Adjust

The table below gives information about all the data fields that you can import from Adjust.

The fields that you can fetch in Adverity are updated regularly to reflect updates to data source APIs. As a result, the fields shown here may not be the same as the fields available in Adverity. If you notice a difference between this documentation and the fields you see in Adverity, please contact your Adverity account manager for more information.

To see the fields you can collect from another data source, go back to the Available fields in Adverity overview.

Field API name	Description	Use in Adverity
Average Daily Active Users (ADAU)	The average number of DAU in the selected period. Calculation: average DAU = (DAU of day1 + DAU of day2 + … + DAU of dayN)/the number of days	metric
Average Monthly Active Users (AMAU)	The average number of MAU in the selected period. Calculation: average MAU = (MAU of day1 + MAU of day2 + … + MAU of dayN)/the number of days	metric
Average Weekly Active Users (AWAU)	The average number of WAU in the selected period. Calculation: average WAU = (WAU of day1 + WAU of day2 + … + WAU of dayN)/the number of days	metric
CTR (Click Through Rate)	The ratio of clicks to impressions. Calculation: CTR = Clicks / Impressions	metric
Click Conversion Rate	The percentage of users that, having clicked the ad, go on to install an app.Calculation: CCR = Installs / Clicks	metric
Click Cost	The sum of click costs.	metric
Clicks	The total number of clicks in a given period. When we speak of clicks, we refer exclusively to clicks on a tracker link.	metric
Cohort Gross Profit	The gross profit of your cohort. Calculation: CGP = cohort_revenue - cost	metric
Cohort Size	The number of users who install your app during the specified period-after-install.	metric
Conversion Per User	The amount of conversion events triggered. Calculation: CPU = Converted Users / Cohort Size	metric
Conversions Per Active User	The average number of conversion events triggered by retained users. Calculation: CPAU = Converted Users / Retained Users	metric
Converted User Size	In a given period-period-after-install, the number of users who converted that many periods ago.	metric
Converted Users	The number of unique users who triggered a given event in the specified period-after-install. One user might contribute to multiple days-after-install.	metric
Cost	The sum of all engagement costs. Calculation: Cost = click_cost + impression_cost + install_cost	metric
DAU (Daily Active Users)	The number of unique users that have opened the app during a given day.	metric
Deattributions	The number of users who have been deattributed (i.e., reattributed away from their install tracker) during the specified period-after-install.	metric
Effective Cost Per Click	The effective cost per click. Calculation: ECPC = cost / paid_clicks	metric
Effective Cost Per Install	The effective cost per install. Calculation: ECPI = cost / paid_installs	metric
Effective Cost Per Mille	The effective cost per mille (thousand impressions). Calculation: ECPM = cost / paid_impressions * 1000	metric
Events	The total number of events triggered.	metric
Events Per Active User	The average number of events retained users trigger. Calculation: EPAU = Events / Retained Users	metric
Events Per Converted User	The average number of events converted users trigger in a given period. Calculation: EPCU = Events / Converted Users	metric
Events Per Day	The total number of events triggered in a given day.	metric
Events Per User	The average number of events triggered by a cohort member. Calculation: EPU = Events / Cohort Size	metric
First Events	The number of events triggered for the first time by a user. The relationship between First Events and Events is similar to the one between Installs and Sessions.	metric
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.	metric
Impression Conversion Rate	The percentage of users that, having registered an ad impression, go on to install the app within 24 hours. Calculation: ICR = Installs / Impressions	metric
Impression Cost	The sum of impression costs.	metric
Impressions	The number of registered impressions in a given period. These are typically defined as the number of users who have been shown the ad, or viewed a video ad through to the end. The exact definition can vary depending on which network you are working with and how they implement the campaigns.	metric
Install Cost	The sum of install costs.	metric
Installs	The total number of installs in a given period. We define an install as when a user installs and then opens the app for the first time. The user must open the app for the install to be counted.	metric
LTV (Lifetime Value)	The average revenue a cohort member generates for the duration of their usage. Calculation: LTV = Revenue Total in Cohort / Cohort Size	metric
MAU (Monthly Active Users)	For a given day, the number of unique users that have opened the app within the preceding 30 days (including the given day).	metric
Paid Clicks	The total number of clicks for which there is cost data.	metric
Paid Impressions	The total number of impressions for which there is cost data.	metric
Paid Installs	The total number of installs for which there is cost data.	metric
Paying User LTV (Lifetime Value)	The average revenue a paying cohort member generated for the duration of their usage. Calculation: PULTV = Revenue Total in Cohort / Paying User Size	metric
Paying User Rate	The percentage of cohort members who are paying users. Calculation: PUR = Paying Users / Cohort Size	metric
Paying User Size	The number of paying users who installed the app at least N periods ago for the N-th period-after-install, with N representing the number of days.	metric
Paying Users	The total number of paying users in a cohort.	metric
Paying Users Retention Rate	The number of unique paying users who return to your app in the days following install. Calculation: PURR = Paying Users / Retained Users	metric
Reattribution reinstalls	The total number of reinstalls that also led to a reattribution in a given period.	metric
Reattributions	Reattribution is the movement of a user onto a new segment following their return to your app after a period of absence, generally as the result of a retargeting or re-engagement campaign.	metric
Reinstalls	The total number of reinstalls in a given period.	metric
Reinstalls Per Day	The total number of reinstalls per day	metric
Reinstalls Total	The total number of reinstalls for a cohort s current and all previous periods	metric
Retained Users	The total number of unique cohort members who returned to your app following their install day.	metric
Retention Rate	The percentage of unique cohort members that returned to the app in the days following install. Calculation: RR = Total Retained Users DWM / Cohort Size	metric
Return On Investment	The return on investment. Calculation: ROI = cohort_gross_profit / cost	metric
Revenue	The amount of revenue a cohort generates per period.	metric
Revenue Events	The number of revenue events triggered in a period.	metric
Revenue Events Per Active User	The average number or revenue events triggered by retained users. Calculation: REPAU = Revenue Events / Retained Users	metric
Revenue Events Per Paying User	The average number of revenue events triggered by paying users. Calculation: REPPU = Revenue Events / Paying Users	metric
Revenue Events Per User	The average number of revenue events generated per cohort member. Calculation: REPU = Revenue Events / Cohort Size	metric
Revenue Events Total in Cohort	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.	metric
Revenue Per Day	The amount of revenue a cohort generates per day.	metric
Revenue Per Event	The average amount of revenue generated per each event. Calculation: RPE = Revenue / Events	metric
Revenue Per Event	The average amount of revenue generated for each in-app event, including non-revenue events.	metric
Revenue Per Paying User	The average amount of revenue a paying user generates. Calculation: RPPU = Revenue / Paying User Size	metric
Revenue Per Revenue Event	The average amount of revenue generated per each Revenue Event. This differs from the Revenue Per Event metric in that it averages only events that trigger revenue and not all Events. Calculation: RPRE = Revenue / Revenue Events	metric
Revenue Per User	The average amount of revenue generated by each cohort member. Calculation: RPU = Revenue / Cohort Size	metric
Revenue Total	The accumulated revenue for a cohort s current and all previous periods	metric
Revenue Total In Cohort	The total revenue accumulated in a certain period from users who installed at least that many periods ago.	metric
Revenue to Cost ratio	The revenue generated by users who installed within your selected timeframe as a percentage of your ad spend Calculation: RCR = cohort_revenue / cost	metric
Revenue-to-cost Ratio	The revenue-to-cost ratio. Calculation: cohort_revenue/cost	metric
Sessions	A session is every time that a user opens the application. There must be a 30 minute break between use, otherwise it is counted as the same session. For example, if a user opens an app every five minutes over a hour long period, this is counted as one session as there was not a sufficient break between any of the uses.	metric
Sessions Per Day	Total number of sessions recorded for all users within specified cohort period. Calculation: SPU = Total Sessions Per DWM / Total Retained Users DWM	metric
Sessions Per User	The average amount of sessions per unique user in the given period. Calculation: SPU = Sessions / Retained Users	metric
Time Spent	The total sum of time users spent in-app during the cohort period. Time spent is measured in seconds.	metric
Time Spent Per Session	Average amount of time spent by users on install day and days following, per session, within specified cohort period. Calculation: TSPS = Total Time Spent / Sessions Note: For day 0, week 0, or month 0 cohort calculations, ensure you subtract any install sessions	metric
Time Spent Per User	Average amount of time spent within specified cohort period. Note that this metric uses the full cohort size as dividend. Calculation: TSPU = Total Time Spent / Cohort Size	metric
Uninstall (cohort)	The total number of uninstalls from users who installed within your selected timeframe.	metric
Uninstalls	The total number uninstalls in a given period.	metric
Uninstalls Per Day	The total number of uninstalls per day	metric
Uninstalls Total	The total number of uninstalls for a cohort s current and all previous periods	metric
WAU (Weekly Active Users)	For a given day, the number of unique users that have opened the app within the preceding seven days (including the given day).	metric
ad_impressions_total_in_cohort_{cohort_period}	The total number of ad impressions for users belonging to a specific cohort. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
ad_impressions_total_{cohort_period}	The cumulative number of ad impressions from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
ad_impressions_{cohort_period}	The total number of times advertisements were displayed to users within a specific cohort timeframe. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
ad_revenue_total_in_cohort_{cohort_period}	The total ad revenue generated by users belonging to a specific cohort. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
ad_revenue_total_per_user_{cohort_period}	The average cumulative ad revenue per user from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
ad_revenue_total_{cohort_period}	The cumulative ad revenue from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
ad_revenue_{cohort_period}	The revenue generated from advertisements within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
ad_rpm_{cohort_period}	Revenue per thousand ad impressions within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
all_revenue_per_user_{cohort_period}	The average revenue per user from all sources within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
all_revenue_total_in_cohort_{cohort_period}	The total revenue from all sources generated by users belonging to a specific cohort. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
all_revenue_total_per_user_{cohort_period}	The average cumulative revenue per user from all sources from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
all_revenue_total_{cohort_period}	The cumulative revenue from all sources from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
all_revenue_{cohort_period}	The total revenue from all sources (ads, in-app purchases, etc.) within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
app_token	App Token.	dimension
cohort revenue	Total revenue from users who were (re)attributed within your selected timeframe	metric
cohort_size_{cohort_period}	The number of users in a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
deattributions_per_user_{cohort_period}	The average number of deattributions per user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
deattributions_{cohort_period}	The number of users who were deattributed within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
first_reinstalls_total_{cohort_period}	The cumulative number of first-time reinstalls from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
first_reinstalls_{cohort_period}	The number of first-time reinstalls within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
first_uninstalls_total_{cohort_period}	The cumulative number of first-time uninstalls from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
first_uninstalls_{cohort_period}	The number of first-time uninstalls within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
gdpr_forgets_total_{cohort_period}	The cumulative number of GDPR forget requests from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
gdpr_forgets_{cohort_period}	The number of GDPR forget requests within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
lifetime_value_ad_{cohort_period}	The total value generated from advertising revenue within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
lifetime_value_iap_{cohort_period}	The total value generated from in-app purchases within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
lifetime_value_{cohort_period}	The total value generated by users across all revenue sources within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
limit ad tracking install rate	Proportion of installs from devices with Limit Ad Tracking enabled: limit_ad_tracking_installs / installs	metric
limit ad tracking installs	Number of installs from devices with Limit Ad Tracking enabled	metric
limit ad tracking reattribution rate	Proportion of reattributions from devices with Limit Ad Tracking enabled: limit_ad_tracking_reattributions / reattributions	metric
limit ad tracking reattributions	Number of reattributions from devices with Limit Ad Tracking enabled	metric
non_install_sessions_{cohort_period}	The number of sessions excluding the initial install session within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
paying_user_lifetime_value_ad_{cohort_period}	The average lifetime value of paying users from advertising revenue within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
paying_user_lifetime_value_iap_{cohort_period}	The average lifetime value of paying users from in-app purchases within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
paying_user_lifetime_value_{cohort_period}	The average lifetime value of paying users across all revenue sources within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
paying_user_rate_{cohort_period}	The percentage of users who made a purchase within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
paying_user_size_{cohort_period}	The total number of paying users within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
paying_users_retention_rate_{cohort_period}	The percentage of paying users who remain active within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
paying_users_{cohort_period}	The number of users who made at least one purchase within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
reattributions_per_deattribution_{cohort_period}	The average number of reattributions per deattribution within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
reattributions_per_user_{cohort_period}	The average number of reattributions per user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
reattributions_{cohort_period}	The number of users who were reattributed within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
reinstalls_total_{cohort_period}	The cumulative number of app reinstalls from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
reinstalls_{cohort_period}	The number of app reinstalls within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
retained_users_{cohort_period}	The number of users who remain active within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
retention_rate_{cohort_period}	The percentage of users who remain active within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
return on investment	The ROI metric derived by cohort_gross_profit / cost	metric
revenue per event	Total revenue divided by number of events.	metric
revenue_events_per_active_user_{cohort_period}	The average number of revenue events per active user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_events_per_paying_user_{cohort_period}	The average number of revenue events per paying user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_events_per_user_{cohort_period}	The average number of revenue events per user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_events_total_in_cohort_{cohort_period}	The total number of revenue events generated by users belonging to a specific cohort. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_events_total_{cohort_period}	The cumulative number of revenue events from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_events_{cohort_period}	The number of revenue-generating events within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_per_paying_user_{cohort_period}	The average revenue per paying user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_per_user_{cohort_period}	The average revenue per user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_total_in_cohort_{cohort_period}	The total revenue from in-app purchases generated by users belonging to a specific cohort. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_total_per_user_{cohort_period}	The average cumulative revenue per user from in-app purchases from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_total_{cohort_period}	The cumulative revenue from in-app purchases from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
revenue_{cohort_period}	The revenue generated from in-app purchases within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
roas_ad_{cohort_period}	Return on Ad Spend for advertising revenue within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
roas_iap_{cohort_period}	Return on Ad Spend for in-app purchase revenue within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
roas_{cohort_period}	Return on Ad Spend (total revenue divided by total cost) within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
sessions_per_user_{cohort_period}	The average number of sessions per user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
sessions_{cohort_period}	The number of app sessions within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
time_spent_per_active_user_{cohort_period}	The average time spent in the app per active user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
time_spent_per_session_{cohort_period}	The average time spent per session within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
time_spent_per_user_{cohort_period}	The average time spent in the app per user within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
time_spent_{cohort_period}	The total time users spent in the app within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
uninstalls_total_{cohort_period}	The cumulative number of app uninstalls from install date until the specified cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
uninstalls_{cohort_period}	The number of app uninstalls within a specific cohort period. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_events_est	The estimated number of events that occurred. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_events_max	The maximum number of events that occurred. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_events_min	The minimum number of events that occurred. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_revenue_est	The estimated revenue generated from events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_revenue_max	The maximum revenue generated from events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_revenue_min	The minimum revenue generated from events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_skan_ecpa	The effective cost per action (ECPA) for SKAdNetwork events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_skan_event_ecr_est	The estimated event conversion rate for SKAdNetwork events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_skan_event_ecr_max	The maximum event conversion rate for SKAdNetwork events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_skan_event_ecr_min	The minimum event conversion rate for SKAdNetwork events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_skan_event_rpu_est	The estimated revenue per user for SKAdNetwork events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_skan_event_rpu_max	The maximum revenue per user for SKAdNetwork events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_skan_event_rpu_min	The minimum revenue per user for SKAdNetwork events. The {event_slug} is a slug for events which can be retrieved using the events endpoint.	metric
{event_slug}_{cohort_period}_conversions_cohort	The number of conversions for a specific event within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_conversions_cost_cohort	The total cost associated with conversions within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_conversions_rate_cohort	The conversion rate for a specific event within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_converted_user_size_cohort	The number of users who completed a specific event conversion within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_events_cohort	The total number of times a specific event occurred within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_events_cost_cohort	The total cost associated with events within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_events_per_conversion_cohort	The average number of events per conversion for a specific event within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_events_per_period	The number of events that occurred in each specific period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_events_rate_cohort	The rate of event occurrence within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_revenue_cohort	The total revenue generated from a specific event within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_revenue_per_conversion_cohort	The average revenue per conversion for a specific event within a cohort period. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric
{event_slug}_{cohort_period}_revenue_per_period	The revenue generated in each specific period from events. The {event_slug} is a slug for events which can be retrieved using the events endpoint. Cohort_period can be expressed as days (d0-d120), weeks (w0-w52), or months (m0-m36), e.g., d3, w26, m36.	metric