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Adjust KPI Service glossary
Warning:
We recommend all Adjust customers switch to Automate and Datascape for reporting. The Datascape metrics glossary provides information about the metrics available with these services.
Adjust's KPI Service lets you pull your Adjust Deliverables, Cohorts, and Events data. Below is a complete list of all available metrics, along with a description, calculation where necessary, and dashboard availability.
App metrics
KPI | Description | Calculation | Available in dashboard |
---|---|---|---|
impressions | The total number of ad impressions reported for your campaigns | ✔ | |
ctr (click-through rate) | The average number of impressions served per click |
clicks / impressions | ✔ |
clicks | The total number of clicks on Adjust tracker links from your campaigns | ✔ | |
installs | The total number of installs that have occurred | ✔ | |
uninstalls | The total number of uninstalls that have occurred. Only available with our uninstall and reinstall tracking package. Contact sales@adjust.com for more information. | ✔ | |
reinstalls | The total number of reinstalls that have occurred. Only available with our uninstall and reinstall tracking package. Contact sales@adjust.com for more information. | ✔ | |
reattribution_reinstalls | The total number of reinstalls that occurred that also led to a reattribution. Only available with our uninstall and reinstall tracking package. Contact sales@adjust.com for more information. | ✔ | |
uninstall_cohort | The total number of uninstalls from users who installed your app within your selected timeframe | ✔ | |
limit_ad_tracking_installs | The total number of installs coming from devices with limit ad tracking (LAT) enabled | ✔ | |
limit_ad_tracking_install_rate | The proportion of installs coming from devices with LAT enabled |
limit_ad_tracking_installs / installs | ✔ |
limit_ad_tracking_reattributions | The total number of reattributions coming from devices with LAT enabled | ||
limit_ad_tracking_reattribution_rate | The proportion of reattributions coming from devices with LAT enabled |
limit_ad_tracking_reattributions / reattributions | |
click_conversion_rate | How many clicks it takes, on average, for a user to install your app |
installs / clicks | ✔ |
impression_conversion_rate | How many impressions it takes, on average, for a user to install your app |
installs / impressions | |
reattributions | The total number of reattributions that have occurred | ✔ | |
deattributions | The total number of deattributions that have occurred. | ✔ | |
base sessions | The total number of user sessions, excluding installs and reattributions. | ||
sessions | The total number of sessions, including installs (first sessions), reinstalls, reattributions, and reattribution reinstalls that occurr. | base_sessions + installs + reattributions | ✔ |
revenue_events | The total number of revenue events that have been triggered | ✔ | |
revenue | The total revenue your app has generated based on the tracked revenue events reported by the Adjust SDK or as recorded via server-to-server event tracking | ✔ | |
cohort_revenue | The total revenue your app has generated from users who installed your app within your selected timeframe. It is based on the tracked revenue events reported by the Adjust SDK or as recorded via server-to-server event tracking. | ✔ | |
avg. daus (daily active users) | The average number of unique daily active users (DAU) for your selected timeframe |
(DAU of day1 + DAU of day2 + … + DAU of dayN) / the number of days in your timeframe | ✔ |
avg. waus (weekly active users) | The average number of unique weekly active users (WAU) for your selected timeframe |
(WAU of week1 + WAU of week2 + … + WAU of weekN) / the number of days in your timeframe | ✔ |
avg. maus (monthly active users) | The average number of unique monthly active users (MAU) for your selected timeframe |
(MAU of month1 + MAU of month2 + … + MAU of monthN) / the number of days in your timeframe | ✔ |
gdpr_forgets | The total number of users who have exercised their right to be forgotten. Adjust permanently deletes the historical personal data for all of these users but retains their aggregated data for dashboard reporting. Their device data will no longer be received by Adjust or appear anywhere in the Adjust dashboard in the future. | ✔ |
Fraud metrics
KPI | Description | Calculation | Available in dashboard |
---|---|---|---|
rejected_installs | The total number of installs that Adjust identified and rejected as fraudulent | ✔ | |
rejected_installs_anon_ip | The total number of installs that Adjust rejected because they came from anonymous IPs | ✔ | |
rejected_installs_too_many_engagements | The total number of installs that Adjust rejected for registering too many engagements within the attribution window | ✔ | |
rejected_installs_distribution_outlier | The total number of installs Adjust rejected for falling outside the threshold set by our distribution modeling analysis | ✔ | |
rejected_installs_click_injection | The total number of installs Adjust rejected for falsified clicks sent between an app download and install | ✔ | |
rejected_installs_invalid_signature | The total number of installs Adjust rejected for containing an invalid or missing SDK Signature | ✔ | |
rejected_reattributions | The total number of reattributions Adjust identified and rejected as fraudulent | ✔ | |
rejected_reattributions_anon_ip | The total number of reattributions that Adjust rejected because they came from an anonymous IP | ✔ | |
rejected_reattributions_too_many_engagements | The total number of reattributions rejected for registering too many engagements within the reattribution window | ✔ | |
rejected_reattributions_distribution_outlier | The total number of reattributions rejected for falling outside the threshold set by our distribution modeling analysis | ✔ | |
rejected_reattributions_click_injection | The total number of reattributions rejected for falsified clicks between an app download and install for a user who previously had your app installed and had that install attributed within Adjust | ✔ | |
rejected_install_rate | The percentage of your total number of installs that Adjust has identified and rejected as fraudulent. The calculation for the Total row excludes Organic and Untrusted Devices trackers. |
(rejected_installs - Organic rejected_installs) / (installs - Organic installs - Untrusted Devices installs + rejected_installs - Organic rejected_installs) | ✔ |
rejected_install_anon_ip_rate | The percentage of your total number of installs that Adjust has rejected because they came from an anonymous IP |
rejected_installs_anon_ip / (installs + rejected_installs) | |
rejected_install_too_many_engagements_rate | The percentage of your total number of installs that Adjust rejected for registering too many engagements within the attribution window |
rejected_installs_too_many_engagements / (installs + rejected_installs) | |
rejected_install_distribution_outlier_rate | The percentage of your total number of installs that Adjust rejected for falling outside the threshold set by our distribution modeling analysis |
rejected_installs_distribution_outlier / (installs + rejected_installs) | |
rejected_install_click_injection_rate | The percentage of your total number of installs that Adjust rejected for falsified clicks sent between an app download and install |
rejected_installs_click_injection / (installs + rejected_installs) | |
rejected_reattribution_rate | The percentage of your total number of reattributions that Adjust has identified and rejected as fraudulent The calculation for the Total row excludes rejected installs from your Organic and Untrusted Devices trackers. Learn why. |
rejected_reattributions / (reattributions + rejected_reattributions) | ✔ |
rejected_reattribution_anon_ip_rate | The percentage of your total number of reattributions that Adjust has rejected because they came from an anonymous IP |
rejected_reattributions_anon_ip / (reattributions + rejected_reattributions) | |
rejected_reattribution_too_many_engagements_rate | The percentage of your total number of reattributions that Adjust has rejected for registering too many engagements within the attribution window |
rejected_reattributions_too_many_engagements / (reattributions + rejected_reattributions) | |
rejected_reattribution_distribution_outlier_rate | The percentage of your total number of reattributions that Adjust has rejected for falling outside the threshold set by our distribution modeling analysis |
rejected_reattributions_distribution_outlier / (reattributions + rejected_reattributions) | |
rejected_reattribution_click_injection_rate | The percentage of your total number of reattributions that Adjust has rejected for falsified clicks sent between an app download and install for a user who previously had your app installed and had that install attributed within Adjust |
rejected_reattributions_click_injection / (reattributions + rejected_reattributions) |
Ad spend metrics
Cost KPI | Description | Calculation | Available in dashboard |
---|---|---|---|
install_cost | Install cost | ||
click_cost | Click cost | ||
impression_cost | Impression cost | ||
event_cost | Event cost | ||
cost | Total cost | click_cost + impression_cost + install_cost + event_cost | ✔ |
ecost | Total cost for eCPI, eCPC, and eCPM | click_cost + impression_cost + install_cost | |
paid_installs | The number of installs, for which there is cost data | ✔ | |
paid_clicks | The number of clicks, for which there is cost data | ✔ | |
paid_impressions | The number of impressions, for which there is cost data | ✔ | |
cpe | Total cost per event | event_cost / paid_events | ✔ |
ecpc | Effective cost per click | ecpi_cost / paid_clicks | ✔ |
ecpi | Effective cost per install | ecpi_cost / paid_installs | ✔ |
ecpm | Effective cost per mille (one thousand impressions) | ecpi_cost / paid_impressions * 1000 | ✔ |
cohort_gross_profit | The gross profit | cohort_all_revenue - cost | ✔ |
return_on_investment | The ROI metric | cohort_gross_profit / cost | ✔ |
rcr | The revenue-to-cost ratio | cohort_all_revenue / cost | ✔ |
roas | Return on ad spend | cohort_all_revenue / cost *100 |
Ad Revenue metrics
Ad Revenue metric | Description | Calculation | Available in dashboard |
---|---|---|---|
ad_revenue | Total revenue (in the app's reporting currency) from ad_impressions | ✔ | |
ad_impressions | Number of ad impressions | ✔ | |
ad_rpm | ad_revenue per mille (thousand impressions) | ad_revenue / ad_impressions * 1000 | ✔ |
Event metrics
Metric | Description | Calculation | Available in dashboard |
---|---|---|---|
revenue_events | The total number of revenue events that have been triggered | ✔ | |
revenue | The total revenue your app has generated based on the tracked revenue events reported by the Adjust SDK or as recorded via server-to-server event tracking | ✔ | |
events | The total number of events that have been triggered | ||
first_events | The total number of events triggered by a user for the first time | ||
revenue_per_event | How much revenue was generated, on average, per event triggered |
revenue / events | |
revenue_per_revenue_event | How much revenue was generated, on average, per revenue event triggered |
revenue / revenue_events |
Cohort metrics
Cohort metric descriptions and calculations will depend upon which day after install you are looking at. For full details on cohorts and their associated KPIs, see our cohorts documentation.
Metric | Description | Calculation | Available in dashboard |
---|---|---|---|
retained_users | Number of users that came back in the period. | ✔ | |
cohort_size | Day 0 - The total number of users who installed your app in your selected timeframe Day n - The total number of users who installed your app in your selected timeframe and have had your app installed for at least n days | ✔ | |
retention_rate | Day 0 - Percentage of users who installed and opened your app (this will always be 100%) Day n - Percentage of unique users who returned to your app on day n after install | retained_users divided / cohort_size | ✔ |
reattributions | Day 0 - Total number of users who were reattributed on the day of install Day n - Total number of users who were reattributed on day n after instal | ✔ | |
deattributions | Day 0 - Total number of users who were deattributed on the day of install Day n - Total number of users who were deattributed on day n after install | ✔ | |
sessions | Day 0 - Total number of sessions triggered by users on the day of install Day n - Total number of sessions triggered by returning users on day n after install | ✔ | |
sessions_per_user | Day 0 - Average number of sessions triggered by a user on the day of install Day n - Average number of sessions triggered by a returning user on day n after install | sessions per DWM / retained users | ✔ |
revenue | Day 0 - Total in-app revenue generated by all users on day of install Day n - Total in-app revenue generated by returning users on day n after install | ✔ | |
revenue_total | Day 0 - Total in-app revenue generated by all users on day of install Day n - Total in-app revenue generated by all users on every day in the cohort period up to and including day n; this is cumulative, so it will only remain the same or increase over time | ✔ | |
revenue_per_user | Day 0 - Average in-app revenue generated by a user on day of install Day n - Average in-app revenue generated by a user on day n after install | revenue per DWM / cohort size | ✔ |
revenue_per_paying_user | Day 0 - Average in-app revenue generated by paying users on day of install Day n - Average in-app revenue generated by paying users on day n after install | revenue N days / paying users N days | ✔ |
revenue_total_in_cohort | For the N-th period-after-install, the revenue accumulated over all periods from 0 to N, from users who installed at least N periods ago | ||
lifetime_value | Day 0 - All revenue (in-app + ad revenue) generated on day 0 divided by all users in your cohort Day n - All revenue (in-app + ad revenue) generated up to and including day n divided by all users in your cohort | all_revenue_total_in_cohort / cohort_size | ✔ |
paying_user_lifetime_value | Day 0 - Total in-app revenue generated on day of install divided by all paying users in your cohort (it is possible for there to be no figure here if no paying users spent money on the day of installing your app) Day n - Total in-app revenue generated up to and including day n divided by all paying users in your cohort | revenue_total_in_cohort / paying_user_size | ✔ |
time_spent | Day 0 - Total time spent in-app by all users in your cohort on day of install, excluding the last session. Measured in seconds. Day n - Total time spent in-app by all returning users on day n after install, excluding the last session. Measured in seconds. | ✔ | |
time_spent_per_user | Day 0 - Average time spent in-app per user on day of install. Measured in seconds. Day n - Average time spent in-app per user on day n after install. Measured in seconds. | time spent total / cohort size | ✔ |
time_spent_per_session | Day 0 - Average time spent per session on day of install. Measured in seconds. Day n - Average time spent per session on day n after install. Measured in seconds. | time spent total / sessions per DWM - install sessions time spent total / sessions per DWM | ✔ |
paying_users | Day 0 - Total number of paying users who installed your app Day n - Total number of paying users who returned to your app on day n after install | ✔ | |
paying_user_size | Day 0 - The total number of users who installed your app in your selected timeframe and completed an in-app purchase at any point Day n - The total number of users who installed your app in your selected timeframe, have had your app installed for at least n days and completed an in-app purchase at any point | ✔ | |
paying_users_retention_rate | Day 0 - Percentage of users who were paying users on day of install Day n - Percentage of users who were paying users on day n after install | paying users / retained users | ✔ |
paying_user_rate | paying_users / cohort_size | ||
revenue_events | Day 0 - Total number of revenue events triggered by all users on the day of install Day n - Total number of revenue events triggered by all retained users on day n after install | ✔ | |
revenue_events_total | Day 0 - Total number of revenue events generated by all users on day of install Day n - Total number of revenue events triggered by all users in the cohort leading up to and including the latest time period (D/W/M); this is cumulative, so it will only remain the same or increase over time. | ✔ | |
revenue_events_total_in_cohort | For the N-th period-after-install, the number of revenue_events accumulated over all periods from 0 to N, from users who installed at least N periods ago | ||
revenue_events_per_user | Day 0 - Average number of revenue events triggered per user on the day of install Day n - Average number of revenue events triggered per user on day n after install | revenue events per DWM / cohort size | ✔ |
revenue_events_per_active_user | revenue_events / retained_users | ✔ | |
revenue_events_per_paying_user | revenue_events / paying_users | ||
converted_users | Day 0 - Total number of users who completed the relevant in-app event on the day of install Day n - Total number of returning users who completed the relevant in-app event on day n after install | ||
converted_user_size | Day 0 - The total number of users who completed the relevant in-app event on the day of install Day n - The total number of users who completed the relevant in-app event by day n and installed your app at least n days ago | ||
conversion_distribution | Day 0 - The probability, as a percentage, of a user who has completed the relevant in-app event completing it on day of install Day n - The probability, as a percentage, of a user who has completed the relevant in-app event completing it on day n after install | converted users / converted user size | |
conversion_per_user | Day 0 - The event conversion rate on day of install for the cohort Day n - The event conversion rate on day n after install for the cohort | converted users / cohort size | |
conversion_per_active_user | converted_users / retained_users | ||
events | Number of events triggered in period | ||
events_per_converted_user | events / converted_users | ||
events_per_user | Day 0 - Average number of events triggered per user on day of install Day n - The event conversion rate on day n after install for the cohort | events per DWM / cohort size | |
events_per_active_user | events / retained_users | ||
uninstalls | Number of uninstalls per period | ✔ | |
uninstalls_total | Day 0 - The total number of users who uninstalled your app on the day of install Day n - The total number of users who uninstalled your app in your cohort period up to and including day n after install; this is cumulative, so it will only remain the same or increase over time | ✔ | |
reinstalls | Number of reinstalls per period | ✔ | |
reinstalls_total | Day 0 - The total number of users who reinstalled your app on the day of install Day n - The total number of users who reinstalled your app in your cohort period up to and including day n after install; this is cumulative, so it will only remain the same or increase over time | ✔ | |
ad_revenue | Day 0 - Total ad revenue generated by all users on day of install Day n - Total ad revenue generated by returning users on day n after install | ✔ | |
ad_revenue_total | Day 0 - Total ad revenue generated by all users on day of install Day n - Total ad revenue generated by all users on every day in the cohort period up to and including day n; this is cumulative, so it will only remain the same or increase over time | ✔ | |
ad_revenue_total_in_cohort | For the N-th period-after-install, the ad_revenue accumulated over all periods from 0 to N, from users who installed at least N periods ago | ||
ad_rpm | Day 0 - Total ad revenue per mille (1000 ad impressions) on day of install Day n - Total ad revenue per mille (1000 ad impressions) per day in the cohort period up to and including day n; this is cumulative, so it will only remain the same or increase over time | ad_revenue / ad_impressions * 1000 | ✔ |
all_revenue | Day 0 - Total in-app revenue + ad revenue generated by all users on day of install Day n - Total in-app revenue + ad revenue generated by returning users on day n after install | ad_revenue + revenue | ✔ |
all_revenue_total | Day 0 - Total in-app revenue + ad revenue generated by all users on day of install Day n - Total in-app revenue + ad revenue generated by all users on every day in the cohort period up to and including day n; this is cumulative, so it will only remain the same or increase over time | ad_revenue_total + revenue_total | ✔ |
all_revenue_per_user | Day 0 - Average in-app revenue + ad revenue generated by a user on day of install Day n - Average in-app revenue + ad revenue generated by a user on day n after install | all_revenue / cohort_size | ✔ |
all_revenue_total_in_cohort | ad_revenue_total_in_cohort + revenue_total_in_cohort |
SKAdNetwork App metrics
KPI | Description |
---|---|
installs | Installs. |
reinstalls | Reinstalls. |
clicks | Clicks. |
impressions | Impressions. |
valid_conversions | Valid conversions. |
invalid_payloads | Invalid payloads. |
conversion_1 | Conversion Value 1 counter. |
conversion_2 | Conversion Value 2 counter. |
conversion_3 | Conversion Value 3 counter. |
conversion_4 | Conversion Value 4 counter. |
conversion_5 | Conversion Value 5 counter. |
conversion_6 | Conversion Value 6 counter. |
conversion | Conversions. |
conversion_by_token | Conversions by token. |
click_conversion_rate | Click conversion rate (installs/clicks). |
impression_conversion_rate | Impression conversion rate (installs/impressions). |
ctr | Click through rate (clicks/impressions). |
direct_installs | Installs from direct conversions. |
direct_reinstalls | Reinstalls from direct conversions. |
direct_valid_conversions | Valid direct conversions. |
direct_invalid_payloads | Invalid payloads from direct conversions. |
direct_conversion_1 | Conversion Value 1 counter from direct conversions. |
direct_conversion_2 | Conversion Value 2 counter from direct conversions. |
direct_conversion_3 | Conversion Value 3 counter from direct conversions. |
direct_conversion_4 | Conversion Value 4 counter from direct conversions. |
direct_conversion_5 | Conversion Value 5 counter from direct conversions. |
direct_conversion_6 | Conversion Value 6 counter from direct conversions. |
direct_conversion | Direct conversions. |
direct_click_conversion_rate | Direct Click conversion rate (direct_installs/clicks). |
direct_impression_conversion_rate | Direct Impression conversion rate (direct_installs/impressions). |
qualifiers | The number of engagements qualified for the attribution, that did not win. See Activity: SKAdNetwork qualifier for more information. |
ad_revenue_min | Minimum ad revenue. |
ad_revenue_max | Maximum ad revenue. |
ad_revenue_est | Average ad revenue. |
ad_impressions_min | Minimum ad impressions. |
ad_impressions_max | Maximum ad impressions. |
ad_impressions_est | Average ad impressions. |
SKAdNetwork Event metrics
KPI | Description |
---|---|
revenue_min | Minimum revenue |
revenue_max | Maximum revenue |
revenue_est | Average revenue |
events_min | Minimum number of events |
events_max | Maximum number of events |
events_est | Average number of events |