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  • Getting Started
    • Welcome to AdLibertas
  • The Platform
    • How it works
    • User-Level Audience Reporting
      • Creating Reports
        • Creating a New User Report
        • Creating Advanced User-Level Reports
        • Advanced Audience Builder
        • Custom Event Metrics
      • Report Layout
        • Report Module: Audience Filtering
        • Chart Type Module: Absolute vs. Relative Reports
        • Daily Totals, Per User, Cumulative Totals
        • Lifecycle Reports
        • Forecasting Module
        • Statistics Module
        • Measuring Confidence
      • Advanced Reporting Methods
        • User Measurement & Calculation Details
        • Date Ranges: Define Audience vs. Create Report
        • Exclude GAID tracking opt-outs
        • Scheduled Reports: Keep Updated & Rolling
        • Reporting on a Firebase AB test
        • Understanding “Audience Restraints”
        • Adding user time to your reports
    • Consolidated Revenue Reporting
      • Reporting Discrepancies
      • Reporting Availability & Timezones
      • Ad Network Re-Repost; Also: Revenue Reconciliation Accuracy
      • Consolidated Reporting vs. Consolidated Inventory Reporting
      • Reporting Table – Column Descriptions Common Metrics (Calculated Fields)
      • Facebook Reporting
      • Consolidated Ad Revenue with multiple mediators
    • Business Analytics
      • Analytics Layout
      • Understanding the "Explore Data" button
      • The Data Table
      • Asking a Question
      • Saving a Question
      • Creating a custom dimension
      • Setting up a pulse
    • Custom Dashboards
      • Custom Dashboard Filters
      • Combining data into a single chart
    • Direct SQL Access
    • Exporting Data
      • Ad Network Reports
      • Chart Reports
      • Custom API connections
      • Downloading & Scheduling Data Reports
      • Deprecated: Line Item Change Log
    • General
      • Change your Username & Password
      • Adding Users to your Account
      • Sharing Collaborative Links
      • AdLibertas Cost
  • Data Integrations
    • Connecting in 3 steps
    • Ad Impression-Level Revenue Connections
      • AppLovin Max User Revenue API
      • ironSource Ad Revenue Measurement Integration
      • Impression level tracking with Admob Mediation
      • Collecting MoPub Impression-Level Data as a Firebase Event
    • Ad Network & Store Connections
      • Adding Ad Network Credentials
      • How does App Store Reporting work?
      • Adding access to Google Play
      • Adding Sub User to App Store Connect
      • Getting the most from Ad Network Reports
    • Analytics Connections
      • Data Set Status
      • Connect AdLibertas to Firebase
      • Connecting AdLibertas to BigQuery
      • Firebase Install Counts in Audience Reporting
      • Setting User Campaigns in Firebase
      • Why use revenue to determine Firebase AB test winners?
      • Firebase Best Practices: keeping Google BigQuery Costs Down
    • Custom Integrations
      • Sending Events via Webhooks to AdLibertas
      • Impression level tracking with Admob Mediation
      • Connecting AdLibertas to BigQuery
      • Importing a custom data set
    • IAP Connections
      • Tracking IAP & Subscriptions in Firebase and BigQuery
      • RevenueCat Integration: WebHooks
      • RevenueCat: Setting Universal Identifiers
    • MMP Connections
      • Connecting Adjust
      • Connecting AppsFlyer
      • Connecting Kochava
  • FAQs
    • General
      • Why does AdLibertas need credentials?
    • Audience Reporting
      • Why doesn't my daily active user count match Firebase?
      • Why doesn’t my retention rate match?
      • Why aren't my install rates matching?
      • Why doesn't my relative user count match retention?
      • What is the probability projected LTV becomes actual LTV?
      • Why doesn’t Firebase and AdLibertas revenue match?
    • Reporting
      • What is “non_mopub” revenue
      • How do customers use AdLibertas?
  • Privacy & Security
    • Privacy & Security Details
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On this page
  • Step 1. API Data Collection
  • Step 2. Data Pipeline: Processing & Storage
  • Step 3. End-User Reporting & Access
  • Reporting Workflow
  1. The Platform

How it works

AdLibertas functions as your private end-to-end data cloud: we do the heavy lifting of managing your data so you can focus your efforts on more valuable activities.

PreviousWelcome to AdLibertasNextUser-Level Audience Reporting

Last updated 2 years ago

Step 1. API Data Collection

We have 100+ APIs that are scheduled to batch-fetch your data from all in-app service providers. We don’t require an SDK for integration, and most data can be collected by simply connecting credentials.

Step 2. Data Pipeline: Processing & Storage

Scheduled Data Import & ETL

Our scheduled, overlapping data import schedules ensures the latest data available is accessible while back-fetching ensures any later-posted data is added to keep data access timely and correct.

We’ve pre-built the ETL & processing algorithms so there’s no need for you to wrestle with scripting your own.

Fully managed data lake

For every AdLibertas customer, we spin up a single-tenant AWS account to house and store your data. We’ve architected your data to be stored as ORC files in S3 buckets. This maximizes long-term cost-efficiency and maintains accessibility and security for all clients. There’s no maintenance or overhead needed.

Building your own Data Pipeline: Best Practices

Fast, parallel-distributed query processing

For processing the many petabytes of information generated by our clients, we adopted Trino a fast, highly parallel, and distributed query engine that is built from the ground up for efficient, low latency analytics at scale.

Step 3. End-User Reporting & Access

Rich, interactive reporting and custom dashboarding

Self-service no-SQL exploration

Our analytics give all users in your organization the ability to build custom-defined user datasets, defined by user-events, actions, and/or user characteristics. There’s no need for complicated SQL-joins or custom Tableau reports, anyone can simply drag and drop user-audiences. This gives your organization complete control and flexibility in refining their data-sets to find the important users and actions in your app.

Interactive, custom reporting & prediction models

Direct SQL Access & Custom Processing

Reporting Workflow

For app developers that want to architect, build and maintain their own data architecture, AdLibertas Head of Architecture, Allen Eubank, in building a scalable, reliable data pipeline.

AdLibertas uses Trino to enable their customers.

Your organization can compare audience datasets across performance metrics and custom events. See the and see how our proprietary machine learning predictions can help you get fast, accurate campaign predictions here

For customers who want direct access to the data, we offer direct , or end-points to Additionally, customers can spin up their own computing clusters to run advanced or custom models against their users or custom datasets.

allows you to create hyper-specific reports on user-level characteristics and behavior. From here, we store these reports in the system -- accessible via the ""-- so you can add them to a or compare them against other user-level reports.

allows you to view your earnings in or drill directly into to create your own reports.

shares our experiences
Read how and why
article on how predicted LTVs work here
SQL access via Amazon Athena
access and download reports.
User-level Audience Reporting
analytics
Explore Data button
custom dashboard
Consolidated Revenue Reporting
pre-built charts
analytics
more details about the platform
BI & Analytics
Connecting in 3 stepsKnowledge Base
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The AdLibertas Approach to Big Data - AdLibertasAdLibertas
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Our Customers - AdLibertasAdLibertas
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Dashboard and reporting