Multivariate Testing In UX

💎 Accessibility For Designers Checklist (PDF: https://lnkd.in/e9Z2G2kF), a practical set of cards on WCAG accessibility guidelines, from accessible color, typography, animations, media, layout and development — to kick-off accessibility conversations early on. Kindly put together by Geri Reid. WCAG for Designers Checklist, by Geri Reid Article: https://lnkd.in/ef8-Yy9E PDF: https://lnkd.in/e9Z2G2kF WCAG 2.2 Guidelines: https://lnkd.in/eYmzrNh7 Accessibility isn’t about compliance. It’s not about ticking off checkboxes. And it’s not about plugging in accessibility overlays or AI engines either. It’s about *designing* with a wide range of people in mind — from the very start, independent of their skills and preferences. In my experience, the most impactful way to embed accessibility in your work is to bring a handful of people with different needs early into design process and usability testing. It’s making these test sessions accessible to the entire team, and showing real impact of design and code on real people using a real product. Teams usually don’t get time to work on features which don’t have a clear business case. But no manager really wants to be seen publicly ignoring their prospect customers. Visualize accessibility to everyone on the team and try to make an argument about potential reach and potential income. Don’t ask for big commitments: embed accessibility in your work by default. Account for accessibility needs in your estimates. Create accessibility tickets and flag accessibility issues. Don’t mistake smiling and nodding for support — establish timelines, roles, specifics, objectives. And most importantly: measure the impact of your work by repeatedly conducting accessibility testing with real people. Build a strong before/after case to show the change that the team has enabled and contributed to, and celebrate small and big accessibility wins. It might not sound like much, but it can start changing the culture faster than you think. Useful resources: Giving A Damn About Accessibility, by Sheri Byrne-Haber (disabled) https://lnkd.in/eCeFutuJ Accessibility For Designers: Where Do I Start?, by Stéphanie Walter https://lnkd.in/ecG5qASY Web Accessibility In Plain Language (Free Book), by Charlie Triplett https://lnkd.in/e2AMAwyt Building Accessibility Research Practices, by Maya Alvarado https://lnkd.in/eq_3zSPJ How To Build A Strong Case For Accessibility, ↳ https://lnkd.in/ehGivAdY, by 🦞 Todd Libby ↳ https://lnkd.in/eC4jehMX, by Yichan Wang #ux #accessibility

UX Designers, So, you've started using AI to see if you can leverage it to amplify what you can do. The answer is yes, but... If you've never been part of the (SDLC) or (PDLC). You'll get through it, but it won't be easy and not to fun at first. If you're in a well established company with a huge design system. Suddenly adding in AI might make life a real pain. It depends on how adaptive the company and others are. If you're starting something from scratch. Well, now you can do whatever you want to. This is where the fun, frustration and learning comes in. Buckle Up.. To give you an example. I've been working on something and it's almost ready for people to test. I was going through and manually testing the user flows. As something was found. Claude inside of Cursor would find the issue after I point it out. It suggests a fix. I review and approve and continue from there. This was taking a lot of time as you might imagine. So, this morning at 2am with what felt like sand in my eyes. "There has to be a way I can automate this..?" Prompt: As you know. I've been testing the user flows manually, and we've been fixing the issues along the way. Do you know if a way that we can automate this without having to send out various emails, and just do this internally? When you find an issue it gets documented in a backlog and we then work those, and run the test again? I got answers. I selected one I liked (playwright) and combined it with ReactFlow so it was visual. Created a dashboard for it. Long story short. I can now run 100% automated user flow tests, see them in action in real-time, see where the issues are and then go fix them. All done in less than 6 hours and at $0 except for my time. So, can you build something like this with the help of AI? Yes, I did and it fully works. #ux #uxdesigner #uxdesign

The psychology behind CTAs that convert: (5 lessons from billions of emails sent) Your CTA (Call-to-Action) isn’t just a button or a link. It’s the moment where all your effort pays off. But here’s the truth: Most CTAs fail because they don’t consider the psychology behind what drives someone to click. Here are 5 CTA strategies I’ve tested that consistently drive higher conversions (and why they work): 1. Make the action feel easy: Instead of: “Complete Your Registration” I tested: “Get Started in 60 Seconds” Why this works: People avoid tasks that feel time-consuming or overwhelming. A CTA that emphasizes speed and simplicity lowers resistance. 2. Use urgency to create momentum: Instead of: “Sign Up for the Sale” I tested: “Ends Tonight: Claim Your 50% Off” Why this works: A deadline taps into FOMO (fear of missing out), pushing people to act now instead of “later.” 3. Highlight a benefit, not a feature: Instead of: “Learn More” I tested: “See How We Boosted Revenue by 27%” Why this works: People don’t want to “learn”. They want outcomes. A benefit-focused CTA paints a clear picture of the value they’ll receive. 4. Be specific, not generic: Instead of: “Click Here” I tested: “Download Your Free Email Template” Why this works: Clarity builds trust. When someone knows exactly what they’ll get, they’re far more likely to click. 5. Match your CTA to their stage in the journey: Instead of: “Buy Now” on a first touchpoint I tested: “Get a Free Demo” Why this works: Asking for too much, too soon, feels pushy. Tailoring your CTA to where the customer is in their decision-making process creates a smoother path to conversion. --- The Big Lesson: Your CTA shouldn’t be an afterthought. It’s the bridge between interest and action. Small tweaks like emphasizing speed, clarity, or outcomes can make a massive difference. What’s the best-performing CTA you’ve tested? Drop it in the comments.

When a business grows rapidly, the cracks in your processes start to show. That’s exactly what happened to us As our team scaled, it became clear: not everyone understood the hypothesis-generation process in the same way. This caused confusion, inconsistent problem-solving, and slowed down decision-making So, we developed a clear format to align everyone, newcomers and veterans alike, around structured, high-impact hypotheses. It starts with identifying the bottleneck In ecommerce, this might mean noticing that users drop off before completing a purchase The first instinct? "Add trust badges at checkout" But that’s too vague Is the real issue trust? A confusing checkout? Delivery costs? We learned to dig deeper: Problem: Low checkout conversion because users lack trust Action: Add trust badges (e.g., privacy policy, money-back guarantees) Expected result: Increase conversion from 20% to 40% 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 + 𝗔𝗰𝘁𝗶𝗼𝗻 + 𝗘𝘅𝗽𝗲𝗰𝘁𝗲𝗱 𝗥𝗲𝘀𝘂𝗹𝘁 This structure keeps our hypotheses focused and testable We prioritize using the ICE framework (Impact, Confidence, Ease). Doesn’t matter if we sum or multiply the values; the important part is consistent prioritization Then, we hold regular meetings: 1) Prepare hypotheses with a defined problem and goal 2) Refine and discuss existing ideas 3) Only brainstorm new ones when we’ve addressed the current list The result? A ready-to-implement hypothesis that’s documented from start to finish. This documentation becomes gold when reviewing what worked and what didn’t Fast growth demands clarity. Rebuilding internal processes isn’t just helpful, it’s necessary What’s your go-to method for hypothesis generation?

Ever noticed how two UX teams can watch the same usability test and walk away with completely different conclusions? One team swears “users dropped off because of button placement,” while another insists it was “trust in payment security.” Both have quotes, both have observations, both sound convincing. The result? Endless debates in meetings, wasted cycles, and decisions that hinge more on who argues better than on what the evidence truly supports. The root issue isn’t bad research. It’s that most of us treat qualitative evidence as if it speaks for itself. We don’t always make our assumptions explicit, nor do we show how each piece of data supports one explanation over another. That’s where things break down. We need a way to compare hypotheses transparently, to accumulate evidence across studies, and to move away from yes/no thinking toward degrees of confidence. That’s exactly what Bayesian reasoning brings to the table. Instead of asking “is this true or false?” we ask: given what we already know, and what this new study shows, how much more likely is one explanation compared to another? This shift encourages us to make priors explicit, assess how strongly each observation supports one explanation over the alternatives, and update beliefs in a way that is transparent and cumulative. Today’s conclusions become the starting point for tomorrow’s research, rather than isolated findings that fade into the background. Here’s the big picture for your day-to-day work: when you synthesize a usability test or interview data, try framing findings in terms of competing explanations rather than isolated quotes. Ask what you think is happening and why, note what past evidence suggests, and then evaluate how strongly the new session confirms or challenges those beliefs. Even a simple scale such as “weakly,” “moderately,” or “strongly” supporting one explanation over another moves you toward Bayesian-style reasoning. This practice not only clarifies your team’s confidence but also builds a cumulative research memory, helping you avoid repeating the same arguments and letting your insights grow stronger over time.

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).

Should you retarget by intent? We ran the test... Most B2B retargeting looks something like this: Someone visits your site, any page at all…and immediately: they’re getting hit with “Book a demo” or “Start your free trial” ads. No nuance. No context. Just one-size-fits-all messaging chasing every visitor around the internet. It’s simple. It’s easy. But also pretty broken. Here’s why: > Not everyone on your site is in the same headspace. > Blog readers aren’t ready to talk to sales. > Product page visitors are curious but not convinced. And people on the demo page? They’re this close but something’s holding them back. Treating all three the same? That’s how you burn ad dollars without actually building pipeline. So we ran a test. One of our clients had a basic retargeting setup. One campaign. One CTA. One generic message. We broke it apart and rebuilt it based on intent. ___________________________ Here’s how we segmented it: Blog readers Top-of-funnel folks in research mode. → We showed them value-first content: guides, checklists, downloads. Product & feature page visitors Mid-funnel visitors sniffing around the solution. → We served ROI calculators, interactive tools, and “how do you stack up” style CTAs. Pricing/demo page visitors Bottom-of-funnel leads with real buying signals. → They saw direct “Book a demo” and “Start your trial” ads with tons of social proof. ___________________________ Here’s what happened over 60 days: Old campaign (one-size-fits-all): > Low click-through rates (~0.4%) > Modest form fill volume > Demo-to-close rates hovering around 17% New segmented retargeting: > 3.1x higher CTR > 2.4x more total form fills > 29% increase in demo-to-close conversion from high-intent segments ___________________________ Better message-match. Cleaner funnel transitions. Better results.

Heads of sales, service providers who run ads with the aim of more sales.. I've ran ads and helped audited more than 350+ ads in the past 2.5 years for service providers and high ticket sales.. here's what most businesses who run ads do not know 👇 Your Ad ROI Lives or Dies at the CTA Why does this matter? Paid media is expensive real estate. The single line (or button) that tells a prospect what to do next is often the difference between pipeline and polite interest (data backs it up). I've managed to help clients doubled their sales in 1 month just by switching up their CTA even datas backed this : # 1, 90 % of visitors who read your ad’s headline will also read the CTA. Skip the generic “Learn More,” and you squander almost all the attention you just paid for. (Source: constant-content.com) # 2, One unmistakable CTA can lift clicks by 371 %. Too many options create friction; one clear ask channels intent. (Source: saleslion.io) # 3, Context- or persona-based CTAs convert up to 202 % better than one-size-fits-all buttons. (Source: hotjar.com) 1️⃣ Match the CTA to the Buying Moment Push “Buy Now” to a cold audience and you’ll pay premium CPCs for zero sales qualified leads. Fit the ask to their current intent, not your quarter-end quota. 2️⃣ Personalise Around Your ICP Inject buyer-specific language (“See logistics pricing for Klang Valley SMEs”) or dynamic fields (industry, use-case) into the CTA. Platform tests show tailored CTAs are three times likelier to get the click. 3️⃣ A/B Test Like It’s a Creative Element Optimise for revenue, not CTR. A flashy verb can spike clicks and tank lead quality. Follow each variant all the way to closed-won. Feed winners into your marketing automation. Sync the high-converting CTA/offer pair with tailored nurture emails or WhatsApp flows. 𝐃𝐨𝐧'𝐭 𝐣𝐮𝐬𝐭 𝐬𝐭𝐨𝐩 𝐚𝐭 𝐨𝐩𝐭-𝐢𝐧. Also, be as specific as possible - ICP, benefits.. 4️⃣ Track the Metrics That Pay Salaries - not just what looks good (I had have clients who have what looks good but we had to switch to help them get real actual sales - not just likes and "good consistent branding" Click-through rate (CTR) 👉 Early warning signal of relevance/creative fit Lead-to-SQL rate 👉 Shows whether the CTA is attracting qualified prospects Pipeline $ / Lead👉 Tells Finance (or the boss who's paying) the ad is worth funding Closed-won revenue 👉 The only metric that ultimately justifies spend Remember: CTAs Aren’t Always “Buy Now” 𝐐𝐮𝐢𝐜𝐤 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲 Before launching your next campaign, ask: Does the CTA speak my ICP’s language? Does it align with their stage of awareness? Will the landing experience fulfil the exact promise? What's my nurturing sequence? If the answer isn’t a confident “yes,” tweak it because that tiny line of copy is where your ad budget either compounds or disappears. if you need help, reach out to me (although my services aren't for every type of business, I'm more than happy to recommend).

Creating a Automation Framework for Netflix like application from scratch using PlayWright 1) Smart Architecture -> Fixtures-First Design (to introduce reusability) -> Custom auth fixtures with auto session management -> Browser context fixtures for parallel execution -> Data setup/teardown ensuring clean environments 2) Intelligent Data Strategy -> Static JSON for stable scenarios -> Faker.js for dynamic realistic data -> Live API data creation for fresh test conditions 3) Design Patterns That Work -> Factory Pattern: Dynamic test data creation -> Page Object Model: Encapsulated reusable components -> Strategy Pattern: Cross-browser testing -> Singleton: Optimized configuration management 4) Complete API Coverage -> REST APIs (CRUD, auth), GraphQL (queries, mutations), OAuth/JWT flows, Third-party integrations -> API + UI Combo: Live data creation through APIs feeding directly into UI test scenarios. 5) Advanced UI/UX Automation -> Visual regression testing -> WCAG accessibility validation -> Responsive design testing -> Performance metrics (Core Web Vitals) -> Cross-browser compatibility 6) ReUsability -> Components setup -> Custom assertions -> Config management through tsconfig, playwright.config, .env files -> Page Objects -> Data Factories 7) Testing Capabilities -> Cross-browser Testing: Chrome, Firefox, Safari, Edge support -> Mobile Testing: Device emulation and responsive design validation -> API Testing: REST and GraphQL endpoint validation -> Visual Testing: Screenshot comparison and visual regression -> Performance Testing: Load time and network performance metrics -> Accessibility Testing: WCAG compliance validation -> Tech Stack Playwright + TypeScript + Faker.js + Docker + CI/CD + PlayWright default Reports + Git Actions + APIs 🎪 Key Lessons -> Architecture investment scales exponentially -> OOP principles reduce complexity -> API-first approach ensures comprehensive coverage -> Mixed data strategy creates realistic scenarios -x-x- Learn PlayWright with JavaScript/TypeScript from Scratch with E2E Automation Course: #japneetsachdeva

Reddit user tend to ROAST LinkedIn content...calling it "totally cringe" - Here's what to avoid...and what to do different 👇 The feed is packed with “I failed. Then I didn’t.” posts and dramatic “One mindset changed everything” stories...and don't forget the AI agents are taking over everything posts... They get engagement, sure. But here’s the truth: likes don’t build pipeline. Most of that content drives attention, not action. And that’s the difference between vanity content and real demand generation. If you’re serious about growing a B2B brand, your goal isn’t to go viral. It’s to build trust, shape perception, and get remembered when buyers enter an active cycle. Cringe content leads with ego. Effective demand gen leads with value. That starts with: A clear unique value proposition that actually means something to your market A deep understanding of your competitors and how you can position differently A unique point of view that simplifies complex problems in your buyer’s language Step 1: Find your message through organic testing Before you spend a dollar on ads, validate what resonates organically. Create 10–15 short posts or 2–3 videos exploring your POV, pain points, and differentiators. Watch which ones get real engagement from ICPs (not just coworkers and marketers). Pay attention to: Comment quality (Are people asking follow-up questions?) Profile views and inbound DMs Company follower increases The content that hits organically becomes your creative testing lab. Step 2: Scale winning content with paid thought leadership ads Take your best-performing post and turn it into a thought leadership ad. Don’t reword it to sound “ad-like.” Keep the authentic tone that worked. Use single image or video formats and target high-fit audiences built from: Job titles and functions of your ICP Matched audiences from your CRM or website visitors Step 3: Build engagement loops with Conversation Ads Target people who engaged with your thought leadership content using Conversation Ads. The goal isn’t to hard-sell but to guide them deeper. Step 4: Use LinkedIn’s Company Engagement Hub You can now see exactly which companies are engaging with your ads and organic content. Go to Campaign Manager → Company Engagement Report → sort by “Engagement Level.” You’ll see which accounts are warming up. Export that list and: Hand it to your SDR team for warm outbound Upload it to other platforms or into your outbound engine to run cross-platform retargeting Step 5: Close the loop with creative iteration Every 2–3 weeks, analyze which messages and visuals perform best. Ask yourself: What narrative got the most video completions? Which CTA drove the most demos or guide downloads? Which posts created real dialogue in the comments? Double down on those angles, and use your next round of content to build upon what resonated. This is how you compound demand instead of chasing fleeting attention.