This solution offers a comprehensive view of dashboards. Furthermore, exploration models allow you to perform complex analytics, such as event, funnel, path, and retention analysis, enabling a deeper understanding of user behavior and engagement patterns.
Overview
This Guidance demonstrates how to harness the power of clickstream analytics by automating the deployment of a comprehensive data pipeline for web and mobile applications. It helps organizations transform raw user interaction data into actionable business intelligence through a configurable AWS solution that streamlines data collection, ingestion, analysis, and visualization. The solution shows immediate business value by providing pre-built dashboards and analytics models that reveal critical user behavior patterns, enhance customer understanding, and optimize marketing effectiveness. Through purpose-built SDKs and APIs, companies can efficiently capture both standard and custom events, enabling data-driven decision making and product innovation while maximizing return on marketing investments.
Benefits
Out-of-the-box analytics
Complete data ownership
Clickstream data are available at the finest granularity within the security perimeter of an AWS account. You can query, extract, share, and join the user behavior data for multiple use cases.
Cost effective
This solution is built on top of AWS serverless analytics services that auto scale for your data volume without requiring you to reserve any resources. Also, unlike other third-party solutions, this solution has no license charge, so you pay only for your actual AWS service usage.
How it works
These technical details feature an architecture diagram to illustrate how to effectively use this solution. The architecture diagram shows the key components and their interactions, providing an overview of the architecture's structure and functionality step-by-step.
Step 1
An Amazon Cognito user pool or OpenID Connect (OIDC) handles authentication.
Step 2
Amazon CloudFront distributes the frontend web UI assets hosted in an Amazon Simple Storage Service (Amazon S3) bucket.
Step 3
Amazon API Gateway manages the backend APIs and routes traffic to AWS Lambda.
Step 4
Amazon DynamoDB stores persistent data from the web UI console.
Step 5
AWS CloudFormation, AWS Step Functions, Amazon EventBridge, and AWS Lambda orchestrate the lifecycle management of data pipelines.
Step 6
The data pipeline, consisting of Application Load Balancer, Amazon Elastic Container Service (Amazon ECS), Amazon Managed Streaming for Apache Kafka (Amazon MSK), Amazon Kinesis Data Streams, Amazon S3, Amazon EMR Serverless, Amazon Redshift, and Amazon QuickSight, provides scalable clickstream ingestion through load-balanced processing, buffered storage, ETL, and warehouse analytics.
Deploy with confidence
Everything you need to launch this Guidance in your account is right here.
We'll walk you through it
Dive deep into the implementation guide for additional customization options and service configurations to tailor to your specific needs.
Let's make it happen
Ready to deploy? Review the sample code on GitHub for detailed deployment instructions to deploy as-is or customize to fit your needs.
See it in action
Solution Web Console
Analytics Studio
Event Analysis
Funnel Analysis
Path Analysis
Analyses
Related content
Hands-On Workshop
In this workshop, you will get hands-on experience in using the Clickstream Analytics on AWS solution. It will guide you through an end-to-end process of building a production-level data pipeline, and collecting and analyzing clickstream data from an App.