Weekly
Get a weekly digest of what reviewers say
Every Monday you see last week's reviews sorted into themes and moods, with the harshest ones quoted.
- Runs
- Weekly
- Apps
- Trustpilot
- AI
- Yes, uses the built-in AI allowance
- Access
- apikey (public)
Send this to your assistant
Create a ClickRuntime automation: every Monday at 9am, take last week's Trustpilot reviews, group them by sentiment and topic such as delivery, price and support, and email me the summary with the three worst reviews quoted.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
A business with hundreds of Trustpilot reviews cannot read each one carefully. The owner skims the stars, notices the average is 4.2 and stops there, while the same complaint about slow delivery appears fourteen times in the last month. By the time anyone connects the dots, the pattern has cost sales and a lower score.
Every week, this collects reviews posted since the last run and passes them to an AI step that identifies the main themes people praise and complain about, with the overall sentiment. The summary arrives by email, so you read one page instead of dozens of reviews.
Customer experience leads and founders use it to decide what to fix first. The goal is to turn a pile of reviews into a short list of things worth acting on, so patterns are caught while they are small and cheap to fix.
What you get out of it
Complaints are grouped into themes
Fourteen reviews about late delivery become one line in the email. Seeing a repeated problem named and counted gets it onto the agenda, where scattered individual reviews would be shrugged off.
Praise you can reuse
The summary shows what customers love, such as friendly support or fast setup. That tells marketing which strengths to highlight and tells the team which habits to protect. Marketing can then use real customer phrases.
Reading time drops sharply
Reading a week of reviews can take an hour. A one-page summary takes two minutes, so the review trends get looked at weekly rather than being skipped because nobody has the time.
Earlier warning of declines
A change in sentiment from one week to the next shows up before the star average moves. You can respond to a product or service issue while only a handful of customers are affected.
Evidence for decisions
When you argue for a fix, a weekly theme summary backs it up with real customer words. It is easier to win budget for a change that customers are visibly asking for.
How it works
What happens, step by step
Every Monday, ClickRuntime collects the Trustpilot reviews posted in the past 7 days.
AI reads them, sorts each into positive, neutral or negative, and groups them by theme such as delivery or support.
You get an email with the mood counts, each theme with what reviewers said, and quotes from the harshest reviews.
Before it runs live
- Connect Trustpilot
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 Trustpilot steps into one automation
Under the hood
The code that runs this automation
from datetime import datetime, timedelta, timezone
from clickruntime import on_trigger, credentials, http, ai, notify
BUSINESS_UNIT_ID = "your-business-unit-id"
@on_trigger
def run(event):
since = (datetime.now(timezone.utc) - timedelta(days=7)).isoformat()
reviews = http.get(f"https://api.trustpilot.com/v1/business-units/{BUSINESS_UNIT_ID}/reviews",
params={"apikey": credentials.secret("TRUSTPILOT_API_KEY"), "perPage": 100,
"orderBy": "createdat.desc"}).json()["reviews"]
week = [r for r in reviews if r["createdAt"] >= since[:19]]
if not week:
return {"reviews": 0}
lines = "\n".join(f"{i}. {r['stars']}★ {r['title']}: {r['text'][:400]}" for i, r in enumerate(week, 1))
summary = ai.generate(lines, max_output_tokens=900,
system="Group these reviews by sentiment and by topic (delivery, price, support, product, other) "
"with counts. Then quote the three worst reviews word for word.").text
notify.email_me(f"Trustpilot: {len(week)} reviews last week", summary)
return {"reviews": len(week)}FAQ
Common questions
Does the AI read the full text of each review?
What if there were no new reviews this week?
Can it pick out reviews that need a reply?
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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