n8n vs Make vs Zapier — A Practitioner's Decision Tree

When Zapier wins

Simple, linear workflows — trigger, one or two actions, done. Low volume. A non-technical team member needs to be able to open it, understand it, and fix it without you. Zapier's constraint is also its strength: it's hard to build something so complex that the next person can't maintain it.

When Make wins

Mid-complexity logic — branching paths, multiple conditions, several data transformations in one flow. Still visual and still no-code, but built for someone comfortable thinking in flowcharts. Make is the right choice when Zapier's linear model starts fighting the actual shape of the process you're automating.

When n8n wins

Complex logic, high volume, or a real requirement to self-host and keep data off a third party's servers. n8n has a steeper learning curve and genuinely benefits from someone dev-adjacent maintaining it, but at scale its per-execution cost and flexibility beat both alternatives, and self-hosting matters if you're in a regulated industry or just don't want customer data flowing through another SaaS vendor.

The decision tree, as questions

• Is the logic linear (trigger → action) or branching (if this, then one of several paths)? Linear leans Zapier, branching leans Make or n8n.
• Who maintains this after the build — a non-technical team member, or someone comfortable with more complexity? Match the tool to that person, not to what you personally prefer.
• Does data residency or self-hosting matter for compliance or cost at volume? If yes, that's n8n's strongest case.
• What's the actual monthly volume? Per-task pricing models (Zapier, Make) get expensive fast at high volume in a way self-hosted n8n doesn't.

What we actually use, and why

Most engagements start on Make for the visual accessibility during the build phase, with an explicit conversation about whether n8n makes sense once volume and complexity are clearer. The tool is never the point — the point is whether the automation still works and is still maintainable a year after the person who built it has moved to the next problem.

The same workflow on each platform

Take a common example: a new lead fills in a form, and you want to add them to the CRM, notify sales in a chat channel, and send a welcome email. On Zapier, that is one trigger and three actions in a straight line, and anyone on the team can read it top to bottom. It is hard to get wrong.

Now add real-world conditions: leads from one country go to one salesperson and the rest to another; existing contacts should be updated rather than duplicated; leads with a company email get a different sequence from leads with a personal one. On Zapier this becomes several separate zaps or a tangle of paths. On Make it is one visual scenario with routers and filters you can see at a glance. On n8n it is one workflow where you can also drop in a few lines of code for the parts that are awkward to express visually.

Maintenance is the real cost

Build cost is a one-off. Maintenance is forever. Every automation will break at some point: an app changes its API, someone renames a field, a form adds a new question. The question that should drive the platform choice is who will be fixing it at that moment, and how quickly they can understand what it does.

This is why the most capable tool is not always the right one. A powerful n8n workflow that only its original builder understands becomes a liability the day that person moves on. A plain Zapier workflow that an office manager can read and repair may be worth more to the business, even if it is less elegant.

Mistakes we see when teams choose a platform

• Choosing based on what one enthusiastic team member already knows, not on who will maintain it
• Spreading automations across all three platforms with no record of what runs where
• Ignoring volume until the monthly bill arrives and the pricing tier has jumped
• Building without error handling, so failures are silent until a customer notices
• Moving platforms to fix a problem that was really a messy underlying process

When to migrate between platforms

Migration is worth considering when a platform is clearly fighting the shape of your workflows, when costs at your current volume have become significant, or when data-residency requirements change. It is rarely worth doing just because a newer tool looks better. Before migrating, write down every live automation, what triggers it, what it touches and who owns it. That inventory is valuable on its own and often reveals automations that can simply be switched off.

Who owns your automation stack

Someone in the business should own the list of automations: what exists, which platform it runs on, who built it and who gets the alert when it fails. That person does not need to build every workflow, but without them the stack grows quietly until nobody can say with confidence what is running.

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