Ad Intelligence and Measurement use cases and solutions
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Amazon Ads Insights
Visualize Amazon Ads campaign reports and audience insights, and reduce implementation time when configuring AWS services to query Amazon Ads APIs.
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.
Spend less time on data engineering and more time on data science to accelerate time to market for ML-based contextual advertising workloads.
Measurement, Attribution & Verification
Leverage analytics and machine learning to draw correlation and causation insights from disparate datasets.
Learn more about featured solutions
Amazon Marketing Cloud Insights on AWS
Easily deploy AWS services to store, query, analyze, and visualize reporting from the Amazon Marketing Cloud API.
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.
Predictive Segmentation Using Amazon Pinpoint and Amazon SageMaker
Predictive Segmentation Using Amazon Pinpoint and Amazon SageMaker combines Amazon Pinpoint with Amazon SageMaker to help automate the process of collecting customer data and creating Amazon Pinpoint segments identified by Machine Learning (ML) for tailored audience messaging.
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.
Real-Time Web Analytics with Kinesis Data Analytics
Real-Time Web Analytics with Kinesis Data Analytics automatically provisions the services necessary to track and visualize website clickstream data in real-time.
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Leading advertising intelligence platforms on AWS
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.
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.
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.
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.
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.
See related technical guides, solution briefs, blogs, videos, and much more.
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.
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.
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.
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.