"Which automation platform should we use" is usually the wrong first question. The right one is "what does this workflow actually need to do" — because Zapier, Make, and n8n are built around different assumptions, and the wrong pick shows up as friction six months in, not on day one.
Zapier: the simplest thing that works
Zapier's whole design philosophy is trigger-then-action simplicity — connect app A to app B, add a filter or two, done. It has the largest app library of the three and the gentlest learning curve, which makes it the right default for straightforward automations that don't need much branching logic.
We used it for exactly that kind of job in a weekly marketing-analytics pipeline: collect daily app-performance metrics, process them with Python, add AI-written commentary, and deliver everything to Slack and Google Slides every Monday morning. Nothing about that workflow needed complex branching — it needed to run reliably on a schedule and hand off cleanly between a few well-defined steps, which is Zapier's strong suit.
The tradeoff is complexity ceiling and cost. Zapier's pricing scales with the number of tasks you run, and multi-step workflows with real conditional logic get awkward fast — you end up fighting the tool's simplicity once your automation needs the workflow equivalent of an if/else chain with five branches.
Make: the visual middle ground
Make (formerly Integromat) sits between Zapier's simplicity and n8n's flexibility. Its visual, node-based canvas makes branching logic genuinely easier to build and read than Zapier's linear "zaps," and its pricing is typically more forgiving at moderate complexity. Where it tends to win is workflows with real conditional routing — several different paths depending on the data — that still don't need custom code. Where it tends to lose to n8n is when you need to self-host for data-residency reasons, or when the built-in nodes don't cover an unusual integration and you need to drop into genuinely custom logic.
n8n: when you need full control
n8n is open-source, self-hostable, and built for workflows that need real logic — custom code steps, complex branching, and integration with systems that were never designed to be integrated with in the first place.
That last part matters more than it sounds. A recurring pattern across our client work is a source system with no API at all: a booking platform, a class-scheduling tool, a payment portal that only exposes a web UI. In an automated invoicing workflow, we used n8n with a headless browser (Browserless) to sign into a no-API platform with session cookies and capture the figures a person would otherwise pull by hand — something that's straightforward to reach for in n8n's code-step model and awkward to bolt onto Zapier's or Make's more constrained node libraries. The same pattern shows up in our retrieval-augmented support email agent, where n8n orchestrates a multi-step AI pipeline — normalize sender, look up the customer record, retrieve FAQ context from a vector database, draft with Gemini, save as a Gmail draft — that's genuinely custom logic, not a linear trigger-action chain.
The tradeoff: n8n asks more of whoever's building and maintaining it. Self-hosting means you own the uptime, and the flexibility that makes complex workflows possible also makes simple ones take longer to set up than they would in Zapier.
The actual decision framework
- A handful of apps, linear logic, "when X happens, do Y" — Zapier. Don't overbuild.
- Real branching logic across common apps, still no custom code needed — Make is often the sweet spot.
- No-API sources, complex multi-step logic, AI orchestration, or data-residency requirements that rule out a SaaS platform — n8n, usually self-hosted.
Most businesses don't need one platform forever. It's common to run Zapier for the simple stuff and n8n for the workflow that actually needs it — the mistake is picking one tool and forcing every automation to fit its shape.