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›About

About

  • Overview

Getting Started

  • Introduction
  • Providing User Data
  • Providing Ad Performance Data
  • Providing Ad Network API access
  • Receiving Data from AlgoLift
  • Receiving Probabilistic Attribution pROAS from AlgoLift
  • Providing SKAdNetwork Postbacks

LTV Projections

  • User Guide

Intelligent Automation

  • User Guide
  • Intelligent Automation FAQ

Intelligent Budget

  • User Guide
  • Intelligent Budget FAQ

FAQ

  • LTV FAQ
  • Organic Lift FAQ

Overview

Components

The AlgoLift service consists of two main components:

  1. Intelligence
    Projects future revenue and reports it back via raw data integration and a web interface.
    • on a per-user granularity for maximum flexibility
    • to multiple time horizons: (i.e. 30, 60, 90, 180, 365 days into the future)
  2. Automation
    Uses these projections to automate marketing actions in order to maximize return on investment.
    • adjusts ad spend across the major networks
    • suggests further optimizations via web/email alerts

Process

AlgoLift integrates with your existing data pipeline via the following process:

data flow

1) Data Ingestion

You deliver daily data into an S3 bucket provided by AlgoLift. The required data are:

  • Attribution (all new users, attributed to an install source)
  • Engagement (any actions users take, such as sessions)
  • Revenue (purchases, ad revenue)
  • Ad Performance (ad spend, targeting, and performance)

You also grant AlgoLift access to ad network(s) for our automation systems to learn about and act upon marketing spend.

2) Processing

Algolift processes this data to generate projections, insights and suggestions.

3) Automation

AlgoLift integrates directly with ad providers to adjust campaigns, bids, and budgets to maximize your Return on Ad Spend across networks.

We may also suggest other changes which will be delivered in the app and via email.

4) Delivery

AlgoLift updates your data in our web interface for immediate access, along with email alerts and reports.

We also deliver all projections back to an S3 bucket for your data processes to pick up.

Introduction →
  • Components
  • Process
    • 1) Data Ingestion
    • 2) Processing
    • 3) Automation
    • 4) Delivery
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