Day 2: Make.com: Visual Automation with More Power

Zapier vs Make.com vs n8n

Three tools, same category, different tradeoffs. Pick the right one for each use case.

Zapier
  + Easiest to learn, largest app library
  + Best for simple 2-3 step workflows
  - Expensive at scale ($49+/mo for more than 5 Zaps)
  - Limited branching logic

Make.com
  + Visual canvas with branches, loops, filters
  + 1,000 free operations/month (vs Zapier's 100 tasks)
  + Much cheaper at scale
  - Steeper learning curve than Zapier

n8n
  + Open source, self-hostable (unlimited free)
  + JavaScript code nodes for custom logic
  + Best for technical users who want full control
  - Requires server setup for self-hosting

Rule of thumb: Start with Zapier for simple automations. Move to Make.com when you need branching or loops. Use n8n when you need to self-host or write custom code.

Make.com Fundamentals

Create a free account at make.com. What Zapier calls a "Zap," Make calls a Scenario. What Zapier calls a "step," Make calls a Module.

The big visual difference: Make shows you data flowing between modules. You can see exactly what data enters and leaves each module, which makes debugging much easier.

Key Make concepts:

• Router: The diamond shape. Creates branches — like an if/else statement. Different branches run based on conditions you set.
• Iterator: Processes a list of items one by one. Zapier handles this with "line items" — Make makes it explicit and visual.
• Aggregator: Collects multiple outputs and combines them into one. Useful after an iterator.

Build: Document Watch → AI Analysis → Slack

Create a new scenario in Make.com. Here's the flow:

Module 1: Google Drive — Watch Files in a Folder. Point it at a "Reports to Review" folder. Set the schedule to every 15 minutes. This triggers whenever a new file appears in that folder.

Module 2: Google Drive — Get a File Content. Use the file ID from Module 1 to get the text content. For Google Docs, use "Download a Document" in text format.

Module 3: OpenAI — Create a Completion. Add the OpenAI module. Set the model to gpt-4o-mini (fast and cheap for document analysis). Write this prompt:

Analyze this document and return a structured summary.

Executive Summary: (2-3 sentences)

Key Findings:
- (bullet 1)
- (bullet 2)
- (bullet 3)

Action Items: (explicit next steps, or "None identified")

Risk Flags: (anything that needs attention, or "None")

Document:
{{2.data}}

Map {{2.data}} by clicking the field and selecting the text output from Module 2.

Module 4: Slack — Create a Message. Add the Slack module, connect your workspace, and choose a channel like #reports or #team-digest. In the message body, map the OpenAI completion output and add the file name as a header. The final message will look like a clean professional brief every time a new document lands in the folder.