Building What Users Actually Need - Lessons from a Year of Iteration
Ever spent weeks, maybe months, building a feature you were sure would wow your users, only to see it land with a resounding meh? It’s the kind of moment that stings. You think you’ve nailed the problem, but what you’ve actually done is build what you thought users needed, not what they were actually asking for.
That’s a hard lesson we learned this year. At Marketrix, we’re building AI to solve a big, messy problem: how to make in-app support actually useful. Think about the frustration of clicking through FAQs, waiting for a chatbot that gives you the same canned answers, or endlessly searching for the button you need. We’re rethinking this experience with AI that doesn’t just respond to questions. It understands the app itself, navigating and guiding users in real time.
But even the smartest AI doesn’t matter if people don’t trust it. Early on, we thought our simulations, the core of how Marketrix works, were enough. They’re designed to explore an app the way a user would, mapping every page, button, and action space. The system builds a deep understanding of the app, so it can guide users without manual scripts or pre-configured paths. It’s powerful stuff. But we hit a wall: no one trusted it because they couldn’t see it working.
So we changed direction. We built a transparency layer that lets users see exactly how Marketrix learns their app, click by click. Suddenly, the “magic” wasn’t hidden, it was right in front of them. And that changed everything.
Then came another lesson. No matter how sophisticated your tech is, users only care about whether it works for them in the moment. Case in point: our AI-driven co-browsing feature. It was intuitive, seamless, and completely invisible. Users kept asking, “Is this thing even doing anything?” We realized the problem wasn’t functionality. It was visibility. The fix? Spotlight mode, a simple tweak that made the cursor more prominent. Engagement spiked overnight.
It wasn’t some groundbreaking feature. It was solving a very human problem: people needed to see what was happening.
And then there’s context. Everyone talks about it like it’s table stakes, but actually delivering it? That’s where the work is. Context-awareness for us means knowing exactly where a user is in their journey, whether they’re stuck on a login screen or buried in the settings menu, and guiding them with tailored, actionable help. It’s what makes support feel intuitive instead of generic. But getting there wasn’t a straight line. It was iteration after iteration, feedback loop after feedback loop, until the guidance felt as seamless as it needed to be.
Looking back, the real lesson of 2024 wasn’t about shipping shiny features or flexing with fancy AI. It was about humility, realizing that no matter how smart you think your product is, your users will always tell you what actually matters. The trick is to listen, adjust, and keep going.
Heading into 2025, we’re not chasing big, splashy milestones. We’re doubling down on the fundamentals, solving real problems, iterating on what works, and cutting what doesn’t. Because at the end of the day, the best products aren’t the ones that impress you with their technology. They’re the ones that quietly, simply, just work. And that’s what we’re building.