Metropolis's computer vision system was so frictionless that users often didn't notice it was working. This counter-intuitive problem forced them to add friction, like text notifications, back into the experience to confirm the product was delivering value and build brand awareness.
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Mailtrap invested in creating a streamlined, low-friction onboarding experience, assuming it would significantly boost conversions. The change had almost no impact. They discovered their developer audience valued the product's core utility so much that they were willing to complete extra steps, rendering the simplified UX improvements ineffective for conversion.
The obsession with removing friction is often wrong. When users have low intent or understanding, the goal isn't to speed them up but to build their comprehension of your product's value. If software asks you to make a decision you don't understand, it makes you feel stupid, which is the ultimate failure.
The "Owner's Delusion" is the inability to see your own product from the perspective of a new user who lacks context. You forget they are busy, distracted, and have minimal intent. This leads to confusing UIs. The antidote is to consciously step back, "pretend you're a regular human being," and see if it still makes sense.
When facing a "brick wall" where user perception contradicts data (e.g., feeling ad load is high when it's low), incremental changes fail. The solution is to re-architect the experience from first principles. This can unlock growth in key metrics like ad load while simultaneously improving user satisfaction.
Customers often rate a service higher if they believe significant effort was expended—a concept called the "illusion of effort." Even if a faster, automated process yields the same result, framing the delivery around the effort invested in creating the system can boost perceived quality.
Despite a clunky, multi-screen setup requiring users to copy and paste API tokens, 80% of early adopters completed the process. This incredible tolerance for friction was an undeniable signal that they were solving a desperate need in the market.
Figma learned that removing issues preventing users from adopting the product was as important as adding new features. They systematically tackled these blockers—often table stakes features—and saw a direct, measurable improvement in retention and activation after fixing each one.
Because AI products improve so rapidly, it's crucial to proactively bring lapsed users back. A user who tried the product a year ago has no idea how much better it is today. Marketing pushes around major version launches (e.g., v3.0) can create a step-change in weekly active users.
Businesses often fail to spot points of friction in their own customer journey because they are too familiar with their processes. This "familiarity bias" makes them blind to the confusing experience a new customer faces. The key is to actively step outside this autopilot mode and see the experience with fresh eyes.
