The easiest analytics. Try it now.Your app just shipped. Now what?
The launch-day high fades fast, and that's when the real work starts. Is anyone actually coming back, where are they getting stuck, what do they want? This is exactly where a serious, enterprise-grade product gets built.
Launch isn't the finish line, it's day one
It's live on the store, the announcement went out, the team celebrated. Then what? For most teams, the honest answer is: not much. But that's exactly where the real work begins. What does a user do the first time they open the app, do they come back on day two, where do they get stuck and bounce? A team that isn't watching this is trying to grow a product blind. Launch day isn't a finish line, it's the first day you start measuring.
Watch first, interpret second
Watching user behavior doesn't mean obsessively tracking every click. It means having the data to ask the right questions: where does the user flow break down, which feature nobody touches, which screen is the one that pushes people out of the app. That's exactly why we built tigr. The SDK collects the core events automatically, and you can add your own custom events in a few lines. What comes out the other end isn't a pile of charts, it's a plain-language summary of what's actually happening.
Conversion doesn't end at the signup form
Signup numbers look nice, but on their own they mean nothing. The real question is: does someone who signs up actually start using the product, are they still there a week later? Without activation and retention, growth is an illusion. Seeing this means tracking the user flow end to end: how many people who sign up reach their first real value, how many are still active in week two. That's what tigr's flow view is for, showing the user's actual journey as it happened, not as you'd guess it.
Feedback isn't a survey, it's a process
Sending a single satisfaction survey a week after launch isn't collecting feedback, it's checking a box. Real feedback is a continuous process: reading support tickets, in-app comments, the moments people give up, and why. The hard part is that most of these signals are scattered and qualitative. That's exactly why tigr's AI digest layer exists, it combines the numbers with the narrative so the team can answer "what should I look at this morning" every single day.
Being a serious product starts with building process
What turns a side project into an enterprise-grade product isn't one big feature, it's repeatable process. A team that reviews metrics weekly, a system that alerts on anomalies, a culture that grounds roadmap decisions in real user data instead of "I think this is how it goes". None of this requires a large data team. With the right tool, even a small team can operate with the discipline of a much bigger company.
Grow with data, not by guessing
Shipping is the easy part. The hard part is not letting up on listening to your users, reading the data, and deciding based on it over the next three months. That's where tigr's job kicks in: remove the technical complexity so your team can spend all its energy on making the right calls. You already had the launch-day celebration. Now it's time for the real work.
The easiest analytics on the market. Add it, see the difference instantly.
No code maze, no data team, no charts to decode. Just add the SDK and let tigr watch it for you and tell you what happened.
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