Customer 360 Analytics
Unifying customer data from web, mobile, POS, and marketing channels into a single analytical view for segmentation and targeting.
Data Analytics
AWS Data Analytics for Retail & E-Commerce
We build analytics platforms for retail and e-commerce companies on AWS that turn transaction data into actionable insights — customer segmentation, demand forecasting, and real-time personalization.
- A source system is connected.
- Ingest lands in the lake or the stream, not a spreadsheet hop.
- Transform cleans and models before anyone charts it.
- Publish is a dashboard or an API, with the same grain.
- A named owner holds the quality gate.
- What lands is decision-ready, not another raw extract.
Key Challenges We Solve
Demand Forecasting
Predicting demand at the SKU level using historical sales data, seasonality, promotions, and external factors.
Real-Time Personalization
Delivering personalized product recommendations and dynamic pricing in real time based on user behavior and purchase history.
Inventory Optimization
Balancing inventory levels across warehouses and stores to minimize stockouts and overstock using predictive analytics.
Our Approach
Retail Data Lake
S3 + Glue + Lake Formation data lake that ingests data from all retail channels, with Athena for ad-hoc analytics and QuickSight for business dashboards.
Real-Time Analytics Pipeline
Kinesis Data Streams for real-time clickstream and transaction processing, enabling sub-second personalization and fraud detection.
ML-Powered Forecasting
Amazon Forecast and SageMaker for demand prediction, inventory optimization, and dynamic pricing models trained on your historical data.
Frequently Asked Questions
How long does it take to build a retail analytics platform on AWS?
A foundational data lake with core reporting takes 6-8 weeks. Adding real-time analytics and ML-powered forecasting typically adds another 4-6 weeks. The platform evolves incrementally — start with the highest-value use cases and expand.
Can AWS analytics handle Black Friday traffic spikes?
Yes. Kinesis, Lambda, and DynamoDB scale automatically to handle traffic spikes. Athena and Redshift Serverless scale compute independently of storage. There is no capacity planning needed for analytics workloads on AWS.
What does a retail analytics platform cost on AWS?
A mid-size retail analytics platform typically costs $500-$2,000/month on AWS, depending on data volume and query frequency. S3 storage is $0.023/GB, Athena queries cost $5/TB scanned, and Glue ETL costs $0.44 per DPU-hour.
Ready to Get Started?
Talk to our AWS experts about aws data analytics for retail & e-commerce.