Ad Intelligence & Measurement

Spend less time on data engineering and more time on data science with access to the broadest analytics and machine learning capabilities in the cloud.

Exponential media growth is transforming data science for the industry, with companies needing to invent new technologies to create audience segments, forecast inventory, predict attribution, and identify contextual signals that improve marketing effectiveness.
Brands, media publishers, and their technology partners can leverage the broadest machine learning and analytics capabilities with Amazon SageMaker and Amazon Rekognition to accelerate time to market for predictive analytics workloads and analyze media for contextual signals to improve personalization. With our AWS Graviton-based compute instances and 15+ purpose-built AWS database engines companies can ingest billions of ad and marketing events per day to drive innovation in audience analysis, measurement, and campaign insights.
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.


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.
Enrich audience data
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.

Ad Intelligence and Measurement use cases and solutions

Explore solutions by use case

Amazon Ads Insights

Visualize Amazon Ads campaign reports and audience insights, and reduce implementation time when configuring AWS services to query Amazon Ads APIs.

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Audience Segmentation & Targeting

Apply cloud-based analytics and machine learning to reduce time spent on data engineering and pre-processing, and improve model accuracy and price-performance.

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Contextual Analysis

Spend less time on data engineering and more time on data science to accelerate time to market for ML-based contextual advertising workloads.

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Measurement, Attribution & Verification

Leverage analytics and machine learning to draw correlation and causation insights from disparate datasets.

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Machine Learning for Real-Time Advertising

Apply machine learning (ML) to openRTB data sets to filter out unwanted inbound and outbound bid requests, forecast campaign delivery, and inform pricing tactics.

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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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Amazon Marketing Cloud Uploader from AWS

Easily upload first-party signals into Amazon Marketing Cloud for evaluating and planning Amazon Ads campaigns.

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Upsolver Data Lake ETL

Upsolver is a cloud-native data lake ETL platform that simplifies data preparation for analytics engines such as Amazon Athena, Redshift and SageMaker using a visual, SQL-based, service.

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Discovering Hot Topics Using Machine Learning

Understand the most popular topics being actively discussed by ingesting digital assets and performing near real-time inferences and analytics.

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Guidance for Contextual Intelligence for Advertising on AWS

This is a contextual advertising solution with enhanced machine learning (ML) capabilities, designed to reach target audiences without using third-party cookies. 

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Real-Time Web Analytics with Amazon Managed Service for Apache Flink automatically provisions the services necessary to track and visualize website clickstream data in real-time.

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Get started with select AWS services

AWS Entity Resolutions is an easy-to-configure, ML-powered entity resolution service that helps companies easily match, link, and enhance related records across applications, channels, and data stores.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon with a single API, along with a broad set of capabilities you need to build generative AI applications, simplifying development while maintaining privacy and security.
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

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HUMAN Security Accelerates ML Training and Time to Market Using Amazon SageMaker

Cybersecurity company HUMAN Security has tripled the number of machine learning (ML) models that it has deployed to production and improved the quality of its digital solutions by using Amazon SageMaker.

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Ampersand Runs 50,000 Concurrent Machine Learning Models on AWS Batch in Less than 1 Day

By using AWS Batch, Ampersand is running and managing thousands of complex ML workloads at the same time, delivering valuable data-driven insights to its customers.

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

To improve the measurement of marketing campaigns in this privacy-centric landscape, marketing measurement company AppsFlyer used Amazon Web Services (AWS) to deliver PredictSK.

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Delivering Ultralow Latency Machine Learning for Amazon Ads

Amazon Ads employed Amazon ElastiCache and Amazon Kinesis to process billions of impressions every day at ultralow latency. Now, the company’s machine learning models recommend relevant products to customers in 20 markets.

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Acxiom Uses Amazon SageMaker for Propensity Scoring 3 Trillion Records

As a result of moving the workload to AWS, Acxiom reduced inference time by 73 percent and reduced total cost of ownership by 61 percent compared to its previous architecture.

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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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Leading companies in Advertising and Marketing Technology are already using AWS. Contact our experts and start your own AWS Cloud journey today.