The reality for most product teams
You're guessing. Or you're digging through Google Analytics for an hour to answer one question. Or you don't bother and decisions stay gut-driven. That's the reality for a lot of teams. They have data somewhere. They don't have data in a form that answers the questions they actually have.
Small teams especially. No dedicated analyst. No one who wakes up thinking about dashboards. The PM has a product to build. The engineer has code to ship. "Can we see how the new flow is doing?" is a reasonable question. It's also a question that might require a new report, a new segment, or a ticket to someone who's already overloaded. So it doesn't get asked. Or it gets asked and the answer comes back two weeks later when the moment has passed.
The result is that product decisions get made without product data. Intuition is fine until it's wrong. And when you're wrong often enough, you start to wish you had a simpler way to know.
The questions product people actually have
Did this change work? Where do people get stuck? Who uses this and who doesn't? Usually straightforward. You don't need a data warehouse to start. You need a way to tie a number to the thing you shipped and see if it moved.
The questions are specific. They're not "give me everything." They're "did the onboarding change improve completion?" or "where do people drop off in the paywall?" or "are people who hit feature X retaining better?" One question, one number (or a small set), one place to look. That's what product people need. Most analytics tools are built to give you everything and let you slice. Product people need a short path to the slice that matters.
If the tool requires you to build a report first, or to learn a query language, or to wait on someone else, the question doesn't get answered. Or it gets answered too late. Tooling built for product questions is tooling that assumes the user is a PM, not an analyst. Different user, different design.
Why traditional analytics tools fall short
They're built for people who write queries and maintain pipelines. They're built for flexibility and scale. That's the right choice when your user is a data team. It's the wrong choice when your user is a PM who needs to know if last week's ship landed.
Product people need answers, not a new skill set. They don't want to learn SQL. They don't want to configure custom dimensions. They want to set a focus, see the number, and when it moves, see what changed. The gap between "powerful and flexible" and "answers the question in under a minute" is huge. Most tools optimize for the first. Product teams need the second.
That doesn't mean the big platforms are bad. It means they're built for a different job. When you have a data team, they're great. When you don't, they're a tax. You're paying for power you can't use and maintaining complexity you don't need.
What we're building
AppFit: analytics that fit how small teams and PMs work. No SQL. No ticket. One focus, a few metrics, a weekly summary, and a product journal so when the number moves you know what shipped or changed. Here's what we built. Here's what happened.
We're building for the team that doesn't have a data person. For the PM who's tired of guessing. For the moment when someone asks "did that work?" and the answer should be a click away, not a sprint away. Product questions deserve product answers. That's what we're building for.
