Google Cloud
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Google Cloud Storage (GCS) provides the primary repository for your raw commercial and behavioral data, while Planhat serves as the system of execution. By establishing a scheduled pipeline between the two, teams automate the retrieval and mapping of flat files into actionable customer records and metrics without manual intervention or engineering dependency.
Unlock the power of Google Cloud with planhat
Improve net revenue retention
Defend recurring revenue using actual product behavior. Planhat pulls time-series usage metrics from GCS folders and maps them to customer records, allowing commercial teams to identify declining adoption patterns early and intervene before a renewal is threatened.
Shorten time to value
Compress implementation timelines by automating historical data onboarding. Operations teams move legacy account data and implementation milestones in bulk from GCS to populate Planhat objects instantly, bypassing engineering bottlenecks to move accounts to kickoff status faster.
Increase process governance
Maintain strict data integrity with automated file routing. Once Planhat successfully ingests a CSV or XLSX file, it is automatically shifted to a dedicated "processed" directory, ensuring the same document is never ingested twice and preventing data duplication across your commercial record.
Improve commercial predictability
Anchor revenue forecasts in objective behavioral evidence. Establishing a reliable scanning cadence—from every five minutes to weekly—ensures that Health Scores and revenue dashboards are built on current file updates rather than outdated snapshots or anecdotal sentiment.
how it works
Flow & configuration
Authentication and service account setup
Connection is established in the App Center by uploading a JSON service account key generated in the Google Developer Console. This provides the secure credentials required for Planhat to periodically access and scan your specific GCS buckets and folders.
Define mapping destinations and data types
Administrators specify the target bucket and folder path, choosing whether the files—supported in XLSX, XLS, CSV, or JSON formats—should populate core CRM objects or aggregate into time-series Metric types. This "fetcher" logic transforms raw rows into usable customer context for reporting and automation.
Configure scan frequency and archival logic
Define the scheduled fetch cadence based on your operational needs, with intervals ranging from every five minutes to once per week. To ensure sync reliability and maintain hygiene, you must specify a "processed" folder path; Planhat automatically archives files in this directory following a successful import to manage ingestion state.
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 ensure bucket-level access and uniform permissions are correctly scoped to avoid 403 errors, and confirm that the target folder structure is live before enabling the scheduled job.
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