Introduction to Adzviser and Amazon S3
Adzviser lets you export your marketing and sales data directly to Amazon S3 buckets in CSV or JSON format — on-demand or on an automated schedule.
What is Amazon S3?
Amazon S3 (Simple Storage Service) is a cloud storage service from AWS. It's widely used for data lakes, backup, and analytics pipelines. With Adzviser's S3 integration, you can:
- Store your marketing data in your own cloud infrastructure
- Feed data into downstream analytics tools, dashboards, or data warehouses
- Maintain full ownership and control of your data
- Automate daily, weekly, or monthly data exports
How Does Adzviser Export to Amazon S3?
Adzviser's setup flow guides you through the entire process in 6 easy steps:
- Create a pipeline — name it and choose Amazon S3 as your destination
- Connect your S3 bucket — provide your AWS access key and secret key
- Select a data source — Google Ads, Meta Ads, Shopify, and other supported platforms
- Choose accounts — pick which ad accounts or properties to export
- Configure metrics and breakdowns — select the data fields you need
- Choose a mode — run a one-time backfill or schedule automatic exports
Export data in CSV or JSON format. Repeated exports can replace files at the same path. See File storage and history for naming, replacement behavior, and retention options.
Backfills and scheduled exports share your account's monthly row capacity across S3 and BigQuery. Check MAR in Usage metrics on Set Up; see how rows are counted and what to do at the limit.
Why Export to Amazon S3?
| Feature | Manual CSV Export | Adzviser → S3 Pipeline |
|---|---|---|
| Automated scheduling | ❌ | ✅ |
| Data source coverage | Export separately from each platform | View supported sources |
| Multiple accounts at once | ❌ | ✅ |
| CSV and JSON output | Manual | ✅ |
| Historical backfilling | ❌ | ✅ |
Example Use Cases
- Data Warehousing: Feed Google Ads and Meta Ads data into Redshift, Snowflake, or Athena via S3
- Custom Dashboards: Export data to S3 and connect it to your own BI tools
- Data Retention: Store exported data in your AWS account and configure S3 versioning and retention if you need earlier file contents
- Cross-Team Sharing: Make marketing data available to your data engineering team through S3
Ready to get started? Follow our Setup Guide to create your first Amazon S3 pipeline.