TICKET MANAGEMENT
Reopened-Ticket Weekly Trend Report
Aggregates a week of reopened tickets from a Postgres support warehouse, computes reopen rate by category and root-cause split.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires
- ActionQuery reopened tickets this week and last from PostgresPostgres
- LogicCompute reopen rate by category and week-over-week delta
- ActionWrite trend narrativeOpenAI
- OutputPost weekly trend report to SlackSlack
What it does
It produces a weekly management view of the reopen problem from your support data warehouse: how many tickets reopened, the incomplete-fix vs unclear-resolution split, and which product categories are getting worse. It compares against the prior week so the trend, not just the snapshot, is visible.
When to use it
Use it for the weekly support ops review when you need numbers, not anecdotes. Assumes Zendesk (or similar) data is already synced into a Postgres warehouse with solve and reopen timestamps.
How it works
- 1A weekly schedule fires the run.
- 2Query Postgres for tickets reopened within N days of solving, this week and last week, joined to category and cause tags.
- 3A logic step computes reopen rate per category and the root-cause split, then the week-over-week delta.
- 4An OpenAI step writes a short narrative highlighting the biggest movers.
- 5Post the report and table to the support ops Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 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.
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Run this workflow in your colony.
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