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playbook

Run a weekly support operating system

Triage the queue, draft the high-volume replies, escalate the real bugs, refresh the macros, and roll the patterns into a voice-of-customer report — one repeatable rhythm that shrinks the queue at its source.

advanced ~half a day

when to reach for this

Run support reactively and you spend every week emptying a bucket that refills overnight — answering the same questions, missing the bug behind fifty of them, and never getting upstream of the cause. The fix is a weekly operating rhythm where each piece feeds the next: triage finds the patterns, replies clear the volume, bugs get escalated, the macro library and help center absorb the repeats, and a report rolls it all up so product fixes the source. This is the capstone that ties the other Customer Support playbooks into one loop — so the queue gets smaller every week instead of just emptier each night.

gather this first

  • The week's ticket export as tickets-week.csv — scrubbed of names, emails, and account numbers to [customer] before upload.
  • Your reusable assets: macros.md from the canned-response library and your help-center article list, so this week's patterns update them instead of starting cold.
  • A fixed slot on the calendar — same half-day each week — because the power of an operating system is that it runs on a rhythm, not when you remember to.

the workflow

  1. Triage the week to find the patterns

    Start by running the *Find what the queue is really about* playbook on the week's export — cluster by root issue, rank by volume, separate the bugs from the noise. Everything downstream keys off this map.

    you ask 
    Read tickets-week.csv. Confirm the row count and date range, then group by underlying issue (not wording), give me the top 6 clusters with counts and one example each, and flag which clusters look like a recurring bug versus normal support. This is the input for the rest of the week's work.

    what you get back A ranked, count-backed map of the week — "login loop (52), double-charge (38, looks like a bug), shipping delay (29)..." — with the bug candidates flagged. The same output the triage playbook produces, now feeding the loop.

    Verify the headline counts against the raw export here — every later step trusts this map, so a wrong number propagates all the way to the report.

  2. Clear the volume with drafted replies

    Run the *Draft a reply that sounds like a person* playbook against the biggest clusters, pulling from macros.md where a template already fits — so you clear the most tickets per minute without going robotic.

    you ask 
    For the top 3 clusters, draft a warm reply in my voice for each — own the issue, one clear next step, [name] and [order number] placeholders, and pull from macros.md if a template fits. Do not invent any order number, refund, ship date, or policy. Flag any cluster where a single reply can't fairly cover the variation.

    what you get back Three on-voice draft replies keyed to the highest-volume clusters, placeholders for every private detail, and a flag where a cluster is too varied for one template — clearing the bulk of the queue fast.

  3. Escalate the real bug, not the symptoms

    Take the flagged bug from triage and hand engineering a tight, evidence-backed report instead of forwarding forty tickets — the count and shared trigger are what get it prioritized over answering it fifty more times.

    you ask 
    The double-charge cluster is flagged as a bug (38 tickets). Write a 4-sentence escalation for our tracker: what's happening, who's affected and how many, the shared trigger, and 2 example ticket IDs as evidence. Neutral, specific, no guesses about the code.

    what you get back A paste-ready bug report with the pattern, the count, the trigger, and example IDs — the one escalation that stops the cluster at its source instead of generating thirty-eight more replies next week.

  4. Refresh the macros and help center from the repeats

    Feed this week's recurring clusters into the *canned-response library* and *help center* playbooks — promote the questions that keep coming back into a template or an article, so next week's volume is lower by design.

    you ask 
    Two clusters repeat from last week: 'how do I change my plan' and 'where's my invoice.' For each, draft a macro for macros.md AND a short help-center article (numbered steps, plain language, 'still stuck?' line, [confirm the steps] where you don't know the real flow). These should absorb the question so it stops hitting the queue.

    what you get back A new macro and a draft help article per repeating cluster — the mechanism that converts a recurring ticket into a self-serve answer, shrinking the queue rather than re-emptying it.

    This is the step that makes the system compound — every week a few repeats become permanent self-serve answers, so the baseline volume trends down.

  5. Roll the week up into the report

    Close the loop by running the *voice-of-customer* playbook on the week's clusters — themes, friction, requests, bugs, with counts and impact — so leadership and product fix the causes you can't fix from the queue.

    you ask 
    Roll this week's clusters into a short voice-of-customer report: a 4-bullet summary, the themes split into friction / requests / bugs / praise with counts and anonymized quotes, and the top 3 things product should look at with owners. Frame the rankings as recommendations to verify. Paste-ready for our team channel.

    what you get back A factual, count-backed weekly report with a prioritized handoff to product — the upstream half of the system, sending causes to the people who can remove them so next week's queue starts shorter.

make it your own

  • **Run the loop component by component:** each step is a full playbook on its own — *Find what the queue is really about*, *Draft a reply that sounds like a person*, *Build a canned-response library you'll actually reuse*, *Build a help center from the questions you actually get*, and *Turn a month of tickets into a voice-of-customer report* — so you can dive into any one when it needs more depth than the weekly pass gives it.
  • **Monthly zoom-out:** keep the weekly rhythm tactical, then run the voice-of-customer playbook on a full month every fourth week for the trend lines a single week can't show.
  • **Automate the rhythm:** wire the whole loop into a /support-week custom command or a scheduled agent (see the Playbook's *Features* tab) that drafts the triage map and the report cut from Monday's export, so you start each week editing instead of from a blank queue.

watch out for

  • The loop only compounds if you verify at each handoff — confirm counts against the raw export, check that drafted replies promise nothing unauthorized, and validate help-center steps in the real product before any of it propagates downstream.
  • You'll touch a full week of tickets in one sitting — scrub names, emails, and account numbers to [customer] before upload, keep [placeholders] in every reply, and anonymize quotes in the report.
  • Claude runs the rhythm; a human owns every decision in it — which bug to escalate, what to promise a customer, whether a recommendation in the report is right. The system makes you faster at the work, not absent from it.

you'll end up with A repeatable weekly rhythm that empties the queue and shrinks it — patterns found, volume cleared, the real bug escalated, repeats converted into self-serve answers, and the week rolled into a report — so support gets upstream of its own work instead of refilling the bucket every night.