You shipped to the App Store. The hard question now isn't "did it get approved" — it's "is anyone actually using it." Answer it by checking five things in order: how many real people open the app (not just installs), whether anyone completes the one action that defines your product (activation), whether they come back (retention), where the installs came from, and whether anything converts. You can read all five in a day or two, and most "I have no idea if this is working" launches are really just missing this short list.
Installs are not users
The first number everyone fixates on is the most misleading. An install is a download; it says nothing about whether the person opened the app, let alone used it. Plenty of installs never produce a second session.
The honest headcount is active users. Firebase logs first_open automatically the first time someone launches the app, and tracks engaged sessions and active users from there (Firebase — Automatically collected events). Compare active users to installs: if 2,000 installed and 300 are active, your story isn't "2,000 users," it's "300 users and an 85% drop-off at the front door" — which is a completely different problem to solve.
Did anyone activate
Traffic without action tells you nothing. Every app has one event that means "this person got value" — created the first thing, completed onboarding, sent the first message. That's activation, and it's the most useful number in your first week. Define it as a single event you log with Firebase, then measure it as a rate: of the people who opened the app, what share activated.
If 300 opened and 18 activated, you don't have an install problem, you have an onboarding problem — far more actionable than a download chart. Watch where in the first-run flow people drop; that points you at the exact screen to fix. The mistake to avoid is defining activation as something trivial like "opened the home screen," which inflates the number and hides the problem. Pick the action that genuinely correlates with sticking around, even if the rate looks ugly at first — an honest 6% you can improve is worth more than a flattering 90% that means nothing.
Do they come back
A launch spike is easy; the second open is the real signal. Retention — the share of new users who return on later days, usually measured as day-1 and day-7 retention — separates "people tried it" from "people use it." Firebase's retention and cohort reporting shows next-day and 7-day return rates for each cohort of new users.
Don't over-read day one. Look at whether the D1 and D7 lines flatten into a stable band rather than falling to the floor. An app nobody returns to has a retention curve that collapses fast, no matter how big the launch looked. Retention is also the number that most reliably predicts whether paid acquisition can ever pay back — a 2% day-7 curve will not survive paid installs, no matter how cheap the install.
Where did the installs come from
Knowing people arrived is half the picture; knowing from where tells you what to do next. Some installs are organic App Store discovery, some come from a launch post, some from paid campaigns. Firebase attributes installs to source where it can, and an attribution tool (a Mobile Measurement Partner) fills in the campaign-level detail that Apple's privacy rules otherwise hide — the division of labor covered in Firebase vs AppsFlyer. If organic search in the stores is quietly growing, that's a durable channel; if a single post drove a one-day spike, you'll see it deflate.
Is anything converting
Finally, the bottom of the funnel: did anyone do the thing worth money — subscribe, pay, upgrade. Even pre-revenue, define the purchase event now (with value and currency) so the funnel is measurable the day you turn on payments. Read it as a rate — paid ÷ active users, or paid ÷ trials — because rates stay meaningful as installs grow while raw counts flatter a spike and then look like a collapse. For the full revenue picture, see how to measure mobile ROAS.
Put the five on one screen
Active users, activation, retention, source, and conversion are the entire post-launch dashboard you need in week one — and they're more honest together than any one alone. Activation without retention is a leaky bucket; retention without a source breakdown can't be scaled; conversion without active users is just noise. The friction is that they live in different places: behavior in Firebase, attribution in an MMP, revenue in your store and billing. Pulling them into one normalized view, with the weak spot flagged and a suggested next step, is what VibesFlyer does over MCP or a daily Telegram digest — so "is anyone using it" stops being a feeling and becomes five numbers you check on a Monday. The definitions behind each are in the mobile metrics glossary.