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🎧 Customer Support report

Mon 8/17/26 to Sun 8/23/26

Report generated: Mon 9/21/26 @ 10:03pm Central

Last sync: Mon 9/21/26 @ 6:04am Central, 8,719 tickets.

Replayed: tickets and messages after that date are excluded, but each ticket's status is its status today, not its status then.

❤️ HEALTH🔍 DIAGNOSIS🌟 PRAISE

❤️ HEALTH

Is the desk ok right now?

📊 Activity

DayMsgs in<1h1-2h2-4h4h+Waiting
Mon 8/1719101111
Tue 8/18951100
Wed 8/191353010
Thu 8/2023114500
Fri 8/212495210
Sat 8/22000000
Sun 8/23000000

Business hours only. Rows do not sum to messages in: 21 more were closed without a reply, nearly all of them a client saying thank you. The ones that were not are under Bad closes.

🚨 Needs attention now

4 messages are waiting on a reply. Longest first.

WaitingCompanySubject

🔇 Bad closes

⚠️ 50 of 50 closed threads in this window are unjudged. An unjudged thread cannot appear as a bad close, so what follows is a floor, not the number.

To finish the window: python3 freshdesk/thread_evaluation.py --as-of 2026-08-24 --threads threads.md, read and judge them, then --verdicts verdicts.jsonl, then re-run this report.

📈 Against your own baseline

This week4w baseline
Tickets in51 ↓66-23%
Messages in88 ↓114-23%
Closed50 ↓64-22%
Still open1
Median response36m ↓42m🟢 -15% better
p90 response3.1h ↓4.3h🟢 -28% better
Still waiting1

Response times are per inbound message, not per ticket, and include messages still waiting at their elapsed-so-far duration. Dropping unanswered ones would mean ignoring a customer improved the percentile.
p90 is the number to watch: a fast median with a slow p90 is a desk that looks healthy and has a tail of people who were left.
Rows with for a baseline are cohort-aged: this week's tickets are days old and earlier weeks' have had a month to close, so comparing them would read as worse every week no matter what.

⏱️ Response distribution

Wait
p5044mhalf were faster
p751.8h
p903.3h10% waited longer than this
p958.1h
p998.2d1% waited longer
max29.3d
AnsweredMessagesShare
< 1 business hour24860%
< 4 hours37891%
< 1 business day39395%
< 3 business days40297%
> 7 business days71.7%

415 inbound messages over the trailing 4 weeks. A single week is too few messages for a p99 to mean anything.

⚡ What changed

🔍 DIAGNOSIS

Why, and who it is coming from.

🏢 Who

Ranked by change against each company's own 4-week baseline, so a client going from one ticket to six outranks a steady heavy user.

CompanyWeekBaselineChange
srascreening.com117.5+47%
ckranz@5
sorders@2
cgajjar@2
ezscreensolutions.com20.2+700%
briana@1
shea@1
sheridanig.com10.0new
cathy@1
robesoncountync.gov10.0new
patrick.cummings@1
pscprotects.com10.0new
mej@1
pbso.org10.0new
melvillen@1
dc.gov10.0new
anthony.biddiex@1
atlanticscreening.com10.0new
customercare@1

🏷️ Tags applied

Computed from the store, not inferred.

💬 Themes

Inferred: read from the ticket bodies, not computed.

Automated research attaches the wrong company, and we pay for it

Four tickets where work was done against an entity that was not the employer. Three ended in a billing credit, which is the cost showing up directly.

Dates keep coming back wrong, and one is now a formal dispute

Five tickets. A wrong date is the error that returns as a reinvestigation rather than a question, and one of these already has.

SLA expiry still is not firing

Five more tickets, the same pattern as last week. Orders run past their SLA, sit open, and a client tells us.

The inbound AI agent is recording answers that do not match the call

Three tickets. This is the worst kind of error we make: it is invisible unless the client listens to the recording, and one of them did.

Blueprints do not do what the client agreed to

Three tickets from two clients, all the same shape: the configuration on the account does not match the SLA they signed up to, and support cannot change it.

Completed work does not arrive on the client's side

Four tickets, including one going the other way: an order they dispatched never reached us.

🌟 PRAISE

Client praise, in their words.

No noteworthy praise this week.

Written by a Claude Code routine. Not for distribution outside Argus.