CUSTOMER SUPPORT
Weekly low-deflection article digest
Each week it pulls article-view and ticket data, ranks help articles by how often they were shown but failed to deflect.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule (Monday morning)
- ActionQuery article views and ticket events from PostgresPostgres
- LogicCompute deflection-failure rate; filter high-traffic offenders
- ActionUpdate Notion tracking page per articleNotion
- OutputPost ranked worst-10 digest to SlackSlack
What it does
Produces a weekly ranked list of the help articles that are deflecting the least. It joins how many times each article was viewed against how many of those sessions still opened a ticket, computes a deflection-failure rate, and publishes the bottom performers so the team always knows the top rewrite candidates.
When to use it
Use this for a recurring docs review ritual. Instead of reacting to one-off escalations, you get a stack-ranked backlog every Monday showing which articles waste the most reader attention without resolving anything.
How it works
- 1A weekly schedule triggers the run.
- 2It queries Postgres for article views and linked ticket-creation events over the trailing 7 days.
- 3A logic step computes failure rate per article (escalations divided by views) and filters to articles with meaningful traffic and a high failure rate.
- 4It writes or updates a Notion database page per offending article with the week's numbers and trend.
- 5A ranked summary of the worst 10 articles is posted to the support Slack channel with links to each Notion page.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect NotionPages, databases, comments.
- 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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