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This page defines every number on the Analytics dashboard. The same numbers come back from the Analytics API.

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Periods and Time Zones

Every view takes a range: Days and hours follow the app’s time zone, an IANA name such as Europe/Istanbul. It is UTC until you change it in the app’s Analytics settings (or with PATCH /v1/analytics/apps/:appId/settings). Changing it moves the day boundaries of every view, including past days.

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Previous-period comparison

Each KPI shows its value for the previous period and the relative change.
  • The previous period has the same length and ends where the current one starts.
  • It is compared over the same elapsed time. “Today” until 14:00 is compared with yesterday until 14:00, not with all of yesterday. For 7d, the 7 days before are compared up to the same time of day.
  • change is (value - previous) / |previous|, so 0.12 means +12%. It is empty when the previous value is 0 or missing.

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KPIs

Revenue is counted when it happens, while installs and install → paid are counted for installs first seen in the period. A purchase today from an install made last month adds to today’s revenue but not to today’s install → paid conversion.

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Filters

Click a row in any breakdown to filter the whole dashboard by it. With the API, add filter=<dimension>:<value>.
  • Filters are repeatable, up to 4. Each filter narrows the results further.
  • ~none matches installs with no value, for example filter=campaign:~none.
  • Filters apply to installs. Every metric is then counted only for installs that match.
With any filter, revenue only counts customers linked to a matching install. Unattributed sales (no linked install) drop out, so filtered revenue can add up to less than unfiltered revenue.

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Breakdowns

Each breakdown is a ranked table of up to 50 rows, with a count and the revenue linked to each row.
  • Revenue on a row uses the dimension of the install that paid, so a purchase this week from an install made last month shows on that install’s source and campaign.
  • Sales with no linked install show on an empty row (“Unattributed” for source).
  • country, device and version are values stored on the install. The country comes from the network location of the device’s request when available, otherwise from the device locale.

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Screen revenue counts a sale more than once

A purchase counts toward every screen the buyer saw before it. If a buyer saw Onboarding, Paywall and Settings before paying $10, each of those rows gets $10. Screen revenue therefore adds up to more than total revenue. Use it to compare screens, not to sum revenue.

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Funnel

An ordered funnel for installs first seen in the period.
  • A step is an event name (first_open, trial_started, onboarding_completed) or a screen view written as screen:<name> (screen:Paywall).
  • A saved funnel has 2 to 6 steps. A funnel passed with steps can have up to 6.
  • Each step must happen at or after the time the install first reached the previous step. Steps can happen after the period ends.
  • Each step shows the number of installs that reached it, the share of the first step, and the share of the previous step.
The default funnel is:
Save your own steps in the app’s Analytics settings (funnel), or pass steps=a,screen:B,c to the API to try a funnel without saving it. GET …/event-names lists the event names and screens seen in the last 30 days, to pick steps from. trial_started and trial_converted come from RevenueCat, so they only count for installs linked with identify.

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Retention

Cohorts of installs by the day or week they were first seen, and the share of each cohort that was active in each later day or week.
  • Period 0 is the cohort’s own day or week. Period 1 is the next day or week, and so on.
  • A user is active in a period when the install sent any app event in it. Sale events do not count.
  • Periods that have not started yet are empty.
  • The last period is partial: it is still running, so its values will grow until it ends.

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LTV

Revenue within 1, 7 and 30 days of install (D1, D7, D30) for installs first seen in the period, grouped by all, source, campaign, keyword, country, device or version.
Maturity rule: a window only counts installs that are at least that many days old. An install from 3 days ago counts for D1 but not yet for D7 or D30. When no install is old enough, the window’s LTV is empty instead of a misleading low number.