Data Overview
AppsFlyer organizes its data into three broad categories: raw event/install reports, aggregated daily reports, and breakdown reports by partner or geography. Each category also splits across three acquisition types: paid (non-organic), organic, and retargeting.
Entity types
Installs
Installs, Organic installs, Retargeting installs
In-app events
In-app events, Organic in-app events, Retargeting in-app events
Uninstalls
Uninstall events, Organic uninstall events
Daily reports
Daily reports, Retargeting daily reports
Partners reports
Partners reports, Retargeting partners reports, Partners events reports, Retargeting partners events reports
Geo reports
Geo reports, Retargeting geo reports, Geo events reports, Retargeting geo events reports
Available data fields
Install and event fields
Event time
Timestamp of the install or event
Event name
Name of the in-app event (e.g., af_purchase, af_complete_registration)
Event value
JSON payload with event parameters and revenue
App ID
Identifier for the app
Media source
Attribution source (e.g., Facebook Ads, Google Ads)
Campaign
Campaign name from the media source
Ad set / Ad
Ad set and ad-level attribution
Country code
Two-letter ISO country code
Platform
iOS or Android
Device type
Device model or type
IDFA / GAID
Device advertising identifiers (subject to privacy restrictions)
Customer user ID
Your internal user identifier (if passed to AppsFlyer)
Is retargeting
Boolean flag indicating retargeting attribution
Cost model / Cost value
Cost data if integrated with cost APIs
Aggregated report fields (daily, partners, geo)
Date
Report date
Media source
Attributed media source
Campaign
Campaign name
Geo / Country
Country dimension (geo reports only)
Impressions
Ad impressions count
Clicks
Click count
CTR
Click-through rate
Installs
Number of installs in the period
Conversion rate
Install rate from clicks
Sessions
App session count
Loyal users
Users with more than a defined number of sessions
Revenue
Total in-app revenue
ROI
Return on investment
ARPU
Average revenue per user
Common field combinations
Media source + Campaign + Installs + Revenue — standard paid acquisition overview
Country code + Installs + Event name — geographic performance by conversion type
Media source + Event name + Event value — partner-level conversion funnel
Date + Installs + Uninstalls — retention and churn trend over time
Use cases by role
Use Partners reports and Installs to compare channel performance side by side. Append organic installs and paid installs into a single sheet to get a unified acquisition view. Connect to Looker Studio or Google Sheets for live campaign dashboards.
Pull raw In-app events into BigQuery for funnel analysis and LTV modeling. Use Coupler.io's Aggregate transformation to roll up event counts by user segment or country. Join install data with uninstall events to calculate cohort retention rates.
Monitor Organic in-app events to understand natural user behavior without paid attribution influence. Use Geo events reports to see which features resonate in specific markets. Send summarized data to ChatGPT or Claude to generate product performance summaries.
Use Daily reports with revenue and cost fields to track ROAS and ROI trends over time. Schedule a nightly refresh into Google Sheets or Excel for budget reconciliation. Combine retargeting and non-retargeting daily reports using Append for total spend visibility.
Platform-specific notes
Raw reports (installs, events, uninstalls) are limited to 90 days of historical data — plan your start date accordingly
Aggregated reports (daily, partners, geo) may support longer date ranges depending on your AppsFlyer plan
Device identifiers (IDFA, GAID) may be empty due to iOS ATT privacy restrictions or Android privacy changes
Cost data fields are only populated if you have AppsFlyer's cost integration enabled for your media sources
Retargeting entities only return data if you have active retargeting campaigns attributed in AppsFlyer
The timezone you set in Coupler.io must match your app's timezone in AppsFlyer settings — mismatches cause date-boundary discrepancies
Last updated
Was this helpful?