On a schedule
Get a daily list of calls on your numbers
Each morning you see yesterday's calls with caller, duration and whether they were answered.
- Runs
- On a schedule
- Apps
- Twilio
- AI
- Not needed
- Access
- read
Send this to your assistant
Create a ClickRuntime automation: every day at 8am, email me yesterday's calls on my Twilio numbers grouped by answered and missed, with caller, duration and totals.
First time? Adding ClickRuntime to your assistant takes about two minutes.
Why use it
Why teams use this automation
A small business that runs on phone calls has no easy way to see how the phone performed yesterday. Twilio's console has every call, but it is a long list with no summary. The owner of a clinic or repair shop only gets a feeling for missed calls from frustrated customers, not from numbers, so staffing and opening hours get decided on hunches.
Each morning, this lists yesterday's calls on your Twilio account, groups them by status such as completed, no answer, busy or failed, and emails you a table with the caller, duration and result, plus totals. You know how many calls came in and how many were missed before the day starts.
It is useful for owners who want to know how well the phone is being answered. Staff can start the day by calling back anyone who was missed.
What you get out of it
Missed calls become visible
A table showing nine missed calls at 5 pm tells you more than an impression. You can see that the gap is at the end of the day and decide whether to extend cover.
Totals at a glance
Counts of answered, missed and failed calls give a quick sense of the day. You can track whether the answer rate improves after a staffing change, with real numbers behind the conclusion.
Callers to ring back
The list includes numbers of people who called and were not answered. Your team can return those calls first thing in the morning, while the caller is still looking for help.
Call length shows workload
Durations reveal which calls are long and which are quick. An unusual spike in duration can signal a difficult issue or a process problem, such as a confusing booking step.
Data for decisions about hours
A few weeks of digests show when calls arrive. That evidence helps you set opening hours and shifts based on demand, instead of guessing which afternoon is busiest. Opening hours and staff rotas then rest on facts.
How it works
What happens, step by step
Every morning at 8, ClickRuntime lists yesterday's calls on your Twilio numbers.
It counts how many were answered, missed or busy.
You get one email with those totals, then a line per call with the time, caller, length and outcome.
Before it runs live
- Connect Twilio
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 Twilio steps into one automation
Under the hood
The code that runs this automation
from collections import Counter
from datetime import date, timedelta
from clickruntime import on_trigger, credentials, http, notify
@on_trigger
def run(event):
sid = credentials.secret("TWILIO_ACCOUNT_SID")
yesterday = date.today() - timedelta(days=1)
calls = http.get(f"https://api.twilio.com/2010-04-01/Accounts/{sid}/Calls.json",
auth=(sid, credentials.secret("TWILIO_AUTH_TOKEN")),
params={"StartTime>": str(yesterday), "StartTime<": str(date.today()), "PageSize": 500}).json()["calls"]
by_status = Counter(c["status"] for c in calls)
rows = [f"{c['start_time'][17:22]} {c['from']:<15} {int(c['duration'] or 0) // 60}m{int(c['duration'] or 0) % 60:02d}s {c['status']}" for c in calls]
notify.email_me(f"Calls on {yesterday}: {len(calls)}", ", ".join(f"{k}: {v}" for k, v in by_status.items()) + "\n\n" + "\n".join(rows))
return dict(by_status)FAQ
Common questions
Does it include outbound calls?
What time zone is yesterday?
Why might some calls show as failed?
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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