Before opening Make: choose a process worth automating
Make.com can connect applications, transform data and run branching logic in a visual scenario. That does not mean every manual task should be automated. The best first candidate has meaningful volume, clear rules, stable inputs and a visible cost of failure. If someone copies data between a form, a CRM and a task manager thirty times a week, the benefit is measurable. If the process runs once a month and every case is different, standardise it first.
Describe the current flow using five fields: trigger, input, decision, action and owner. Record a baseline for processing time, omissions and delay. Those numbers will tell you whether the scenario improves the operation. Use sample records and a test pipeline for the first build so that the scenario cannot change live customer data until the logic and permissions have been reviewed.
Automate a stable process. If the rules change every week, Make will only encode today's chaos.
The shared architecture of a reliable Make scenario
Use a webhook when the source can send an event immediately. If an application has no instant trigger, use scheduled polling but retain an external ID or last-processed timestamp. This prevents a rerun from creating a second customer, project or invoice. Name modules after the business action—“Find contact by email,” not “Search record 2”—and add short notes in the scenario itself.
| Layer | What you configure | Practical check |
|---|---|---|
| Trigger | Webhook or scheduled polling | Can the same event arrive twice? |
| Validation | Required fields and formats | What happens when an email or ID is missing? |
| Logic | Filters, routers and transformations | Is every route condition explicit? |
| Actions | Create or update records | Which system is the source of truth? |
| Control | Error handler, retry and alert | Who is notified and how is work recovered? |
| Evidence | Execution log and business timestamp | Can the team establish what happened? |
Process 1: website lead to CRM and accountable owner
Do not automatically send a personalised proposal based only on unstructured enquiry text. A safer first version sends a confirmation to the prospect and creates a task for a salesperson. Track median time to first response, leads without an owner and duplicates. If AI classifies the enquiry, restrict it to approved categories and send low-confidence cases to a review queue.
Trigger
The website form sends a custom webhook to Make. Capture source, campaign, consent, name, company, email and enquiry text.
Validate
Normalise email and telephone values. Search HubSpot, Pipedrive or Monday CRM for an existing contact using a stable identifier.
Route
If the contact exists, add an activity; otherwise create it. Use a router to assign by service, country or company size.
Act
Create a time-bound follow-up, notify the correct owner and store a first-response deadline in the CRM.
Process 2: won deal to delivery-ready project
The trigger is a deal moving to Won. Make retrieves the client, service, value, start date and owner. It creates the correct Asana or Monday project from a template, a Google Drive folder, an onboarding checklist and a team notification. The scenario writes the project URL back to the CRM so sales and delivery see the same context.
Do not trigger on stage name alone. Add conditions for a signed agreement, confirmed start date and billing contact. Store the deal ID in every new record. On a rerun, Make should search for that ID and update the existing project instead of creating another one. Measure time from Won to kickoff readiness and the number of projects that start without required information.
Process 3: invoice, due date and payment follow-up
After an approved milestone, Make can retrieve billing data from the CRM, create a draft invoice in the supported finance system and request review. A person verifies tax, contract and bank details. Only then is the invoice sent and its number, value and due date written back to the project. This removes re-keying while keeping a human checkpoint around a high-risk action.
A second scheduled scenario checks unpaid invoices each business day. Filters separate “before due date,” “up to seven days overdue” and “escalate.” Messages use approved templates and stop as soon as payment status becomes paid. Do not rely only on a sent email: create an activity log and a finance-owner task when status is missing or delivery fails.
Process 4: client onboarding without missing steps
When a new client becomes active, the scenario sends a welcome message through Brevo or Mailchimp, creates the client folder, adds standard tasks and schedules a check-in. A router selects the correct onboarding package by service. If the client has not completed a required form after three days, Make sends a reminder and alerts the account owner. Completion activates the next tasks automatically.
Keep marketing consent separate from operational communication. A service onboarding message and a newsletter have different purposes and may rely on different permissions. Store consent source and timestamp in the system that owns the contact profile. Measure time to first value, completion rate and manual reminders—not the raw number of emails sent.
Process 5: weekly management digest
On Monday morning, Make retrieves a limited set of CRM, delivery and finance data: new leads, pipeline value, overdue tasks, capacity, invoices issued and overdue payments. It transforms the fields into a common format and writes them to Notion, Google Sheets or a BI dataset. The system then sends a concise digest with links to source records, rather than a table of untraceable numbers.
Define every metric before automating it. “Active customer” and “late project” must mean the same thing across systems. If AI drafts the narrative, provide structured figures and ask it to highlight exceptions without inventing causes. Numbers remain sourced from business systems; AI formats and summarises. Include a timestamp and a warning when one source is incomplete rather than publishing a misleading report.
Production launch: a 14-day control checklist
Build the happy path and validation in week one. Add exception handling, alerts and execution monitoring in week two. Launch with limited volume and review every result. The automation is ready not when it runs once, but when failure is predictable and manageable. After thirty days, compare the baseline: time saved, successful execution rate, omissions and operating cost. Only then repeat the pattern for another process.
- Name a business owner and a maintainer for the Make scenario.
- Use service accounts and least privilege rather than personal credentials.
- Test missing fields, duplicates, invalid formats, timeouts and an unavailable app.
- Configure the appropriate error handler, incomplete executions and a named alert channel.
- Set a monthly execution or credit threshold and monitor unexpected spikes.
- Document the trigger, systems, fields, owner, recovery method and last test date.
- Run in parallel for one week and compare outputs with the manual process.
Sources and further reading
Product capabilities change. The links below are primary or official sources reviewed when this guide was published.