UX And Behavioral Economics

You don’t need better UX. You need fewer decisions 🚀 Founders love to say their product needs “better UX.” So they bring in designers to polish onboarding, clean up the UI, or add clever microcopy. But the core problem remains the same: using the product still feels like work. If you look at most products today, they feel like decision trees (especially SaaS tools). They’re packed with small choices: → Which plan should I pick? → Do I need this setting? → What happens if I click that? And while each little decision seems harmless on its own, they add up and the product starts feeling more like a quiz than a tool. One of my biggest hacks as a designer was to learn that you need to design for the laziest, most impatient user possible. If it works for them, it’ll work for anyone. The old playbook said: “Make decisions easier.” The new one says: Only present decisions when they matter. Default the rest. Automate what you can. The goal isn’t to eliminate choice but reduce the ones that don’t add value. Give users control when it matters, not when they’re just trying to get something done. Good UX isn’t about more clarity. It’s about less cognitive load. The moment you start realizing that, everything changes. That’s also how we try to design at Lovable. When users build with our AI, we try to handle as much as possible in the background. While most tools expect you to set up everything manually, we flip the model. You describe what you want & we handle the rest for you. Based on pure intend. → Want a dashboard? Say it. → Need Google login + Supabase? Say it. → Ready to publish? Just say it. You chat & Lovable builds. And it’s not just UI, we handle logic, backend, and integrations too. Think about products that feel effortless in your day to day. They constantly make smart choices for you: → Apple Pay defaults to your most-used card → Notion AI suggests starting points → Linear pre-fills fields based on context That’s not just “good UX.” It's context-aware UX. OpenAI’s new agent is another perfect example. You don’t click through menus or tweak settings. You just say: “Book me a flight to Berlin next Thursday.” And it’s done. People don’t want more options. They want faster outcomes. They want control without the effort. So here's my take: Great UX means reducing decisions. Hiding complexity and making the product feel like it already knows what the user wants. Because the less someone has to think, the faster they can move. And the best products in the world don't just pretend to look smart, but act smart. If your product still feels like work, it’s not a UX problem. It’s a decision problem. So design for fewer choices and smarter defaults. Super excited to hear your take. Comment below!

In 2018, Michael Kirchler and Stefan Palan ran two real-world field experiments. 𝟭. 𝗜𝗰𝗲 𝗰𝗿𝗲𝗮𝗺 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁 (𝗼𝗻𝗲-𝗼𝗳𝗳 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀) — Customers ordered ice cream under three conditions: * Normal: just ordering * Compliment: “You have the best ice cream in town” * Tip: a small tip given before preparation 𝟮. 𝗗𝗼𝗻𝗲𝗿 𝗸𝗲𝗯𝗮𝗯 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁 (𝗿𝗲𝗽𝗲𝗮𝘁𝗲𝗱 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻𝘀) — Customers returned to the same vendor for 5 consecutive days, again under: * Normal * Compliment * Tip 𝗞𝗲𝘆 𝗙𝗶𝗻𝗱𝗶𝗻𝗴𝘀: 𝟭. 𝗖𝗼𝗺𝗽𝗹𝗶𝗺𝗲𝗻𝘁𝘀 𝘄𝗼𝗿𝗸 — 𝗶𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲𝗹𝘆 * Salespeople gave more food after receiving a compliment. * Effect is statistically strong and consistent across settings. 𝟮. 𝗧𝗶𝗽𝘀 𝗮𝗹𝘀𝗼 𝘄𝗼𝗿𝗸 — 𝗯𝘂𝘁 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗹𝘆 Tips triggered larger immediate increases in food weight. However, once you account for the cost of the tip, customers often did not get full value back. 👉 𝗠𝗼𝗻𝗲𝘆 𝗯𝘂𝘆𝘀 𝗿𝗲𝗰𝗶𝗽𝗿𝗼𝗰𝗶𝘁𝘆, 𝗯𝘂𝘁 𝗶𝘁’𝘀 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲. 𝟯. 𝗧𝗵𝗲 𝗺𝗼𝘀𝘁 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗶𝗻𝘀𝗶𝗴𝗵𝘁: 𝘁𝗶𝗺𝗲 * Compliments compound over time * Each visit with a compliment led to more generosity than the last. * Roughly +5g more per visit in the doner experiment. * Tips do not compound * The effect of tipping stayed flat (or even weakened). * No learning, no escalation. 👉 𝗜𝗺𝗺𝗮𝘁𝗲𝗿𝗶𝗮𝗹 𝗴𝗶𝗳𝘁𝘀 𝗰𝗿𝗲𝗮𝘁𝗲 𝗮 𝗿𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗶𝗻𝗴 𝗿𝗲𝗹𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗹𝗼𝗼𝗽. 𝗠𝗼𝗻𝗲𝘁𝗮𝗿𝘆 𝗴𝗶𝗳𝘁𝘀 𝗱𝗼𝗻’𝘁. In sum, money answers: “Is this worth my time?” Recognition answers: “Am I valued here?” Monetary rewards influence behavior. They don’t necessarily build engagement and commitment.

When I worked on Google Pay, we had the opportunity of having Daniel Kahneman, better known as the author of “Thinking Fast and Slow” advising us. By focusing on creating delight, we outpaced other payment apps with only ¼ the marketing spend, and only ¼ as many features as the competition. Here’s how we did it. Nobody at the time thought of payments as an activity that could be fun, or delightful. It was just something that you had to get done, and be over with as quickly, and cheaply as possible. That’s why all the fintech companies were competing to provide more features, better integrations, lower fees, and faster payments. But eventually, everyone starts hawking the same features, and margins start trending to zero. Worse, Google Pay was a latecomer to the payments space! We had nowhere near the same number of features that other payment apps offered. We knew that we couldn’t possibly compete on rational factors alone. Instead, we set out to design the most delightful payments experience of all. In the words of Marie Kondo, we wanted to create moments that could “spark joy” for users. 𝟭) 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗔𝗳𝗳𝗲𝗰𝘁 𝗧𝗵𝗲𝗼𝗿𝘆 Unexpected good outcomes feel better to our brains. Each time someone paid with Google Pay, they would get a reward in the form of a virtual scratch card. It would reveal either a variable cashback amount or discounts. We turned payments from a painful, dull activity into a delightful surprise. This not only kept people coming back to Google Pay for the dopamine hits, but they even started creating video tutorials on YouTube to tell people about it. 𝟮) 𝗥𝗲𝗰𝗶𝗽𝗿𝗼𝗰𝗶𝘁𝘆 Payments are embedded within human relationships, like splitting a bill from a night out with friends. People feel obligated to return favors. So, we designed a referral program in which both the referrer and the new user, would get a reward for using the app to make payments to a new contact. Existing users started to nudge everyone in their friends and family circles to start sending money to each other using Google Pay. We turned Google Pay into one of the most prominent mobile payment apps in India, and even other countries like Canada, and the US. I’m trying to do the same for personal finance. Today, tracking your net worth, spending, investments, and planning for certain financial goals is dull, overwhelming, and a hassle. I believe there’s a better way. Why can’t it be as delightful as tracking your workouts, or leveling up a character in a video game? If you’re interested to know more, check out our beta program in the comments below!

I think we’re measuring the wrong stuff… and it’s quietly killing momentum. 2026 has to be the year we fix it. Impressions. Clicks. MQLs. “Engagement.” The real game is happening in DMs, Slack threads, forwarded newsletters, and meetings. Here are 6 metrics I’d focus on in 2026 GTM (and why they matter). 1) Conversations → conversions What it is: Of the conversations your content starts, how many turn into a real next step (intro, meeting, opp). Why it matters: Content doesn’t “generate leads.” It generates conversations. Pipeline comes from what you do next. How to track: Tag every inbound convo (DM/email/reply) and mark the outcome: no fit / nurture / meeting / opp. 2) REAL ICPs engaging with content What it is: Not “engagement.” Engagement from the right people (titles, seniority, company tier, intent). Why it matters: 1 CFO at a target account > 1,000 random likes. How to track: Maintain an ICP list (titles + account tiers) and measure: % of engagers who match ICP of target accounts engaged per week repeat ICP engagers (X touches in 30 days) 3) Brand mentions inside ICP-relevant conversations What it is: How often your brand comes up when your ICP is discussing the problem you solve (not when you post). Why it matters: This is the difference between “content that performs” and a brand that gets recommended. How to track: Collect signals: customer calls (“we heard about you from…”), community moderators, partner chatter, dark social screenshots, and sales intel. Even a simple monthly “mention log” works. 4) Conversation velocity What it is: The speed from publish → first qualified conversation, and from convo → meeting. Why it matters: Velocity is the earliest indicator your messaging is landing. If it’s slow, you’re not sharp enough yet. How to track: time-to-first-ICP-convo after a post/report time-to-meeting after first touch “conversation depth” score (comment → DM → problem share → meeting ask) 5) Brand + category position What it is: Are you being associated with a clear “lane” (category/point of view) or just “a vendor who posts”? Why it matters: In 2026, positioning is distribution. If people can’t summarize your POV in one sentence, you’re invisible. How to track: Quarterly “message recall” check: ask prospects/customers: “What do we do?” “What do we believe?” “What are we known for?” 6) Dark social + word-of-mouth What it is: The off-platform sharing that actually drives deals: forwards, screenshots, Slack drops, “my friend sent me this.” Why it matters: A huge percentage of B2B buying happens in private. If your GTM can’t see dark social, you’re flying blind. How to track: “How did you find us?” (mandatory field) inbound screenshots / Slack mentions private replies after posts If your 2026 GTM dashboard doesn’t include conversations, ICP quality, dark social, and category position, it’s going to keep optimizing for attention… while someone else captures intent.

When someone lands on your site, every extra word, button, or menu is a cognitive tax. Take this landing page comparison: Attio - keeps the load light • One navigation bar • 12 words in total for the header + sub-header • 9 clickable exits above the fold • Lots of whitespace • Sneak peak at product imagery The result = focus 🧘♀️ HubSpot - seems to have many cooks in the kitchen • Two navigation bars at the top • 50% more words (24 words in the header + subheader) • 13 clickable exits above the fold • Bigger chat widgets • Lifestyle imagery instead of whitespace The result = distraction 🐿️ With busier pages comes higher cognitive load, the paradox of choice, and decision paralysis 🧠 In real terms: if someone pauses even a split second more and doesn’t act, they’re more likely to bounce. And this isn’t just true for landing pages - it applies to pricing pages, homepages, dashboards… anywhere with competing priorities 👩🍳 👩🍳 👩🍳 It’s easy to add, hard to cut. ✂️ Good design isn’t what you add, it’s what you remove (or don't add in the first place). So ask yourself: What's the 30% you can remove from your page? 🗑️

🚀 #LinkedInGrowth - The #LinkedIn is saturated with people selling “growth hacks.” The uncomfortable truth: no one actually understands the algorithm end to end. Most advice is recycled folklore, outdated tests, anecdotal wins, or short-lived spikes mistaken for strategy. Based on direct observation across thousands of posts in 2025–2026, the algorithm consistently rewards three things: relevance, demonstrated expertise, and genuine conversation within your professional graph. Not viral reach. Not theatrics. 💡 You don’t need to stand out to everyone. You need to stand out to the people who matter in your niche. LinkedIn evaluates your content primarily against your 1st- and 2nd-degree network, shared industries, and topical authority, not the entire platform. Growth is contextual, not global. What actually moves the needle: 1️⃣ Comments now outperform original posts. Thoughtful comments (15+ words) from relevant professionals often generate 2–5× the reach of likes. Comments drive dwell time, signal credibility, and travel deeper into niche feeds. → Five to ten substantive comments per day in your domain will outperform random posting. 2️⃣ Depth beats volume, every time. The algorithm tracks engagement quality: long comments, threaded discussion, saves, and shares with context. Ten real conversations outperform 500 drive-by reactions. Engagement bait (“Comment YES”) is now, at best, neutral—and often penalized. 3️⃣ Consistency matters—but only within a clear niche. Two to five posts per week are sufficient. What matters is topical focus. Stick to your lane. Authority signals compound when your content reinforces a coherent narrative of expertise. Text posts and carousels routinely outperform flashy formats when they spark genuine discussion. 4️⃣ Conversation design, not applause. Strong opening lines and experience-backed insights win. Ask questions that invite expertise, not agreement. Respond quickly, especially in the first hour. Early interaction materially boosts distribution. 5️⃣ Reciprocity is not optional. Engage first. The algorithm favors mutual visibility within professional clusters. When respected peers comment on your posts, distribution expands—organically and predictably. 6️⃣ Dwell time is a hard metric. Optimize for it. External links suppress reach. If you must share one, place it in the comments. Native text, documents, and carousels consistently generate longer session time and better reach. 7️⃣ Your profile is part of the algorithm. Headline, About section, and experience shape how LinkedIn classifies you. A fuzzy profile leads to a fuzzy distribution. Authority attracts authority. 👉Bottom line: LinkedIn growth in 2026 is not about gaming the system. It’s about being useful, credible, and consistent in your corner of the ecosystem. 🔥 Quality compounds. Noise disappears. #LinkedInGrowth #PersonalBranding #ContentStrategy #ProfessionalVisibility

The number every creator or brand is told to chase might be the exact thing holding them back. Here's the pattern I've seen over and over, across newsrooms and platforms: the accounts that actually last aren't always the ones with the biggest numbers. They're the ones where the comments section has become a place people go to talk to each other, not just to the creator. This is the telling sign: reach is "rented," whereas reciprocity is owned. To be clear, I'm not saying reach doesn't matter as it's usually how people find you in the first place, but reach on its own is a starting point, not a strategy. I've watched creators grow their following into six figures and still feel like they're shouting into a room where no one's talking back. Reach gets people in the door. Reciprocity is what makes them stay in the room. I've sat across the table from creators convinced their next milestone would finally make them feel they had arrived, and let me tell you, it rarely does. Part of the confusion is that follower count, reach, and reciprocity get treated as one thing, when they're three different things. Your follower count is a one-time decision someone made: they opted in, once. It doesn't tell you who's actually seeing your content today, let alone engaging with it. Reciprocity is a different thing altogether: it's not who saw a post, it's who came back on purpose, and who brought someone else with them. Here's why that third one matters more than people think: a follower is a passive audience member until something makes them active. The moment someone replies, or tags a friend, or starts a conversation in your comments, they've gone from spectator to participant - and participants are the ones who keep a community alive when the excitement of a launch or a viral moment fades. A huge follower count with no participation is a room full of people who came to the party and never spoke to anyone. It looks full but it's not alive. That's why reciprocity is the more durable thing to build for. A follower count can't compound on its own (it just sits there) but reciprocity can because every real conversation makes someone more likely to start the next one. The uncomfortable part of my job is telling talented people that the number they're chasing isn't the one that will necessarily make their work durable. The reassuring part is that the real metric - sparking conversation - is something you can be intentional about. Have a different take? Would love to read it in the comments.

Our designer Rishikesh spends an hour every day watching users get stuck. Every morning at 10 AM, he watches session recordings on 4x speed, looking for the moment users pause too long, click the same button twice, or try the same action again. Here’s a tiny example from last week. Users wanted to download their finished deck. But instead of clicking the download button, many of them were typing "download" into the agent. That is a product failure. The user should not have to ask the agent to do something the interface already supports. So Rishi made a small change: when users typed keywords like "download," we automatically surfaced the download button right where they needed it. The result: agent and support requests about downloading dropped to zero. Last month, we caught 14 patterns like this. Most were invisible in our analytics dashboard. This is why we watch users get stuck. Not because we enjoy watching people struggle. Because this is where the roadmap often hides. A support ticket tells you what a user could articulate. A behavior trace tells you what they actually experienced. The best product insights are often not in what customers say they want. They are in what customers keep trying to do despite your product fighting them. Founders/product teams: what is one thing your users keep trying to do that your product keeps fighting them on?

𝗪𝗵𝗮𝘁'𝘀 𝘁𝗵𝗲 𝗽𝗿𝗶𝗰𝗲 𝗼𝗳 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗢𝘃𝗲𝗿𝗹𝗼𝗮𝗱 𝗶𝗻 𝗣𝗿𝗼𝗰𝘂𝗿𝗲𝗺𝗲𝗻𝘁? Cognitive overload happens when the mental effort required to use a system or process exceeds the user’s capacity. In Procurement, this happens when tools are overly complex or poorly designed. 𝗧𝗵𝗲 𝗰𝗼𝗻𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗲𝘀 𝗼𝗳 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗢𝘃𝗲𝗿𝗹𝗼𝗮𝗱 𝗮𝗿𝗲 𝘀𝗶𝗴𝗻𝗶𝗳𝗶𝗰𝗮𝗻𝘁 and range from a persistent operational inefficiency, more errors, low adoption of complex solutions and ultimately a risk for employee burnout. While some level of complexity is inevitable to support advanced functionality, the way tools and workflows are designed plays a crucial role for their usability, how effectively users can engage with them and the level of mental load they create. The Cognitive Load Theory (CLT), introduced by John Sweller in the 1980s, provides a framework for reducing mental strain by focusing on how users learn, process and retain information. The CLT identifies three types of cognitive load and offers insights into how Procurement Systems can be optimised for usability: 1️⃣ 𝗜𝗻𝘁𝗿𝗶𝗻𝘀𝗶𝗰 𝗟𝗼𝗮𝗱 which arises from the inherent complexity of the task or information. In Procurement, examples include multi-dimensional RFP scoring or the authoring of complex contracts and their SLAs. 𝗛𝗼𝘄 𝘁𝗼 𝗵𝗮𝗻𝗱𝗹𝗲 𝘁𝗵𝗶𝘀? Break down and simplify complex tasks into manageable steps using modular workflows, and provide pre-configured templates for common scenarios. 2️⃣ 𝗘𝘅𝘁𝗿𝗮𝗻𝗲𝗼𝘂𝘀 𝗟𝗼𝗮𝗱 stemming from poor system design, irrelevant information or inefficient processes. For example, clunky interfaces, unnecessary workflow steps or dashboards that hide insights under excessive detail. 𝗛𝗼𝘄 𝘁𝗼 𝘀𝗼𝗹𝘃𝗲 𝘁𝗵𝗶𝘀? Minimise Extraneous Load with a functional user interface design, using smart visualisations and streamlining workflows. 3️⃣ 𝗚𝗲𝗿𝗺𝗮𝗻𝗲 𝗟𝗼𝗮𝗱 resulting from the cognitive effort that directly supports learning and mastery. Examples include tooltips, clear guidance, and onboarding processes that make systems easier to navigate. 𝗛𝗼𝘄 𝘁𝗼 𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘁𝗵𝗶𝘀? Enhance Germane Load with role-specific training, embedded tool tips & intuitive help features accelerating user learning. All three types can lead to a reduced capacity of employees to be able to operate effectively and potential negative consequences and mental stress. 𝗖𝗼𝗴𝗻𝗶𝘁𝗶𝘃𝗲 𝗼𝘃𝗲𝗿𝗹𝗼𝗮𝗱 𝗰𝗼𝗺𝗲𝘀 𝗮𝘁 𝗮 𝗵𝗶𝗴𝗵 𝗽𝗿𝗶𝗰𝗲. 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 𝘄𝗵𝗶𝗰𝗵 𝗰𝗼𝗻𝘀𝗶𝗱𝗲𝗿 𝗮 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗱𝗲𝘀𝗶𝗴𝗻 and optimise their cognitive load levels by unveiling tasks step by-step, simplifying design and providing helpful learning features, 𝗵𝗮𝘃𝗲 𝗮 𝗵𝗶𝗴𝗵𝗲𝗿 𝗰𝗵𝗮𝗻𝗰𝗲 𝘁𝗼 𝘁𝘂𝗿𝗻 𝗳𝗿𝗼𝗺 𝗮 𝗵𝗲𝗮𝗱𝗮𝗰𝗵𝗲 𝘁𝗼 𝗮 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗯𝗼𝗼𝘀𝘁𝗲𝗿. ❓How do you think can solutions be humanised to reduce cognitive load. ❓What else helps to generate a good usability and user experience.