In HubSpot, we manage service tickets that are frequently rescheduled, with each reschedule creating a new associated service object. Ideally, we want to update only the most recent associated service record with new data from the ticket (like the reschedule reason or updated date).
Currently, HubSpot workflows allow copying data from the most recent associated object, but there is no way to paste data into a specific associated object, such as the most recently created or most recently updated record.
Use Case Example:
- Ticket is scheduled → Service object is created
- Ticket fails → that specific Service is updated
- Ticket is then rescheduled → a new service is created
- We need to copy new data from the ticket into only the most recent service object
But HubSpot doesn’t allow us to define which associated service to update — so it updates all, or none, without precision.
Current Limitation:
- Workflow actions like “Copy property value to associated record” lack conditional targeting
- No native ability to update only the most recent or updated record in a set of associated objects
- No option to filter associated objects before selecting where to paste
Proposed Feature:
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Add workflow support for:
- Copying to a specific associated object, e.g., “most recently created,” “most recently updated,” or one that meets defined filters
- Filtering associated records before updating (e.g., object type, property value, pipeline)
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This should work for all objects — custom or standard — including Tickets, Deals, and Custom Objects like “Services” or “Appointments”
Impact:
- Drastically reduces manual data syncing for rescheduled services
- Enables clean and accurate record keeping, avoiding updates to historical records
- Unlocks smarter automation for teams using custom objects and multiple associations
Who It Helps:
- Ops and service teams with repeated or rescheduled appointments
- Companies using custom objects for fieldwork, installations, or service tasks
- Anyone using tickets/deals with multiple associated records over time
