Weekly
Get a weekly summary of what customers struggled with
Each Monday you get the main themes and pain points from last week's tickets.
- Runs
- Weekly
- Apps
- Zendesk
- AI
- Yes, uses the built-in AI allowance
- Access
- read
Send this to your assistant
Create a ClickRuntime automation: every Monday at 9am, read last week's Zendesk tickets, group them into the top 5 themes with an example for each, and email me the summary.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
A head of support knows tickets are piling up but cannot say why. Reading 600 tickets from last week is impossible, tags are inconsistent, and the dashboard only counts them by status. Meanwhile the product team keeps asking what customers are struggling with, and the answer given in meetings is based on the three most memorable tickets, not the full picture.
Every week, last week's tickets are collected from Zendesk. The built-in AI reads their subjects and descriptions, groups them into themes, and writes a short analysis: the top issues, an approximate share for each, and a few representative examples. The write-up is emailed to you, ready to forward to product or leadership.
Valuable for support leads who report to product and for teams without a data analyst. The email can be forwarded to product without edits.
What you get out of it
Product hears the real top issues
Product managers get ranked themes with real examples, so roadmap discussions start from what customers actually raised, not from the three tickets people happen to remember. Examples are quoted from real tickets.
Patterns appear before they become crises
A theme that was small two weeks ago and is large now often signals a regression. The weekly read catches it while the cost of fixing it is still low and customers are still forgiving.
No analyst required
Reading and coding hundreds of free-text tickets by hand takes hours. The first pass by the AI means a person only reviews conclusions and spot-checks examples, which fits into a Monday morning.
Documentation gaps are exposed
A cluster of how-to questions about one feature tells you which help center article is missing or hard to find. Writing it removes a steady stream of tickets for weeks afterward.
A consistent record week after week
Saved emails build a history of what customers struggled with. In a quarterly review, you can show how themes rose and fell after releases, fixes and new documentation. A comparison with earlier weeks is easy.
Support's voice in planning
Support teams often know the pain points but lack figures. A weekly ranked summary with examples gives them evidence to bring to planning meetings, where evidence changes decisions more than opinion does.
How it works
What happens, step by step
Once a week, ClickRuntime collects the Zendesk tickets created in the last seven days.
AI reads them and groups them into the main problems customers had, with a count and an example ticket for each.
You get an email with the list of themes, biggest first.
Before it runs live
- Connect Zendesk
What you get
Build your own
Need it to work differently?
Your own rules
Conditions, thresholds, filters and exceptions, written the way you'd explain them to a colleague.
Any number of apps
One automation can read from one app and update several others. Over 248 apps are ready, and anything with an API works too.
AI where it helps
Summaries, classification, extraction and drafts use ClickRuntime's built-in AI, with no extra key.
On a schedule or on each event
Runs as often as every 5 minutes, or the moment an app sends an event, and keeps track of what it already handled.
Changes you can ask for
- Run it at a different time, more or less often, or only on weekdays
- Change what the AI looks for, or how it writes the result
- Add another app, for example also send it to Slack
- Combine it with other Zendesk steps into one automation
Under the hood
The code that runs this automation
from datetime import date, timedelta
from clickruntime import on_trigger, http, credentials, ai, notify
ZD = "https://yourcompany.zendesk.com/api/v2"
AGENT_EMAIL = "you@yourcompany.com"
def zd(method, path, **kw):
r = http.request(method, f"{ZD}{path}", auth=(f"{AGENT_EMAIL}/token", credentials.secret("ZENDESK_API_TOKEN")), **kw)
r.raise_for_status()
return r.json() if r.content else None
@on_trigger
def run(event):
since = (date.today() - timedelta(days=7)).isoformat()
tickets = zd("GET", "/search.json", params={"query": f"type:ticket created>={since}", "per_page": 100})["results"]
lines = "\n".join(f"#{t['id']} {t['subject']}: {(t['description'] or '')[:200]}" for t in tickets)
summary = ai.generate(f"Group these support tickets into the top 5 themes, with a count and one example ticket each:\n{lines}",
max_output_tokens=700).text
notify.email_me(f"Zendesk themes: {len(tickets)} tickets last week", summary)
return {"tickets": len(tickets)}FAQ
Common questions
Does the AI see customer personal data?
How are themes decided?
Can I analyze only one group or brand?
What permissions does it need?
Does it need AI?
How many runs does it use?
Can I change how it works?
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