TICKET MANAGEMENT
Log a customer-effort score for every reopened Front ticket
Each time a Front conversation reopens, computes a customer-effort score from the reopened thread and writes a timestamped row to Postgres so you can trend effort backlash over…
How it runs
The automated pipeline, trigger to output.
- TriggerFront conversation reopenedFront
- ActionAssemble reopened thread + metadataFront
- ActionCompute effort score with OpenAIOpenAI
- OutputInsert effort event into PostgresPostgres
What it does
Turns reopens into measurable data. Instead of treating a reopen as a one-off annoyance, this workflow scores how much effort the customer is now spending to get the same problem solved, and records it. Over weeks you get a clean dataset of which issues, agents, and inboxes generate the most repeat friction.
When to use it
Use it when you want hard numbers behind the gut feeling that 'reopens are getting worse.' Perfect for building a recurring effort-backlash dashboard or feeding QA reviews with objective scores rather than anecdotes.
How it works
- 1Front fires a conversation-reopened event.
- 2The flow assembles the full reopened thread and metadata (inbox, assignee, tags) from the Front payload.
- 3OpenAI produces a Customer Effort Score (1-7) with a one-line rationale.
- 4The score, rationale, conversation id, and timestamp are inserted into a Postgres effort_events table.
- 5The row is keyed for later aggregation, leaving the conversation untouched in Front.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
More Ticket Management workflows
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Front-to-Linear Recurring Bug Linker
When a Front ticket is tagged as a bug, it searches Linear for an existing matching issue and either links the ticket to that parent issue or opens a new tracked one.
Front Duplicate Conversation Clusterer
When a new Front conversation arrives, it semantically compares the report against open conversations.
Intercom Known-Issue Auto-Responder
When a new Intercom conversation matches a known active incident, it attaches the conversation to that incident's parent ticket and sends the customer the current status reply.
Weekly reopen-by-agent coaching digest
Aggregates each agent's solved-then-reopened tickets for the week, identifies the most common reopen reason per agent, and emails a private coaching digest to the support manager.
Escalate repeat reopens to a Linear bug
Detects when the same underlying issue reopens across multiple tickets, uses an AI agent to cluster them by root cause.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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