Weekly
See your top and fastest-rising pages
A weekly email lists your most viewed pages and those that grew most since the week before.
- Runs
- Weekly
- Apps
- Google Analytics
- AI
- Not needed
- Access
- analytics.readonly
Send this to your assistant
Create a ClickRuntime automation: every Monday, email me my 20 most viewed pages last week and the 10 that grew most compared with the week before.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
A blog editor wants to know which posts deserve an update, but Google Analytics only answers that after navigating to the pages report, setting two date ranges and sorting by change. She has been meaning to do it for months. Meanwhile a post that doubled in views last week sits stale with an out-of-date screenshot, and a great opportunity to capture that interest goes unused. A reader skims the same stale advice.
Each week, ClickRuntime pulls page views by page path for the last two weeks, ranks pages by total views and by growth, and emails both lists. You see your biggest pages and the ones climbing fastest, which tells you where fresh attention would pay off.
Documentation teams and ecommerce category managers use the same view to watch what customers read.
What you get out of it
Updates go where interest is rising
A page whose views doubled deserves a refresh now, while the traffic is there. Improving the call to action on a rising post often converts more of it into subscribers or sales.
Content planning based on evidence
Seeing what readers actually viewed beats guessing. Editors can commission a follow-up to a rising article, or a deeper guide on a topic that keeps appearing in the top list.
Stale top pages get noticed
Your most-viewed pages carry most of your traffic, so errors there are costly. A weekly look reminds you to fix broken links and old prices on pages that many people see.
Early signs of a viral or press hit
Fast climbers often reflect a mention somewhere. Spotting it in a few days lets you add internal links and a signup form while the wave is still moving. A few days of lead time makes a real difference to how much of it you capture.
Pruning decisions get easier
Pages that never reach the top or the growth list are candidates for merging or removal. Over time the site gets tighter, which helps readers and search engines. Fewer, stronger pages are easier to maintain and tend to rank better than a pile of thin ones.
How it works
What happens, step by step
Every week, ClickRuntime pulls page views for each page on your site from Google Analytics, for this week and the week before.
It ranks the ten most viewed pages and the five that gained the most views since last week.
You get one email with both lists, showing the views or the gain next to each page.
Before it runs live
- Connect Google Analytics
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
- Add an AI step, for example to summarize, sort or draft a reply
- Add another app, for example also send it to Slack
- Combine it with other Google Analytics steps into one automation
Under the hood
The code that runs this automation
from clickruntime import on_trigger, credentials, http, notify
PROPERTY = "123456789"
@on_trigger
def run(event):
rows = http.post(f"https://analyticsdata.googleapis.com/v1beta/properties/{PROPERTY}:runReport",
headers={"Authorization": f"Bearer {credentials.connection('google', 'work')}"},
json={"dateRanges": [{"startDate": "7daysAgo", "endDate": "yesterday", "name": "this"},
{"startDate": "14daysAgo", "endDate": "8daysAgo", "name": "last"}],
"dimensions": [{"name": "pagePath"}], "metrics": [{"name": "screenPageViews"}], "limit": 500},
).json().get("rows", [])
views = {}
for r in rows:
page, rng = r["dimensionValues"][0]["value"], r["dimensionValues"][1]["value"]
views.setdefault(page, {"this": 0, "last": 0})[rng] = int(r["metricValues"][0]["value"])
top = sorted(views.items(), key=lambda kv: -kv[1]["this"])[:10]
growth = sorted(views.items(), key=lambda kv: -(kv[1]["this"] - kv[1]["last"]))[:5]
text = "Most viewed:\n" + "\n".join(f"{v['this']:>7,} {p}" for p, v in top)
text += "\n\nFastest growing:\n" + "\n".join(f"{v['this'] - v['last']:>+7,} {p}" for p, v in growth)
notify.email_me("Top pages this week", text)
return {"pages": len(views)}FAQ
Common questions
How are pages ranked for growth?
Does the report include the page title or just the path?
Can I exclude pages like the homepage or checkout?
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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