Been digging into data analytics lately for our app. Looking at ways to connect user acquisition metrics with actual revenue.
Seems like there’s potential to get more granular with attribution.
Curious what others are doing to bridge that gap between growth and revenue data.
I focus on connecting user IDs to purchase events. That way I can trace back which channels bring in paying users.
Cohort analysis helps too. I look at 30-day retention and ARPU for different groups.
Simple approach but gives actionable insights without getting lost in the data.
Test cohorts not channels. Track which users stick and pay.
Drop the vanity metrics. Focus on customer lifetime value (LTV) by acquisition source.
Set up post-install event tracking. Tag users from each channel. Then measure their revenue over time.
You’ll see which sources bring high-value users vs. those who install and ghost. Helps cut wasted ad spend fast.
For retention, look at key actions that correlate with long-term use. Could be completing onboarding, using a core feature X times in the first week, etc.
Once you know what drives real value, optimize your funnel to push users toward those behaviors. Works better than chasing install numbers.
We switched to event-based tracking last year. Game changer.
Now we can see exactly which actions lead to purchases. Not just installs, but specific in-app events.
For example, we found users who complete 3+ workouts in the first week are 4x more likely to subscribe. So we doubled down on early engagement campaigns.
Also helps with ad spend. We can trace back high-value users to specific ad sets and optimize there.
Takes some setup, but the insights are worth it. Let me know if you want more details on implementation.
We use UTM tags on ads and track in-app events. Helps see which channels bring paying users. Not perfect, but gives us a general idea where to focus.