Mobile User Experience Best Practices

Latency is death by a thousand cuts. So, fix it. Here are 5 proven ways: 1. Fix Your Database Queries A single poorly written query can add 500ms without you even noticing. Multiply that by thousands of requests, and you’ve got a disaster. Slow queries = slow product. - Stop running SELECT *. - dd indexes. - Kill N+1. - Measure, don’t guess. (EXPLAIN is your best tool) 2. Cut Network Hops Every time a request bounces from Service A → Service B → Service C → Service D... You’re adding latency. - Collapse small services where it makes sense. - Check backend-for-frontend (BFF) 3. Cache Frequently Used Data If data doesn’t change, why fetch it again? Sessions. Catalogs. Config. Keep it hot. Serve it fast. Stale cache is bad. But most of the time, no cache is worse. 4. Batch & Parallel Requests Latency stacks up when you send multiple small requests sequentially. Don’t make 10 trips for 10 items. Batch them. Or go parallel. Fewer requests. Faster results. 5. Reduce Data Transfer Sending too much data is like delivering a truckload when you only needed a backpack. - Strip unused fields. - Compress responses. - Paginate results. - Optimize images. Speed isn’t just a feature. It’s the foundation of user experience. Comment with your worst latency story. And share this with that engineer who thinks another microservice is the answer. 😉

Did you know 75% of smartphone interactions come down to just scrolling your thumb on a touch screen? This means people don’t want to need both hands to navigate a mobile site. They want everything to be a thumb tap away. If your site is a hassle to use on mobile, people just won’t use it. As you think about designing your site, consider what thumb-only navigation, or "Thumb Zones," might look like. “Thumb Zones” are where users are most comfortable and likely to take action on a mobile device. You can see this in the diagram below (courtesy of Branding Brand), and includes the following: → Primary CTAs (like "shop now") in the primary zone. → Essential information and secondary CTAs (like “learn more” instead of “shop now”) in the secondary zone. → Controls to change the mode or initiate different tasks (including search, privacy policies, and navigation menus) in the tertiary zone. This reduces friction by establishing a hierarchy, keeping the subconscious engaged and it maximizes the “tappability” of your content. Now think about your current post-click landing pages and checkouts, would you change anything?

Product managers & designers working with AI face a unique challenge: designing a delightful product experience that cannot fully be predicted. Traditionally, product development followed a linear path. A PM defines the problem, a designer draws the solution, and the software teams code the product. The outcome was largely predictable, and the user experience was consistent. However, with AI, the rules have changed. Non-deterministic ML models introduce uncertainty & chaotic behavior. The same question asked four times produces different outputs. Asking the same question in different ways - even just an extra space in the question - elicits different results. How does one design a product experience in the fog of AI? The answer lies in embracing the unpredictable nature of AI and adapting your design approach. Here are a few strategies to consider: 1. Fast feedback loops : Great machine learning products elicit user feedback passively. Just click on the first result of a Google search and come back to the second one. That’s a great signal for Google to know that the first result is not optimal - without tying a word. 2. Evaluation : before products launch, it’s critical to run the machine learning systems through a battery of tests to understand in the most likely use cases, how the LLM will respond. 3. Over-measurement : It’s unclear what will matter in product experiences today, so measuring as much as possible in the user experience, whether it’s session times, conversation topic analysis, sentiment scores, or other numbers. 4. Couple with deterministic systems : Some startups are using large language models to suggest ideas that are evaluated with deterministic or classic machine learning systems. This design pattern can quash some of the chaotic and non-deterministic nature of LLMs. 5. Smaller models : smaller models that are tuned or optimized for use cases will produce narrower output, controlling the experience. The goal is not to eliminate unpredictability altogether but to design a product that can adapt and learn alongside its users. Just as much as the technology has changed products, our design processes must evolve as well.

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

AI is killing the UX Design role as we know it. Designers who adapt will evolve into Strategic Experience Architects who will be in high demand. While traditional designers are "pixel-pushing," a new set of designers is emerging.  They're using AI to fast-track design ideas and turning prototypes into working code. A lot of what UX designers are doing manually today is exactly what AI tools are getting good at: • Rapid wireframing concepts • UI component creation • Basic user research • Persona development • Usability testing automation The ability to automate some UX tasks is already here. We have to assume that the technology will only advance quickly. I recently spoke with several Product Managers who are already replacing basic UX tasks with AI tools. When PMs can generate, iterate, and validate designs using AI, what happens to the traditional UX role? Simple products and startups will streamline. PMs with AI will be able to handle the basics. We're already seeing this shift. However, there's a big opportunity here as well. AI has a critical blind spot: it can't grasp the nuanced psychology of human behavior. It can't navigate complex stakeholder dynamics. It can't translate business objectives into meaningful user experiences. This is where the evolution happens. The future belongs to Strategic Experience Architects who: ✦ Define the right problems to solve ✦ Extract insights from human complexity ✦ Align teams around user value ✦ Guide AI with human context The market is splitting: → Basic products: UX roles blend into other roles on the team → Complex enterprises: Strategic UX roles become critical Fortunately, most valuable products are complex and human-centered. Want to stay relevant? Here's what to consider. 1. Master AI design tools   But don't just use them, learn to orchestrate them 2. Evolve from maker to strategist   Your value is in thinking, not in pushing pixels (AI will eventually handle this) 3. Develop business intelligence   Connect user needs to revenue 4. Study human psychology    This is your moat against AI 5. Learn systems thinking Focus on developing repeatable systems in your daily work The UX industry isn't dead, but it is transforming. -- ♻️ Share if you think this will help others ➕ Follow Jason Moccia for more insights on AI and Product Design

Lyft knew they had a problem. Only 5.6% of its users are over 65, and those users are 57% more likely to miss the ride they ordered. So, Lyft created Silver – a special app version for seniors. But why create a separate app when these improvements would benefit all users? The curb-cut effect is real. Features designed for wheelchair users ended up helping parents with strollers, travelers with luggage, and delivery workers with carts. The features in Lyft's senior-friendly app wouldn't only benefit older riders: 💡The 1.4x larger font option? Great for bright sunlight, rough rides. 💡Simplified interface? Less cognitive load for all of us. 💡Live help operators? Great for anyone when there's a problem. 💡Select preference for easy entry/exit vehicles? Not everyone likes pickup trucks. What started as an accommodation should became a universal improvement. The most powerful insight? Designing for seniors forced Lyft to prioritize what truly matters: simplicity and ease of use. Will they leverage this for all their users? The next time someone suggests adding another button to your interface or feature to your product, consider this approach instead: sometimes the most innovative design is the one that works for everyone. Rather than creating separate "accessible" versions, what if we just built our core products to be usable by all? This is the paradox of inclusive design - what works better for some almost always works better for all. What "accessibility" feature have you encountered that actually made life better for all users? #UniversalDesign #ProductThinking #CustomerExperience

Design decisions benefit more from behavioral user experience metrics. Involving your audience in the design process gives you real-time feedback on key aspects of their experience. Tools like Helio can help you capture valuable insights that improve your business KPIs, guided by user experience metrics. Using usability tests and surveys lets you quickly gather qualitative and quantitative user feedback. Behavioral data collected early in the design process helps you understand a design's success. Emotional indicators are usually trailing, as confusion or lack of clarity can lead to drops in sentiment and feelings. Here’s the user feedback you can collect to help refine your design decisions with stakeholders: Usability → Makes sure users can easily and quickly use the product to do what they want. Comprehension → Ensures users understand the product, how it works, and what it can do for them. Engagement → Tracks how often and how long users interact with the product, showing their interest and involvement. Desirability → Checks how attractive and appealing the product is to users, affecting their initial and ongoing interest. Viability → This examines whether the design is practical, sustainable, and aligned with business goals for long-term success. Completion → Measures how often users successfully finish tasks or reach goals, showing how effective the product is. Sentiment → Collects overall feelings and attitudes about the product to understand user satisfaction and loyalty. Feeling → Describes users' emotions when using the product, which can affect their overall experience and willingness to stick around. Response Time → Measures how quickly users responds, affecting user satisfaction and perceived performance. Reaction → Captures users' immediate emotional responses, providing quick insights into their first impressions and perceptions. Considering user experience in each design decision offers many benefits: It makes decisions clearer for stakeholders, speeds up decision-making, quickly identifies user pain points, and establishes a baseline for ongoing improvement. We use these metrics to help us improve business results using iterative design and continuous research. What are your thoughts? #productdesign #productdiscovery #userresearch #uxresearch

"Mother Mary," the engineer blurted out. "396 milliseconds." The room erupted. They'd just shattered the 400-millisecond barrier—what IBM researchers called the "Doherty threshold." Here's why it mattered: For 14 years, the computing world believed users needed 2 seconds of response time. The thinking? People needed time to process their next move. Dead wrong. In 1982, IBM discovered that when systems respond in under 400 milliseconds, something magical happens. Users stay glued. Their productivity soars. They enter a flow state that lasts for hours. Cross that threshold? Their minds wander. The spell breaks. The implications were staggering: ✓ Google found that a 500ms delay = 20% drop in searches ✓ Shopzilla increased revenue 12% by speeding up from 7 to 2 seconds ✓ Amazon calculated every 100ms of latency costs them 1% in sales But here's what's wild: This was discovered before the internet, before mobile, before AI, before we carried supercomputers in our pockets. Today? Users expect instant. Touch latency on tablets. Page loads on mobile. Every interaction is judged in milliseconds. The lesson: Speed isn't a luxury. It's the price of admission. Your users' attention is the scarcest resource in the world. Every millisecond you waste is a millisecond they might spend elsewhere. What's your product's response time?

It seems like every day, someone who doesn’t know anything about design proclaims “UI is going away” thanks to advances in AI. The logic goes that soon we’ll just converse with an AI assistant to get everything done. We won’t need any of these pesky menus, buttons, maybe not even screens. But user interfaces aren’t disappearing; they’re evolving. AI makes great UI more important than ever so that we can understand and use it effectively, building better mental models of what this technology can and cannot do. We cannot know AI capabilities and limitations solely from a text box. Let’s stop pretending that a single chat box is the pinnacle of user experience. Conversational AI is powerful, but one size doesn’t fit all for interactions. In many cases, a visual interface is far more efficient and user-friendly than typing or speaking. Consider voice assistants: Alexa was originally voice-only, but even Amazon realized pure voice has limits, hence the Echo Show and devices with screens. Why? Because humans consume visual information faster than spoken information. We can read ~250 words per minute but speak or listen at ~150 wpm. If you ask an AI assistant for the top five movies playing tonight, do you really want to sit and listen as it reads a list aloud? Probably not. The rise of AI is leading new kinds of UI, not a UIpocalypse. We’re already seeing the advent of UI for AI: interfaces designed specifically to harness AI’s power without dumping the burden on the user to craft perfect prompts. Instead of hiding functionality behind a blank text box, give people intuitive controls to direct the AI. Imagine an image editing AI. Rather than forcing the user to type “make the sky brighter and remove the tree on the right,” why not let them click or highlight the parts of the image they want changed? Select a region and adjust a slider, or paint over the object to remove. Tools, not just text boxes. This kind of direct manipulation is often more precise and user-friendly than playing AI Mad Libs with a prompt. AI is also enabling hyper-personalization of interfaces. Rather than one UI to rule them all, AI can tailor the layout, content, and functionality to each user’s needs in real time. Far from disappearing, UIs might become even more present but highly individualized. The future of UX could be one where every interaction is an individualized experience, with interfaces adapting on the fly to a user’s context and preferences. Rumors of UI’s demise are greatly exaggerated. User interfaces are adapting to AI. From multi-modal experiences that blend conversational AI with visual elements, to adaptive UIs personalized by AI, to new design patterns for AI-first products, it’s an exciting evolution. But nowhere in this future does the UI vanish into a black box. Good UI will be a competitive advantage and a key to unlocking AI’s potential for users. Read more: https://lnkd.in/esCfwmKz

Slashed a Webflow site's load time from 6.2s to 1.8s Client's reaction: "How did you do this without rebuilding?" The secret? 5 unconventional optimizations. Here's the full breakdown 👇 The site was beautiful but slow. Killing their Google rankings. And losing mobile visitors. The unexpected culprits: → Oversized background images → Unoptimized CMS queries → Multiple font families → Heavy custom code → Nested interactions Here's exactly what we did: 1. Images: → Converted to AVIF → Added lazy loading → Removed unused assets 2. Interactions: → Combined similar ones → Used CSS where possible → Removed scroll-based triggers 3. Code cleanup: → Removed jQuery dependencies → Merged custom scripts → Minified everything The results shocked everyone: → Mobile speed: 1.8s → Core Web Vitals: All green → Mobile conversions: +27% → Bounce rate: -41% Best part? No design changes are needed. Want the same speed gains? DM "Speed Check" for a FREE performance audit. I'll show you exactly what's slowing your site. #webflow #webperf #webdesign #ux ___ Sebastian Bimbi here, your go-to Web-dev. Daily tips & behind-the-scenes. Follow for Webflow mastery. Got questions? Ask below!