Ticket Cluster
by
Support pattern detection for ecommerce teams: group tickets by the underlying cause, then route each cluster to a macro, a product fix, a content change or a proactive message.
Support teams handle tickets one at a time, which is the right way to treat a customer and the wrong way to see a pattern. Forty tickets about the same seam failure look like forty conversations, get forty replies, and never reach the person who could stop the forty-first. The work that would remove the volume entirely is invisible from inside the queue. This skill groups tickets by their underlying cause rather than by their category, then routes each cluster to a macro, a product fix, a content change or a proactive message, with an owner.
What It Does
- Groups tickets by underlying cause rather than by the tag an agent chose.
- Sizes each cluster in handling time and in the revenue behind it.
- Separates a question the site should answer from a defect that needs fixing.
- Detects a cluster that is growing before it becomes the week's volume.
- Finds the customers affected who have not written in yet.
- Routes each cluster to a macro, a fix, a content change or a message, with an owner.
Use Cases
- Turn forty tickets about one issue into one product conversation.
- Find the question that belongs on the product page rather than in a macro.
- Message the affected customers who have not complained yet.
- See which cluster is growing fastest before next week.
Example Session
What are people writing in about this week, and what should we do about it?
Four clusters cover 71% of the volume. Only one needs a macro.
- Cluster | Tickets | Handling time | Route | Owner
- Navy jacket seam failure | 38 | 19 hours | Product fix, recall batch | Quality
- Where is my order, holiday delay | 52 | 9 hours | Proactive message | Ops
- Tee sizing between two sizes | 31 | 7 hours | Product page content | Merch
- Discount code not applying | 24 | 6 hours | Macro plus checkout fix | Storefront
The seam cluster is a quality issue affecting one production batch, and 94 customers bought from that batch while only 38 have written in. Messaging the other 56 before they discover it costs a replacement each and preserves the relationship. The sizing cluster is not a support problem at all: it is a missing sentence on a product page, and it will keep generating seven hours a week until that sentence exists.
Why This Beats Prompting It Yourself
Ticket Tags vs The Cause Underneath Them: The Hidden Risk
A generic prompt groups tickets by the category an agent selected, which reflects how the ticket was handled rather than why it was sent. Returns, quality and shipping tags will scatter one seam failure across three buckets, and the pattern that would have triggered a batch recall never assembles.
When You Still Need The Customers Who Have Not Written In
Thirty-eight people complained and ninety-four bought from that batch. The fifty-six who have not written in are the ones where a proactive message still changes the outcome, and no view of the ticket queue will ever show them because they are not in it. Working backward from the cluster to the affected population is the step that converts support data into a save.
Known Limitations
Clustering is based on ticket text, so it is weaker on very short tickets and on languages outside your configured set, and small clusters are reported as unclassified rather than forced into a group. Linking a cluster to a production batch requires order and batch data to be joinable. It routes the clusters and assigns owners, and does not create tickets, tasks or messages in your systems.
Install It
- Download the ZIP.
It is free and there is no account to create. - Unzip it into your agent's skills folder.
Claude Code reads ~/.claude/skills/, which is hidden by default: the command in the folder block opens it. Other agents scan their own directory, so drop the same folder there instead. - Ask your agent to use it.
Restart the agent if it was already running, then it picks the skill up with no config.
skills folder
Copy
~/.claude/skills/ticket-cluster/
SKILL.md
references/cluster-rules.md
weekly/
# one file per week, with the route and owner
# macOS: create the folder and open it in Finder
mkdir -p ~/.claude/skills && open ~/.claude/skills
# Windows: paste in the Explorer address bar
%USERPROFILE%\.claude\skills\Frequently asked questions
How is this different from ticket tagging?
Tags record what an agent did. This groups tickets by what caused them, which regularly spans three or four tags, and then decides whether the answer is a macro, a fix, a content change or a message. A macro is the right answer far less often than tagging implies.
Which agents does the skill run in?
Any agent that supports the open SKILL.md format: Claude Code, Cursor, Codex CLI, GitHub Copilot, Gemini CLI, Manus, Grok and others load it unmodified. The format is portable, the location is not. Each agent scans its own skills directory, so you drop the same folder into whichever one yours uses. There is no config file to edit and no API key to provision.
What does it need connected to work?
Ticket text with timestamps and handling time, plus order data so clusters can be linked to products and batches. Batch-level data is optional and is what makes the proactive messaging possible.
Why route a cluster away from support?
Because a question that keeps arriving is usually a failure somewhere upstream. Writing a better macro for a sizing question makes each ticket cheaper and does not reduce the count. One sentence on the product page removes the cluster.
How does it find customers who have not written in?
By identifying what the complaining customers have in common, usually a product and a purchase window, and finding everyone else in that set. It is only as precise as your batch or order data allows, and the output states how wide the affected group is.
What is included with the skill?
The skill itself, the cluster rules reference, the weekly routing format, and the owner mapping. It is free and security scanned. We re-publish the ZIP when the rules change, so download it again if your clusters start shifting.
Support volume is a product problem wearing a helpdesk badge.
Polar ties ticket clusters to orders, SKUs and returns in one semantic layer, so the fix you assign lands where the cost is.
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