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How To Use Make? Step By Step Guide For Beginners

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Make (formerly Integromat) is a powerful visual automation platform that lets you connect different apps, services, and APIs to automate repetitive tasks without writing code. Instead of manually moving data from one app to another, you build automated workflows called Scenarios.

How Make Compares to Zapier

While Zapier is famous for its simple, linear, text based layouts, Make uses an open canvas.

  • Visual Map: You drag, drop, and link modules together like a mind map.
  • Complex Logic: You can branch workflows in multiple directions easily using “Routers”.
  • Cost Efficiency: Make counts “operations” (individual actions) rather than “tasks,” making it significantly cheaper for multi step workflows.

Core Terminology

  • Scenario: Your entire automated workflow from start to finish.
  • Module: A single step inside a scenario representing a specific app action (e.g., Google Sheets “Add a Row”).
  • Trigger: The event that starts your scenario (e.g., “When a new email arrives”).
  • Action: What happens after the trigger (e.g., “Create a Trello card”).
  • Router: A tool that splits your workflow into multiple paths based on specific conditions.
  • Operation: Every single action executed by a module counts as one operation against your monthly plan limit.

Step by Step Beginner’s Guide

To help you learn, we will build a real world starter scenario: Whenever you receive a new email in Gmail, Make will automatically save the sender’s details and message to a Google Sheet.

Step 1: Create a Free Account

  1. Go to the Make Signup Page.
  2. Create a free account.
  3. Select your organization name and preferred hosting region (US or EU).

Step 2: Prepare Your Google Sheet

Before touching Make, create the destination for your data:

  1. Open Google Sheets and create a blank spreadsheet.
  2. Name it Email Log.
  3. Label three columns in the first row: Date, Sender Email, and Subject.

Step 3: Create a New Scenario

  1. Log into your Make Dashboard.
  2. Click the Create a new scenario button in the top right corner.
  3. You will see a large empty workspace with a big circle and a plus sign (+) in the middle.

Step 4: Set Up the Trigger (Gmail)

  1. Click the large + icon in the center of the canvas.
  2. Search for Gmail and click on it.
  3. Select the trigger called Watch Emails.
  4. Click Create a connection and sign into your Google account to grant Make permission.
  5. In the settings popup, set Folder to Inbox and Criteria to All emails. Click OK.
  6. A popup will ask where to start watching; choose From now on and click OK.

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Step 5: Set Up the Action (Google Sheets)

  1. Hover over your Gmail module on the canvas and click the small Add another module circle attached to its right side.
  2. Search for Google Sheets and click it.
  3. Select the action called Add a Row.
  4. Click Create a connection to link your Google Drive account.
  5. Select your spreadsheet (Email Log) and choose Sheet1.
  6. Make will now display your column headers (Date, Sender Email, Subject).
  7. Click into the Date field. A panel of dynamic variables from your Gmail trigger will slide out. Click on the Date variable.
  8. Click into Sender Email and map it to the Sender > Email Address variable.
  9. Click into Subject and map it to the Subject variable. Click OK.

Step 6: Test Your Scenario

  1. Click the Run once button in the bottom left corner of the screen.
  2. Send a test email to your Gmail account from a separate email address.
  3. Watch the Make canvas. You will see numbers appear above the circles, indicating successful data processing.
  4. Open your Google Sheet to verify that the email information populated perfectly.

Step 7: Turn It On

  1. If the test worked, find the Scheduling switch at the bottom left of your screen.
  2. Toggle it from OFF to ON.
  3. Set your preferred interval (the free plan allows checks as often as every 15 minutes).
  4. Save your scenario by clicking the disk icon.

How To Use Make AI For Automating Finance Operations?

Using Make AI (which combines Make’s visual canvas with native AI assistants and OpenAI/Anthropic integrations) allows you to automate highly complex, unstructured financial tasks that traditional software cannot handle. Here is a comprehensive breakdown of how to use Make AI for financial operations, including actionable workflows and a step by step setup guide.

Core Capabilities: What Make AI Does for Finance

  • Unstructured Data Extraction: Pulls line items, tax numbers, and payment terms from messy PDF invoices or receipts.
  • Contextual Expense Categorization: Evaluates transaction descriptions against your specific chart of accounts to categorize expenses accurately.
  • Discrepancy Detecion: Cross references supplier invoices against purchase orders and flags anomalies or double billings.
  • Drafting Executive Summaries: Analyzes cash flow data rows and outputs structured executive summaries or natural language financial updates.

You can learn how to create interactive business reports with Power BI and DAX using guide for beginners.

Three High Impact Make AI Finance Workflows

Automated Invoice Processing & Reconciliation

  • The Blueprint: Incoming invoice emails are scanned → Make AI extracts the text → An AI prompt validates the total against an internal Google Sheet database → The data is instantly pushed to accounting platforms like QuickBooks or Xero.
  • Why AI matters: It reads visual data layout changes across different vendors without needing rigid templates.

AI Driven Expense Auditing & Policy Compliance

  • The Blueprint: Employees upload receipts to a communication channel like Slack or Microsoft Teams → Make AI extracts items, cost, and vendor → The AI checks the data against company policy rules (e.g., “Flag any meals over $50” or “Flag weekend purchases”) → It auto approves or pings HR.
  • Why AI matters: It evaluates the context of a purchase rather than just looking at a raw number.

Intelligent Cash Flow & Revenue Reporting

  • The Blueprint: Daily or weekly sales figures are pulled from Stripe or Shopify → Make AI organizes the raw numbers into trends → The AI drafts a summary report detailing changes in MRR (Monthly Recurring Revenue) or churn → It emails the draft to the CFO.

Step by Step Guide: Building an AI Invoice Processor

This starter workflow automatically parses an email invoice attachment, extracts key financial data via AI, and logs it into a tracking sheet.

Step 1: Set Up Your Tracking Sheet

  1. Open Google Sheets and create a sheet called AI Expense Tracker.
  2. Add these headers: Vendor Name, Invoice Date, Subtotal, Tax, Grand Total, and Risk Flags.

Step 2: Configure the Gmail Trigger

  1. Create a new scenario on Make.
  2. Add the Gmail module and choose the Watch Emails trigger.
  3. Set Filter criteria to look only for emails with attachments containing the word “invoice” or ending in .pdf.

Step 3: Add the Make AI Module

  1. Click Add another module next to Gmail.
  2. Search for the Make AI toolset (or the OpenAI / ChatGPT module if using custom API keys).
  3. Select the Extract Structured Data (or Prompt / Chat Completion) action.
  4. The Critical Prompt: Configure your AI prompt to act as a strict financial parser. Copy and paste something precise like this:
You are a strict financial data extraction API. Your job is to parse the attached invoice document and extract specific fields with 100% accuracy. Do not guess, summarize, or add conversational text. Output ONLY the following fields in plain text or structured variables:

1. Vendor Name: The official legal name of the merchant/supplier.
2. Invoice Date: The date the invoice was issued. Format strictly as YYYY-MM-DD.
3. Subtotal: The total amount BEFORE taxes and discounts. Numeric value only (e.g., 1250.50). Do not include currency symbols.
4. Tax: The total tax amount (VAT/Sales Tax). Numeric value only. If 0 or not specified, write 0.00.
5. Grand Total: The final amount due after all taxes and discounts. Numeric value only.
6. Risk Flags: Evaluate the document. Output "NONE" if everything looks standard. If you detect any of the following, list them: "MISSING_TAX_ID", "DUPLICATE_BILLING_SUSPECTED", "FUTURE_DATE", or "AMOUNT_MISMATCH" (if Subtotal + Tax does not equal Grand Total).

Strict Rule: If any field cannot be found with absolute certainty, return "NOT_FOUND" for that specific field. Never invent data.
  1. Map the Gmail attachment Data or URL input directly into this AI module.

Step 4: Map Extracted Fields into Google Sheets

  1. Add a final Google Sheets module using the Add a Row action.
  2. Connect your AI Expense Tracker sheet.
  3. Map the variable tags generated by the AI module directly into the corresponding sheet headers (e.g., Map the AI’s Vendor Name output to the Vendor Name column).

Step 5: Test and Activate

  1. Click Run Once in the bottom left corner.
  2. Send an email to your account with a sample invoice attached.
  3. Ensure the AI correctly parses the messy document text and populates the clean ledger. Toggle the Scheduling switch to ON.

Critical Safeguards for AI Finance Workflows

  • Always Keep a Human in the Loop (HITL): Never let an AI make an autonomous payout or push directly to tax records. Design Make scenarios to routing high value items to a “Pending Review” status in your ERP or accounting ledger.
  • Enforce Strict System Prompts: Explicitly instruct your AI modules to output data in fixed formats (such as ISO currency codes like USD/EUR or YYYY-MM-DD date structures) to avoid breakages in downstream systems.
  • Monitor Operation Usage: AI operations use higher computation tokens. Keep an eye on your Make Plan Limits to ensure your enterprise workflows remain within budget.
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