---
title: App Metrics Index: 35 Formulas and Definitions
description: Every app metric in one table: CPI, CPA, CAC, activation, retention, churn, DAU/MAU, ARPU, ARPPU, LTV, ROAS, payback and more, with formulas and definitions.
url: https://appmetricslibrary.com/metrics/
---

# All app metrics, A to Z by stage

Formulas and definitions for every metric in the library.

**Short answer**

Every metric in the library on one page: 35 entries grouped by stage, each with its formula and a one-sentence definition. Select a name for the full entry and calculator.

Index

## Which metrics are in the library?

| Metric | Formula | Definition |
|---|---|---|
| Acquisition |  |  |
| [Cpi Cost per install](https://appmetricslibrary.com/metrics/cpi/) | CPI = Ad spend ÷ Attributed installs | Cost per install (CPI) is the average amount an app pays in advertising for each install a campaign drives: ad spend divided by the installs attributed to that spend. |
| [Cpa Cost per action](https://appmetricslibrary.com/metrics/cpa/) | CPA = Ad spend ÷ Actions completed | Cost per action (CPA) is the average ad spend for each user who completes a chosen in-app action, such as a sign-up, a trial start or a first purchase. |
| [Cac Customer acquisition cost](https://appmetricslibrary.com/metrics/cac/) | CAC = Total acquisition cost ÷ New customers | Customer acquisition cost (CAC) is the total cost of winning one new customer: acquisition spend in a period divided by the new customers gained in that period. |
| [eCpi Effective cost per install](https://appmetricslibrary.com/metrics/ecpi/) | eCPI = Total cost ÷ Installs | Effective cost per install (eCPI) is the cost per install worked out after the fact, by dividing what a campaign cost by the installs it delivered, whatever the buying model. |
| [Ctr Click-through rate](https://appmetricslibrary.com/metrics/ctr/) | CTR = Clicks ÷ Impressions × 100 | Click-through rate (CTR) is the share of ad impressions that led to a click: clicks divided by impressions, shown as a percentage. |
| [Cti Click-to-install rate](https://appmetricslibrary.com/metrics/click-to-install-rate/) | Click-to-install rate = Installs ÷ Clicks × 100 | Click-to-install rate (CTI) is the share of ad or link clicks that end in an install: installs divided by clicks, as a percentage. |
| [Org Organic install share](https://appmetricslibrary.com/metrics/organic-install-share/) | Organic share = Organic installs ÷ Total installs × 100 | Organic install share is the percentage of an app's installs that no paid campaign or tracked link is credited with. |
| Activation |  |  |
| [Act Activation rate](https://appmetricslibrary.com/metrics/activation-rate/) | Activation rate = Users who activated ÷ Installs × 100 | Activation rate is the share of new installs that reach the first meaningful step you define, usually a completed sign-up, within a set number of days. |
| [Obc Onboarding completion rate](https://appmetricslibrary.com/metrics/onboarding-completion-rate/) | Onboarding completion = Users finishing the last step ÷ Users starting onboarding × 100 | Onboarding completion rate is the share of users who start an app's onboarding flow and finish its last step. |
| [Ttv Time to first value](https://appmetricslibrary.com/metrics/time-to-first-value/) | TTFV = Median of (Time of first value event − Install time) | Time to first value (TTFV) is how long a new user takes, from install or sign-up, to reach the first moment the app delivers what it promised. |
| [Kyc KYC completion rate](https://appmetricslibrary.com/metrics/kyc-completion-rate/) | KYC completion = Users verified ÷ Users who started KYC × 100 | KYC completion rate is the share of fintech app users who start identity verification and end up verified. |
| [Ftr First transaction rate](https://appmetricslibrary.com/metrics/first-transaction-rate/) | First transaction rate (day n) = Users with a first transaction by day n ÷ Users in the cohort × 100 | First transaction rate is the share of new fintech users who complete their first deposit, payment, investment or trade within a set number of days. |
| Engagement |  |  |
| [Dau Daily active users](https://appmetricslibrary.com/metrics/dau/) | Average DAU = Sum of each day's unique active users ÷ Days in the period | Daily active users (DAU) is the number of unique users who do a qualifying action in an app on a given day. |
| [Mau Monthly active users](https://appmetricslibrary.com/metrics/mau/) | MAU = Unique users active in the last 30 days (or the calendar month) | Monthly active users (MAU) is the number of unique users who do a qualifying action in an app over a 30-day period or a calendar month. |
| [Stk DAU/MAU stickiness](https://appmetricslibrary.com/metrics/dau-mau-stickiness/) | Stickiness = Average DAU ÷ MAU × 100 | DAU/MAU stickiness is the share of a month's active users who use the app on a typical day: average daily active users divided by monthly active users. |
| [Sl Average session length](https://appmetricslibrary.com/metrics/session-length/) | Average session length = Total session time ÷ Number of sessions | Average session length is the mean time a user spends in an app per session, from opening it to leaving or timing out. |
| [Spu Sessions per user](https://appmetricslibrary.com/metrics/sessions-per-user/) | Sessions per user = Sessions ÷ Active users | Sessions per user is the average number of separate times each active user opens and uses an app in a given period. |
| [Wt Watch time per user](https://appmetricslibrary.com/metrics/watch-time-per-user/) | Watch time per user = Total minutes watched ÷ Active viewers | Watch time per user is the average number of minutes each active viewer streams in a period. |
| [Ccr Course completion rate](https://appmetricslibrary.com/metrics/course-completion-rate/) | Course completion = Learners who completed ÷ Learners who started × 100 | Course completion rate is the share of learners who start a course and finish it. |
| [Str Learning streak rate](https://appmetricslibrary.com/metrics/learning-streak/) | Streak rate (n days) = Learners with a current streak of n or more days ÷ Active learners × 100 | A learning streak is the number of consecutive days a learner completes at least one lesson; as a metric, teams track the share of active learners holding a streak of a set length. |
| [Lvl Level progression rate](https://appmetricslibrary.com/metrics/level-progression/) | Level n reach rate = Players who reached level n ÷ Players in the install cohort × 100 | Level progression rate is the share of players from an install cohort who reach a given level, used to show where players stop playing. |
| Retention |  |  |
| [Ret Retention rate](https://appmetricslibrary.com/metrics/retention-rate/) | Day n retention = Cohort users active on day n ÷ Users in the cohort × 100 | Retention rate is the share of users from an install cohort who come back and use the app on a given day after installing, such as day 1, day 7 or day 30. |
| [Chn Churn rate](https://appmetricslibrary.com/metrics/churn-rate/) | Churn rate = Customers lost in the period ÷ Customers at the start of the period × 100 | Churn rate is the share of users or subscribers at the start of a period who are lost by its end. |
| [Uni Uninstall rate](https://appmetricslibrary.com/metrics/uninstall-rate/) | Uninstall rate (n days) = Cohort installs uninstalled within n days ÷ Installs in the cohort × 100 | Uninstall rate is the share of installs that are removed from devices within a set period after install. |
| Monetisation |  |  |
| [Arpu Average revenue per user](https://appmetricslibrary.com/metrics/arpu/) | ARPU = Revenue in the period ÷ Active users in the period | Average revenue per user (ARPU) is the revenue an app earns in a period divided by its active users in that period. |
| [Arppu Average revenue per paying user](https://appmetricslibrary.com/metrics/arppu/) | ARPPU = Revenue from paying users ÷ Paying users | Average revenue per paying user (ARPPU) is revenue in a period divided by the users who paid in that period. |
| [Arpd Average revenue per daily active user](https://appmetricslibrary.com/metrics/arpdau/) | ARPDAU = Daily revenue ÷ DAU | Average revenue per daily active user (ARPDAU) is one day's revenue divided by that day's active users, usually averaged over a week or a month. |
| [Pcr Paying user conversion rate](https://appmetricslibrary.com/metrics/paying-user-conversion-rate/) | Paying user conversion = Paying users ÷ Users × 100 | Paying user conversion rate is the share of users who make at least one payment, measured over a period or within a set number of days from install. |
| [Sub Subscription conversion rate](https://appmetricslibrary.com/metrics/subscription-conversion-rate/) | Trial-to-paid = Trials converted to paid ÷ Trials started × 100 | Subscription conversion rate is the share of users who move to a paid subscription, most often measured as free trials that become paying subscriptions. |
| [Ltv Lifetime value](https://appmetricslibrary.com/metrics/ltv/) | LTV = ARPU per month × Gross margin ÷ Monthly churn | Lifetime value (LTV) is the total revenue, or gross profit, a user is expected to bring in over their whole time with an app. |
| [Roas Return on ad spend](https://appmetricslibrary.com/metrics/roas/) | ROAS = Attributed revenue ÷ Ad spend × 100 | Return on ad spend (ROAS) is the revenue attributed to advertising divided by what that advertising cost, shown as a percentage or a multiple. |
| [Pb Payback period](https://appmetricslibrary.com/metrics/payback-period/) | Payback (months) = CAC ÷ (Monthly ARPU × Gross margin) | Payback period is the time it takes for the gross profit from a newly acquired user, or cohort, to cover what it cost to acquire them. |
| Virality |  |  |
| [K K-factor (viral coefficient)](https://appmetricslibrary.com/metrics/k-factor/) | K = Invites sent per user × Invite conversion rate | The k-factor, or viral coefficient, is the number of new users each existing user brings in through invites or shares. |
| [Ref Referral install share](https://appmetricslibrary.com/metrics/referral-install-share/) | Referral share = Installs from referral links or codes ÷ Total installs × 100 | Referral install share is the percentage of new installs that come from users inviting other users, usually through a referral link or code. |
| Framework |  |  |
| [Ns North star metric](https://appmetricslibrary.com/metrics/north-star-metric/) | North star = Users doing the core action × How often they do it, in a set period | A north star metric is the single measure a team picks to capture the value users get from the product, chosen so that growing it tends to grow revenue too. |

FAQ

## Questions

**How many metrics does the library cover?**

35 metrics across acquisition, activation, engagement, retention, monetisation and virality, plus the north star metric. Each has its own page with a calculator.

**Why do tools report different values for the same metric?**

Because definitions differ: what counts as active, which attribution window applies, whether organic users are included and how days are cut by timezone. Align the definition before comparing numbers.

**Which currency do the calculators use?**

The calculators show US dollars, but every formula works in any currency: enter your own figures in the currency you report in and read the results in that currency.

**What is the difference between a metric and a KPI?**

A metric is any measured quantity; a KPI is a metric a team has chosen as a target for judging performance. Most metrics here become KPIs only for the teams whose work moves them.

**Do I need an MMP to measure these metrics?**

Not for all of them. Engagement and monetisation metrics come from product analytics and billing data, while metrics split by ad channel, such as CPI, ROAS or retention by source, need installs attributed to campaigns.