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AWS S3 provides the scalable storage for your raw commercial and behavioral data, while Planhat acts as the execution layer. By connecting them, teams automate the retrieval and mapping of flat files into customer records and time-series metrics, ensuring data is operationalized without manual entry or engineering dependency.
Unlock the power of AWS S3 with planhat
Improve net revenue retention
Defend recurring revenue with automated consumption alerts by periodically fetching time-series usage metrics from S3. This ensures Customer Success Managers identify declining adoption patterns in near real-time, enabling earlier intervention before usage gaps threaten a renewal.
Shorten time to value
Accelerate onboarding by automating historical data ingestion from cloud storage. Operations teams move legacy account data and implementation milestones from S3 in bulk to populate Planhat objects instantly, bypassing custom API development to ensure kickoffs start with a complete customer context.
Increase process governance
Maintain strict data hygiene and a clear audit trail with automated file routing. Planhat automatically shifts successfully ingested CSV or XLSX files into a dedicated processed folder, preventing data duplication and ensuring commercial records remain accurate across scheduled sync cycles.
Improve commercial predictability
Anchor revenue forecasts in objective behavioral data by transforming raw device or usage records from S3 into structured company metrics. This allows leadership to base growth projections on actual product engagement signals rather than anecdotal or subjective sentiment.
how it works
Flow & configuration
Secure authentication and region mapping
An authorized user connects the AWS app in Planhat’s App Center using Basic Auth (Access Key ID and Secret Access Key) and defines the API base URL specific to the correct AWS region. This establishes the secure link required for Planhat to access and scan your cloud storage bucket.
Configure bucket path and ARN roles
Set up the action template by defining the Bucket Name, Folder Path, and ARN Role. These configurations allow Planhat to identify precisely where recurring data files land and provide the necessary permissions for the platform to retrieve them automatically.
Map flat files to Planhat models
Admins define whether the incoming files—supported in XLSX, XLS, CSV, or JSON formats—populate CRM objects like Companies and End Users or aggregate into time-series Metric types. This mapping ensures that raw rows are translated into usable customer context for dashboards and workflows.
Define scheduling and archiving logic
Select the scan frequency, ranging from every five minutes to once per week, based on your reporting requirements. To ensure high-frequency sync reliability, Planhat automatically moves processed files into a designated "processed" directory after ingestion so they are not re-imported in subsequent cycles.
Manage security and sync constraints
The integration functions as a one-way inbound sync and does not support bidirectional data exchange or cross-system record deletion. Operations teams must manage manual security key rotations within Planhat to avoid ingestion gaps, as the platform cannot automatically update rotated AWS credentials.
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