Innovate faster for the post-cookie era with the broadest analytics and machine learning capabilities in the cloud.

Spend less time on data engineering, and more time on data science with the broadest and deepest cloud capabilities for analytics and machine learning.
With AWS, you can reduce heavy lifting and invent faster in areas such as ad measurement, audience segmentation, propensity scoring, identity resolution, identity enrichment, contextual segmentation, inventory forecasting, dynamic creative optimization, and predictive attribution.
TripleLift Invents New Ad Units for Product Placement in Streaming TV with AWS Machine Learning


heavy lifting

With AWS, data science teams spend less time preparing, pre-processing and setting up analytics infrastructure; and more time inventing using the broadest and deepest analytics, artificial intelligence, and machine learning services of any cloud provider. AWS customers process vast amounts of data with Amazon EMR, which supports 21 different open source processing projects, and use Amazon SageMaker to easily prepare, build, train, and deploy high-quality machine learning (ML) models quickly.


Analyze distributed data in privacy-safe workspaces with the broadest capabilities of any cloud provider for secure analytics and storage, including tools for data collaboration, governance, confidentiality, storage, preparation, security, and analytics. With AWS Lake Formation, you can build a secure data lake in days, defining data sources and what data access and security policies you want to apply.
Improve interoperability
Enrich audience data with your preferred data providers via AWS Data Exchange, which makes it easy to find, subscribe to, and use third-party data in the cloud. Qualified data providers include Adstra, Acxiom, Epsilon Data Management, Foursquare, Kantar, and others. Once subscribed to a data product, you can use the AWS Data Exchange API to load data directly into Amazon S3 and then match it with other identifiers using Amazon EMR and AWS Glue Catalog.

Advertising intelligence solutions and services

Amazon Marketing Cloud Insights on AWS

Easily deploy AWS services to store, query, analyze, and visualize reporting from the Amazon Marketing Cloud API.

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AWS services

Build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows.
AWS Lake Formation is a service that makes it easy to set up a secure data lake in days.
Amazon Rekognition offers pre-trained and customizable computer vision (CV) capabilities to extract information and insights from your images and videos.
Amazon EMR is a cloud big data platform for running large-scale distributed data processing jobs, interactive SQL queries, and ML applications using open-source analytics frameworks such as Apache Spark, Apache Hive, and Presto.
Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning to deliver the best price performance at any scale.
Amazon Simple Storage Service (Amazon S3) is an object storage service offering industry-leading scalability, data availability, security, and performance.

Leading advertising intelligence platforms on AWS

AppsFlyer logo

AppsFlyer Builds a Predictive Analytics Solution for iOS 14+ Using Amazon SageMaker

AppsFlyer used Amazon SageMaker and AWS Serverless capabilities to build a predictive analytics product in 6 months that predicts the lifetime value of a mobile app user with machine learning—improving accuracy on its attribution modeling and protecting user privacy in compliance with Apple’s iOS 14.

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FreeWheel logo

FreeWheel Uses Amazon SageMaker for Digital Video and TV Ad Inventory Prediction

FreeWheel uses Amazon SageMaker to predict advertising inventory for digital video and linear TV months in advance for billions of ad-serving records per day—reducing overall efforts by 60%, costs by 50%, and improving accuracy of its predictions.

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TripleLift logo

TripleLift Invents New Ad Units for Real-Time Product Placement in Streaming TV Using ML

TripleLift pioneered a solution for dynamically inserting product placement ads into streaming TV shows by using a combination of custom-built models and ML on AWS.

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Publicis Media Automates Audience Segmentation Using Machine Learning on AWS

Publicis Media built a machine learning pipeline that provides media buyers with highly-accurate recommendations on audience segments using Amazon EMR and Amazon Redshift.

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Nielsen logo

Nielsen Processes 250 Billion Ad Events per Day Using Serverless Computing on AWS

Nielsen Marketing Cloud processes 250 billion ad measurement events per day using serverless computing with AWS Lambda and containers with Amazon EKS to achieve 20 percent cost efficiency.

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Accelerate with key industry partners

Customers can easily tap into third-party data sets via AWS Data Exchange (ADX) partners for Advertising and Marketing, and accelerate time to market for their advertising intelligence applications using the AWS Partner Network (APN).

AWS Data Exchange

AWS Partners


See related technical guides, solution briefs, blogs, videos, and much more.

Featured resource

AWS re:Invent: Distributed machine learning for digital video and TV ad serving

Discover how FreeWheel (a Comcast company) uses Amazon SageMaker to predict advertising inventory for digital video and linear TV months in advance for billions of ad serving records per day. Learn how FreeWheel built an end-to-end distributed ML pipeline for long-range, time-series inventory prediction across audience segments, geographies, and media types at massive scale.

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Annalect Uses Containers and Redshift Spectrum to Process Trillions of Events

Annalect, a subsidiary of Omnicom Media Group, reduced its cost per usable terabyte from $70 per usable terabyte to less than $5—a 92% cost savings—as it analyzes trillions of events and petabytes of data per month.

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Contextual targeting and ad tech migration best practices

Get an insider’s view on migrating and developing next-generation contextual advertising and verification workloads on AWS—cost effectively and at scale.

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End-to-end machine learning using Spark and Amazon SageMaker

Learn how AWS customers are developing production-ready ML models to optimize auction dynamics and bid pricing in milliseconds.

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