UX Design For Customer Support Tools

🌎 Designing Cross-Cultural And Multi-Lingual UX. Guidelines on how to stress test our designs, how to define a localization strategy and how to deal with currencies, dates, word order, pluralization, colors and gender pronouns. ⦿ Translation: “We adapt our message to resonate in other markets”. ⦿ Localization: “We adapt user experience to local expectations”. ⦿ Internationalization: “We adapt our codebase to work in other markets”. ✅ English-language users make up about 26% of users. ✅ Top written languages: Chinese, Spanish, Arabic, Portuguese. ✅ Most users prefer content in their native language(s). ✅ French texts are on average 20% longer than English ones. ✅ Japanese texts are on average 30–60% shorter. 🚫 Flags aren’t languages: avoid them for language selection. 🚫 Language direction ≠ design direction (“F” vs. Zig-Zag pattern). 🚫 Not everybody has first/middle names: “Full name” is better. ✅ Always reserve at least 30% room for longer translations. ✅ Stress test your UI for translation with pseudolocalization. ✅ Plan for line wrap, truncation, very short and very long labels. ✅ Adjust numbers, dates, times, formats, units, addresses. ✅ Adjust currency, spelling, input masks, placeholders. ✅ Always conduct UX research with local users. When localizing an interface, we need to work beyond translation. We need to be respectful of cultural differences. E.g. in Arabic we would often need to increase the spacing between lines. For Chinese market, we need to increase the density of information. German sites require a vast amount of detail to communicate that a topic is well-thought-out. Stress test your design. Avoid assumptions. Work with local content designers. Spend time in the country to better understand the market. Have local help on the ground. And test repeatedly with local users as an ongoing part of the design process. You’ll be surprised by some findings, but you’ll also learn to adapt and scale to be effective — whatever market is going to come up next. Useful resources: UX Design Across Different Cultures, by Jenny Shen https://lnkd.in/eNiyVqiH UX Localization Handbook, by Phrase https://lnkd.in/eKN7usSA A Complete Guide To UX Localization, by Michal Kessel Shitrit 🎗️ https://lnkd.in/eaQJt-bU Designing Multi-Lingual UX, by yours truly https://lnkd.in/eR3GnwXQ Flags Are Not Languages, by James Offer https://lnkd.in/eaySNFGa IBM Globalization Checklists https://lnkd.in/ewNzysqv Books: ⦿ Cross-Cultural Design (https://lnkd.in/e8KswErf) by Senongo Akpem ⦿ The Culture Map (https://lnkd.in/edfyMqhN) by Erin Meyer ⦿ UX Writing & Microcopy (https://lnkd.in/e_ZFu374) by Kinneret Yifrah

90% of engineers using AI coding tools are doing it wrong. They're treating AI like a code monkey. Fire prompt → Get code → Accept all changes → Ship. That's why we see 128k-line AI pull requests that became memes (look this up, it's a fun read). After spending quite a bit of time using AI dev tools, I discovered the real game isn't about generating more code faster. It's about rapid engineering while managing cognitive load. My workflow now: 1. Start with AI-generated system diagrams 2. Ask questions until I understand the architecture 3. Create detailed change plans 4. Break down into AI-manageable chunks 5. Maintain context throughout This isn't coding. It's orchestration. The best engineers aren't typing anymore. They're conducting symphonies of AI agents, each handling specific complexity while the human maintains the vision. Think about it → We're moving from IDEs to "Cognitive Load Managers." Tools that auto-generate documentation, visualize dependencies in real-time, and explain impact before you commit. The future isn't AI writing code. It's AI helping you understand what code to write. The billion-dollar opportunity? Build the tool that turns every engineer into a systems architect who happens to code. We're not being replaced. We're being promoted. Who else sees this shift? #AI #SoftwareEngineering #DevTools #FutureOfCoding #TechLeadership

“Why don’t our customers use the Help Center?” It’s one of the most common frustrations I hear from CS and Support teams. They think: 𝘐𝘵’𝘴 𝘴𝘰 𝘮𝘶𝘤𝘩 𝘦𝘢𝘴𝘪𝘦𝘳! 𝘐𝘵’𝘴 𝘢𝘷𝘢𝘪𝘭𝘢𝘣𝘭𝘦 24/7! 𝘐𝘵’𝘴 𝘳𝘪𝘨𝘩𝘵 𝘵𝘩𝘦𝘳𝘦 𝘪𝘯 𝘧𝘳𝘰𝘯𝘵 𝘰𝘧 𝘵𝘩𝘦𝘮! 𝘚𝘰 𝘸𝘩𝘺 𝘥𝘰 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘬𝘦𝘦𝘱 𝘦𝘮𝘢𝘪𝘭𝘪𝘯𝘨 𝘮𝘦 𝘰𝘳 𝘤𝘢𝘭𝘭𝘪𝘯𝘨 𝘴𝘶𝘱𝘱𝘰𝘳𝘵 𝘪𝘯𝘴𝘵𝘦𝘢𝘥? 𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: most teams think about Help Center usage as an adoption issue. But it’s not about 𝘢𝘥𝘰𝘱𝘵𝘪𝘰𝘯. It’s about 𝘴𝘶𝘤𝘤𝘦𝘴𝘴. Customers won’t adopt your Help Center just because it exists. They’ll adopt it after they experience success with it once. So instead of pushing adoption, we need to engineer success. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝟯 𝘄𝗮𝘆𝘀 𝗜’𝘃𝗲 𝘀𝗲𝗲𝗻 𝘁𝗵𝗶𝘀 𝗱𝗼𝗻𝗲: 𝟭. 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲 𝗶𝘁 𝗶𝗻𝘁𝗼 𝗼𝗻𝗯𝗼𝗮𝗿𝗱𝗶𝗻𝗴. When a customer asks a question, pull up the Help Center with them. Let them see it solve their problem in real time.    𝟮. 𝗨𝘀𝗲 𝗶𝘁 𝗮𝘀 𝗮 𝗹𝗲𝗮𝘃𝗲-𝗯𝗲𝗵𝗶𝗻𝗱. At the end of onboarding calls, when you assign homework, leave them on the exact Help Center articles they’ll need to complete it.    𝟯. 𝗠𝗼𝗱𝗲𝗹 𝘁𝗵𝗲 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳. In support or CS conversations, don’t just answer, show the Help Center article you rely on. When customers see you use it, they’ll start trusting it too. The principle is simple: Adoption doesn’t drive success. Success drives adoption. When your customers experience success through the Help Center (or your AI chatbot), they’ll 𝘱𝘶𝘭𝘭 it into their workflow on their own. And that’s how you scale both support and customer success. Help your customers succeed once, and adoption will take care of itself. #customersuccess

When you're deploying AI agents for a CX function, having a good Knowledge Base is a non-negotiable. Why? When optimized, it can empower your AI agents to deliver fast, accurate responses. When neglected, it can leave customers frustrated and agents underperforming. If you want to make sure your help center actually HELPS, here are 5 strategies you can deploy: 1. Structure your content in a Q&A format with clear headings and concise instructions to make it easy for both customers and AI to find relevant information. 2. Use precise keywords. If you have membership tiers, explicitly say which tier you're talking about. 3. Update content regularly with release dates for new features and remove outdated articles. 4. Use visuals (carefully). Reference images and annotations can improve usability—just make sure you have the bandwidth to keep them accurate. 5. Make agents accessible by providing a clear link to the AI agent channels for when customers need help beyond the answers available to them. A lot of companies view help centers as a nice-to-have but the truth is, the ROI is massive. And if you're thinking of using (or already use) AI agents for your customer support, you need to keep it well maintained so the agents can: → Identify knowledge gaps → Make suggestions to make your documentation easier to understand When your help center is optimized, AI agents can perform at their best, which translates to happier customers and less workload for your team. Read the full article for more strategies we recommend—link in the comments! 👇

“Let me explain the issue again…I was saying…” Does this sound familiar? We’ve all been there: stuck on the phone or chat, explaining the same problem to a new support agent for the third, fourth, or fifth time, feeling unheard. But customer service isn’t just about solving problems. It’s about making people feel heard. Yet, far too often, support interactions feel robotic, cold, and disconnected. You’re bounced between departments. Asked to repeat yourself again and again. Given a ticket number instead of a real solution. And the worst part? No one seems to remember your last conversation. This isn’t just inefficient; it’s deeply frustrating and exhausting, and it shows a lack of empathy. Customer service must go beyond transactions. It should tap into attentive empathy, truly listening to customers, acknowledging their frustrations and cognitive empathy, and offering relevant solutions based on past interactions and emotional context. So how do we do that at scale? OpenAI’s latest update is a step in that direction. ChatGPT can now remember past conversations across sessions. This simple upgrade unlocks a smarter, more empathetic future for customer service. Imagine this: • Your support agent already knows what you’ve been through • They pick up right where you left off • They tailor responses to your preferences and pain points This is what modern, emotionally intelligent service should feel like. And the data speaks volumes: 🔹 76% of customers say repeating themselves is their #1 frustration 🔹 81% prefer brands that personalize the experience With AI memory in play, customer service teams can now: • Offer personalized support journeys • Reduce friction in every interaction • Proactively engage based on past pain points • Build long-term trust through seamless continuity For businesses, this means: • Smarter, AI-powered systems that improve with every touchpoint • Consistent journeys that feel human even when powered by machines • Stronger retention through empathy-led engagement If you’re a forward-thinking company, here’s what to do: • Invest in AI tools with conversational memory • Redesign support flows to feel continuous, not fragmented • Train agents to collaborate with AI as empathy amplifiers • Prioritize data transparency and privacy to build lasting trust Because when customers feel understood, they don’t just stay, they advocate. #AI #ChatGPT #customerexperience #CX #KSA #SaudiArabia

It takes more than just fancy visuals to build impactful dashboards! Here’s what you need to keep in mind: 1. 𝗗𝗲𝗳𝗶𝗻𝗲 𝘁𝗵𝗲 𝗣𝘂𝗿𝗽𝗼𝘀𝗲: What questions should your dashboard answer? Align it with your stakeholder's business goals to ensure its relevance.     2. 𝗞𝗻𝗼𝘄 𝗬𝗼𝘂𝗿 𝗔𝘂𝗱𝗶𝗲𝗻𝗰𝗲: Customize your dashboard to the needs of your end-users. Are they executives looking for high-level insights or operational managers needing detailed data?     3. 𝗞𝗲𝗲𝗽 𝗜𝘁 𝗦𝗶𝗺𝗽𝗹𝗲: Avoid overloading your dashboards. Focus on key metrics and visualizations that provide the most value. Less is often more.     4. 𝗖𝗵𝗼𝗼𝘀𝗲 𝘁𝗵𝗲 𝗥𝗶𝗴𝗵𝘁 𝗩𝗶𝘀𝘂𝗮𝗹𝘀: Use the appropriate chart types for your data like bar charts for comparisons, and line charts for trends. Only use more complex charts if they add something a simple bar or line chart couldn't show.     5. 𝗦𝗵𝗼𝘄 𝗞𝗣𝗜𝘀 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗹𝘆: Group related KPIs next to each other. Always include indicators for what is a good or problematic value. Be transparent about the units. Colors can help to make them better understandable, but don't go too crazy on them.     6. 𝗘𝗻𝘀𝘂𝗿𝗲 𝗗𝗮𝘁𝗮 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆: Double-check your data sources and calculations. Inaccurate data will decrease trust in your data and can lead to poor business decisions. Validate everything you use.     7. 𝗗𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗶𝘁𝘆: Make your dashboard interactive. Allow users to drill down into details, filter data, and switch between views.     8. 𝗧𝗲𝘀𝘁 𝗮𝗻𝗱 𝗜𝘁𝗲𝗿𝗮𝘁𝗲: Gather feedback from your users and iterate. Continuous improvement ensures your dashboard remains relevant and useful over time.     9. 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗲 𝘁𝗵𝗲 𝗡𝗲𝗲𝗱: Check if the dashboard should be created at all. Building it might not be the best course of action if it's only needed for a single time. Keep these tips in mind and you’ll create dashboards that deliver real business value. How do you balance simplicity and detail in your dashboards? ---------------- ♻️ 𝗦𝗵𝗮𝗿𝗲 if you find this post useful ➕ 𝗙𝗼𝗹𝗹𝗼𝘄 for more daily insights on how to grow your career in the data field #dataanalytics #datascience #dashboards #datavisualization #careergrowth

The rapid development of artificial intelligence (AI) is outpacing the awareness of many companies, yet the potential these AI tools hold is enormous. The nexus of AI and emotional intelligence (EQ) is emerging as a revolutionary game-changer. Here’s why this intersection is crucial and how you can leverage it: 🔍 AI can handle data analysis and repetitive tasks, allowing humans to focus on empathetic, creative, and strategic work. This synergy enhances both productivity and the quality of interactions. Imagine a retail company struggling with high customer churn due to poor customer service experiences. By integrating AI tools like IBM Watson's Tone Analyzer into their customer service process, they could identify emotional triggers and tailor responses accordingly. This proactive approach could transform dissatisfied customers into loyal advocates. Practical Application: AI-driven sentiment analysis tools can help businesses understand customer emotions in real-time, tailoring responses to improve customer satisfaction. For example, using AI chatbots for initial customer service interactions can free up human agents to handle more complex, emotionally charged issues. Strategy Tip: Integrate AI tools that provide real-time sentiment analysis into your customer service processes. This allows your team to quickly identify and address customer emotions, leading to more personalized and effective interactions. By integrating AI with EQ, businesses can create a more responsive and human-centric experience, driving both loyalty and innovation. Embracing the combination of AI and EQ is not just a trend but a strategic move towards future-proofing your business. We’d love to hear from you: How is your organization leveraging AI to enhance emotional intelligence? Share your thoughts and experiences in the comments below! #AI #EmotionalIntelligence #CustomerExperience #Innovation #ImpactLab

🧠 𝗗𝗲𝗮𝘁𝗵 𝗯𝘆 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱: 𝗪𝗵𝘆 𝗠𝗼𝗿𝗲 𝗩𝗶𝘀𝘂𝗮𝗹𝘀 ≠ 𝗠𝗼𝗿𝗲 𝗖𝗹𝗮𝗿𝗶𝘁𝘆 We’ve all seen dashboards that look like digital fireworks—colorful charts, heat maps, gauges, KPIs, and slicers… all squeezed into a single view. The 𝘪𝘯𝘵𝘦𝘯𝘵𝘪𝘰𝘯? To impress. The 𝘳𝘦𝘴𝘶𝘭𝘵? Confusion. 🎯 Dashboards are not art projects. They are decision-support tools. And when we try to display 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴, the audience understands 𝗻𝗼𝘁𝗵𝗶𝗻𝗴. Visual clutter creates cognitive overload—leaders spend more time deciphering the dashboard than acting on it. 🔑 𝗛𝗲𝗿𝗲’𝘀 𝗺𝘆 𝗴𝗼-𝘁𝗼 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲: 📌 “𝘖𝘯𝘦 𝘗𝘢𝘨𝘦, 𝘖𝘯𝘦 𝘗𝘶𝘳𝘱𝘰𝘴𝘦.” If your dashboard doesn't answer a specific business question or support a single decision, it's just decoration. ✅ Instead of asking “𝘞𝘩𝘢𝘵 𝘦𝘭𝘴𝘦 𝘤𝘢𝘯 𝘐 𝘢𝘥𝘥?”, ask: “What can I remove to sharpen focus?” “Which chart drives action?” “Is this helping someone decide faster, or just showing off the data?” 🧹 Simplify. Prioritize. Align visuals to the why behind the dashboard. 💬 𝙒𝙝𝙖𝙩’𝙨 𝙮𝙤𝙪𝙧 𝙗𝙞𝙜𝙜𝙚𝙨𝙩 𝙙𝙖𝙨𝙝𝙗𝙤𝙖𝙧𝙙 𝙙𝙚𝙨𝙞𝙜𝙣 𝙥𝙚𝙩 𝙥𝙚𝙚𝙫𝙚? (𝘐’𝘭𝘭 𝘨𝘰 𝘧𝘪𝘳𝘴𝘵: 𝘴𝘱𝘦𝘦𝘥𝘰𝘮𝘦𝘵𝘦𝘳𝘴 𝘧𝘰𝘳 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 🤦♂️) #DataAnalytics #DashboardDesign #DataDrivenDecisionMaking #MISReporting

Designing Effective Dashboards📈📊 (links below) A well-crafted dashboard should be intuitive, efficient, and capable of delivering insightful information. Here is a checklist to ensure you incorporate the key features of effective dashboard design: ✔ Focus on key information. Rather than displaying all available data, identify and present what is most relevant to the dashboard's objectives. ✔ Choose the right visualizations. Opt for charts, graphs, and tables that accurately convey your data in an easily digestible format. ✔ Prioritize the conveyance of insights over the mere presentation of raw data. ✔ Highlight critical data points and insights prominently. ✔ Arrange the content logically for easy navigation. Apply the principle of proximity by grouping related data visualizations close to each other. ✔ Ensure each chart communicates a single, clear message. ✔ Enable detailed exploration through drill-down functionality, allowing users to delve into more specific data by clicking or tapping on visual elements. ✔Test and Iterate 📖 Guides: ✔ What you should know before designing a dashboard (by Mimi) https://lnkd.in/diyVTWbj ✔ Data visualisation principles (by Kamila Giedrojc) https://lnkd.in/dtjZWEnH ✔ You might not need a dashboard (by Irina Wagner, PhD)  https://lnkd.in/daJ-wmaE ✔ Practical rules for better dashboard design (by Taras Bakusevych) https://lnkd.in/djS5Z8ye "Storytelling with Data" by Cole Nussbaumer Knaflic: A must-read for anyone interested in presenting data effectively. Tableau Public: Explore thousands of dashboards for inspiration and learning. https://lnkd.in/g4EXXQtP Dribbble's Data Visualization: For design inspiration and the latest trends in dashboard aesthetics. 🔨 Tools: ✔ Hope UI Admin Dashboard Kit for Figma (by Iqonic Design)  https://lnkd.in/dN45ygit ✔ SaaS B2B Dashboard template for Figma https://lnkd.in/dfnqhHmm 

Dashboard Design Secrets Revealed: How I Helped Fintech Startups Explode 10x Remember that sinking feeling of staring at a dashboard, clueless about what's next? Been there. As a product designer with 5 years under my belt, I've seen countless SMB dashboards that are beautiful...but useless. But what if I told you there's a framework used by industry giants like PayPal and Klarna to turn data into decisions? Introducing the "Focus, Flow, Clarity" Dashboard Framework: → Focus: Laser in on 1-3 key metrics that matter most to your business. No more information overload! → Flow: Guide users through a visual narrative, making insights instantly clear. Think data story, not data dump. → Clarity: Use intuitive design elements and actionable CTAs to turn insights into action. No more guesswork! This framework isn't just theory. I've used it to: → Boost conversion rates by 25% for a payments startup. → Reduce churn by 18% for a crypto exchange. → Help a wealth management app secure $5M in funding. So, how can you apply this framework to your SMB SaaS product? → Identify your 3 north star metrics. What are the 3 things that absolutely must move the needle for your business? → Map your user journey. What are the key steps users take to achieve their goals? Design your dashboard to support that journey. → Clarity is king. Use clean visuals, concise labels, and actionable CTAs to make every pixel count. P.S. Want to see the framework in action? Check out my portfolio (link in bio) for real-world examples! Ready to ditch the dashboard data dump and unlock actionable insights? Let's chat! #dashboards #saasdesign #fintech #web3 #conversionrateoptimization