Knowing whether a new product or feature is working is a key part of product management. Research and discovery help you figure out where to go, but a solid data strategy helps you get there—and stay on track.
How measuring feature success fits into your product pipeline
Here’s how feature development usually goes:
- Someone spots a problem or opportunity.
- A PM digs in, talks to users, and defines the problem.
- The team comes up with a solution.
- Stakeholders weigh in, prototypes get refined.
- The feature is scoped, prioritized, built, tested, and shipped.
But there’s something missing here: once it’s live, how do you know if it worked? How do you know it didn’t make things worse?
You could wait for complaints or send out a survey. But that’s more guessing than measuring. And guessing doesn’t help you improve.
What a feature success strategy should include
The best time to plan how you’ll measure success is before you start building. By the time code is written, it’s often too late to go back and figure out what you should’ve tracked.
A good plan includes:
- Understanding what success looks like
- The metric(s) you’ll track
- A tracking plan for the feature (these are usually unique to each one)
This sets you up to answer the key question: Did this feature do what we hoped it would?
A simple example: measuring feature success with data
Let’s say you notice that most users are dropping out of the onboarding flow just seconds after arriving. You assume they’re getting confused and frustrated, and you confirm this through user research. You decide to build a guided wizard that explains each onboarding step as users go.
Here’s how you’d measure if that worked:
- Success metric: Percentage of users who complete onboarding
- Baseline: 10% complete the flow today
What success looks like:
- 20% increase in the first week (10% → 12%)
- Steady weekly growth
- 30% retention within 3 months
What you’d track:
- Where users drop off
- How long they stay on each step
- Which tooltips they click
- Which fields they get wrong and have to re-enter
- Anonymous info like browser, country, and device
- Tracking early usage helps you catch issues fast and make better product decisions. Metabase lets you build dashboards for this with minimal setup.
Use data to build better features
A clear plan for how you’ll measure the success of new products and features helps your team stay focused. It keeps you from flying blind and gives you what you need to make smart changes along the way.
The goal isn’t to be perfect—it’s to learn quickly, fix what’s not working, and keep moving forward. See how other teams use Metabase to do just that.