n8n vs Zapier vs Make: Which Automation Tool Should Your Business Use?

If you’re automating lead follow-up, CRM updates or reporting, you’ll quickly hit the same question: n8n, Zapier or Make? All three connect apps and run workflows. They differ in how easy they are, how they charge, and how much control you get.

Here’s how we choose for clients.

The short answer

• Zapier — easiest to start, biggest app library. Best for simple, low-volume workflows owned by non-technical teams.
• Make — visual builder with strong branching and data handling. Best for complex workflows at moderate volume, usually at a lower cost than Zapier.
• n8n — most flexible and can be self-hosted. Best for high-volume, AI-heavy or data-sensitive workflows, with a bit more technical setup.

Side-by-side comparison

Pricing and features change frequently — check each vendor’s current pricing page before you commit.

How usage is counted (and why it matters)

The biggest cost surprise in automation is how each platform counts usage:

• Zapier counts each successful action step as a task. A five-step workflow that runs 1,000 times can use thousands of tasks.
• Make counts operations — roughly each module that runs — which often works out cheaper for multi-step workflows.
• n8n Cloud counts a full workflow run as one execution regardless of steps; self-hosted n8n has no per-execution fee, but you pay for and maintain the server.

For a high-volume, multi-step workflow, that difference can be large. For ten runs a day, it barely matters — pick the tool your team finds easiest.

When we recommend Zapier

• The person maintaining the workflow isn’t technical.
• You need a niche app that only Zapier supports well.
• Volume is low and the workflow is simple, like “new form submission → add row to sheet → notify on Slack.”

When we recommend Make

• Workflows need branching, loops, filters or data transformation.
• Volume is moderate and cost matters.
• You want a clear visual map of a complex process.

When we recommend n8n

• You’re building AI agents or multi-step AI workflows with tools, memory and retrieval.
• Volume is high, and per-step pricing would get expensive.
• Data sensitivity means you want it running on your own infrastructure.
• You have — or want us to provide — someone technical to maintain it.

A typical example: WhatsApp lead follow-up

New lead from a Meta form → check for duplicates in CRM → create or update the lead → send an approved WhatsApp template → let an AI step classify the reply → notify sales if it’s a hot lead.

• In Zapier, this is quick to build but every step counts as usage at volume.
• In Make, it’s a clean visual scenario with routers for each reply type.
• In n8n, it’s one workflow with an AI agent node for the replies, and can run self-hosted for high lead volumes.

All three can do it. The right choice depends on volume, who maintains it and where your data needs to live.

Our recommendation

Start with the workflow, not the tool. Map the process, estimate monthly runs and steps, decide who will maintain it, and check where the data must live. Then the choice is usually obvious.

If you want a second opinion, our AI automation team can map your first workflow on a free strategy call, and the ROI calculator will estimate payback.