Placing clear labels next to each input (e.g., "1 = Yes, 0 = No"). 2. Better yet, use intuitive design and replace numbers with a combo box or radio buttons labeled "Yes" and "No." 3. Group the questions by topic. 4. Use headers and field groups to break them up for screen reader users. 5. Only display five or six at a time so people don't get overwhelmed and bail out. 6. Ensure instructions remain visible or are repeated near the question for easy reference. Accessibility isn’t just a "nice to have." It’s critical to ensure everyone can participate. Don’t let bad design create barriers and invalidate your survey results. Alt: A screen shot of a survey containing numerous questions with an instructing you to answer 1 for Yes and 0 for No. The instruction is written at the top and it gets lost when you scroll down to answer other questions. #AccessibilityFailFriday #AccessibilityMatters #InclusiveDesign #UXBestPractices #DigitalAccessibility

User Feedback Loops: the missing piece in AI success? AI is only as good as the data it learns from -- but what happens after deployment? Many businesses focus on building AI products but miss a critical step: ensuring their outputs continue to improve with real-world use. Without a structured feedback loop, AI risks stagnating, delivering outdated insights, or losing relevance quickly. Instead of treating AI as a one-and-done solution, companies need workflows that continuously refine and adapt based on actual usage. That means capturing how users interact with AI outputs, where it succeeds, and where it fails. At Human Managed, we’ve embedded real-time feedback loops into our products, allowing customers to rate and review AI-generated intelligence. Users can flag insights as: 🔘Irrelevant 🔘Inaccurate 🔘Not Useful 🔘Others Every input is fed back into our system to fine-tune recommendations, improve accuracy, and enhance relevance over time. This is more than a quality check -- it’s a competitive advantage. - for CEOs & Product Leaders: AI-powered services that evolve with user behavior create stickier, high-retention experiences. - for Data Leaders: Dynamic feedback loops ensure AI systems stay aligned with shifting business realities. - for Cybersecurity & Compliance Teams: User validation enhances AI-driven threat detection, reducing false positives and improving response accuracy. An AI model that never learns from its users is already outdated. The best AI isn’t just trained -- it continuously evolves.