Question 1

What manual work around Visible can be automated?

Accepted Answer

Manual data entry into Visible from external sources can be automated, such as pulling performance metrics from connected tools and pushing them directly into Visible dashboards or reports. Routine updates to stakeholder communications based on changing data can also be triggered automatically, reducing the need to manually refresh and redistribute reports. Automation works best for repetitive tasks like syncing data on a schedule, generating updated snapshots of key metrics, or triggering alerts when specific performance thresholds are met.

Question 2

How does data flow between Visible and other tools?

Accepted Answer

Visible can receive data from external platforms through API connections or webhooks, allowing metrics and records to flow in automatically rather than through manual entry. Data can also flow out of Visible to downstream tools when you need to trigger actions elsewhere based on Visible data or share performance information with other systems. The direction and frequency of data flow depends on how you configure the connection, whether that is one-time syncs, scheduled intervals, or real-time event-based updates.

Question 3

What are common issues when automating data into Visible?

Accepted Answer

Data formatting mismatches can cause incoming information to fail validation or map to the wrong fields in Visible, especially if source systems use different date formats or naming conventions. Permissions and authentication errors may prevent automated connections from accessing Visible or writing data if API credentials are not configured correctly. Additionally, gaps in data or missing required fields from the source system can block records from being created or updated in Visible, so you should validate that all mandatory information is present before automation runs.

Question 4

How should I structure Visible to support reliable automations?

Accepted Answer

Use consistent naming conventions and field structures in Visible so that external systems know exactly where to map incoming data. Ensure all required fields are clearly defined and populated before automation runs, and test your data flow with sample records first to catch formatting or validation issues. Document which fields are used by automations and avoid changing their names or data types after automations are live, as this can break connections and cause data misalignment.

Automate the manual work in Visible

Visible by the numbers

Top 5 Visible friction points when done manually

Syncing cap table updates across Visible

Pulling investor data from Visible repeatedly

Updating financial metrics in Visible manually

Reconciling Visible with your actual records

Recreating Visible reports for board meetings

What you can automate in Visible

Add new Mailchimp subscribers to Visible metrics

Add values to Visible metrics when HubSpot deals move to a new stage

Create Affinity notes when new requests are completed in Visible

Increment metrics in Visible for new deals won in Pipedrive

Update Visible metrics from a PostgreSQL Query

Update Visible metrics from new or updated Google Sheet rows

Tools commonly connected to Visible

Visible Automation questions

Ready to automate your work in Visible?