n8n vs Zapier vs Make: Which Automation Tool Fits Your Business?

Almost every business we work with has the same quiet problem: people spend hours each week copying data from one tool into another. A form submission gets pasted into a spreadsheet, the spreadsheet row gets retyped into the CRM, and someone remembers (or forgets) to post a heads-up in Slack. Workflow automation platforms exist to kill exactly that kind of busywork, and three names come up in nearly every conversation: Zapier, Make (formerly Integromat), and n8n.

All three can connect a web form to a CRM in an afternoon. The differences show up later, when your workflows get more complex, your volume grows, a step fails at 2 a.m., or your legal team asks where customer data is being processed. Picking the wrong tool rarely breaks anything on day one, but it can mean a painful migration a year in.

In this guide we compare the three platforms the way we do for clients: by how they bill, how hard they are to build with, how they handle errors, what they offer for AI, and what they mean for data privacy. We finish with two real-world workflow examples and a recommendation matrix you can use to make your own call.

The short version

If you only read one section, read this one:

• Zapier is the easiest to start with and has the largest catalog of ready-made integrations. It is ideal for non-technical teams running simple, linear workflows. It can get expensive as volume grows because you pay per task.
• Make offers a visual canvas with powerful branching, iteration, and data transformation, usually at a lower cost per unit of work than Zapier. It has a steeper learning curve but rewards people who think in flowcharts.
• n8n is a developer-friendly, source-available platform you can self-host or use as a cloud service. It shines for complex logic, custom code, AI agent workflows, and situations where data must stay on your own infrastructure.

How the pricing models actually differ

We deliberately are not quoting prices here, because all three vendors adjust their plans regularly. What matters more than today's numbers is what each platform counts, because that determines how your bill scales.

Zapier: billed by task

Zapier counts a task each time an action step successfully runs. A workflow (a "Zap") with one trigger and four actions uses roughly four tasks per run. Triggers and certain built-in utility steps are generally not counted, but every action that does real work is. A workflow processing 2,000 leads a month with four actions each consumes around 8,000 tasks.

Make: billed by operation or credit

Make historically counted operations: nearly every module that runs in a scenario, including the trigger, counts as one. Make has been moving toward a credit-based model, but the principle is similar: more modules and more loop iterations mean more consumption. Because loops over arrays count each iteration, a scenario that processes 50 line items per invoice can use far more units than you expect.

n8n: billed by execution (or free to self-host)

n8n Cloud counts executions: one full run of a workflow counts once, regardless of how many steps it contains. That makes long, multi-step workflows dramatically cheaper to run at scale. The self-hosted Community Edition has no per-execution fee at all; you pay instead for the server, maintenance, and the expertise to run it. Some enterprise features, such as SSO and advanced permissions, require a paid license.

Platform	Billing unit	What makes the bill grow	Self-hosting
Zapier	Task (per action step)	More steps and more runs	No
Make	Operation / credit (per module run)	More modules, more runs, loop iterations	No
n8n	Execution (per workflow run)	More runs only	Yes

A practical tip: before choosing, estimate your monthly runs and the number of steps per run for your three most important workflows. Multiply it out under each model. The difference is often small at low volume and large at high volume.

Ease of use and build complexity

Zapier

Zapier's editor is a vertical list of steps with plain-language prompts. A marketing coordinator can build a working Zap without training. Branching ("Paths"), filters, and formatters exist, but complex logic quickly becomes hard to read.

Make

Make uses a visual canvas where modules are bubbles connected by lines. Routers, iterators, and aggregators let you split data, loop over lists, and merge results. This makes it excellent for data-heavy flows, but people who have never thought about arrays and bundles usually need a few hours to get comfortable.

n8n

n8n also uses a node-based canvas, and it assumes a bit more technical comfort. You can drop into JavaScript or Python in a Code node, write expressions to transform data, call any REST API with the HTTP Request node, and inspect the exact JSON flowing between steps. For developers this is freeing; for non-technical users it can feel like a lot.

Integrations and extensibility

Zapier has the largest library of pre-built app connectors by a wide margin, with thousands of apps. If you rely on a niche SaaS tool, there is a good chance Zapier supports it and the others do not. Make has a large catalog too, with connectors that often expose more API endpoints per app than Zapier does. n8n has a smaller official library, supplemented by community nodes.

That gap matters less than it looks. Any of the three can call an arbitrary API through an HTTP or webhook step, and n8n in particular makes this easy enough that "missing integration" is rarely a blocker for a technical team.

Error handling and reliability

This is where we see the biggest difference between hobby automations and production automations. Every external API eventually times out, rate-limits you, or returns something unexpected. What happens next is what matters.

• Zapier sends error notifications, offers automatic replay of failed runs on some plans, and lets you add basic error-handling paths. Debugging is done through the Zap history, which is clear but limited for complex flows.
• Make has granular error handlers you attach to individual modules: retry, ignore, rollback, resume with a fallback value, or commit what succeeded. Incomplete executions can be stored and resumed. It is one of Make's strongest features.
• n8n supports per-node retry settings, "continue on fail" behavior, and dedicated error workflows that trigger whenever another workflow fails. You can route failures to Slack, log them to a database, or open a ticket. Execution logs show the full input and output of every node.

Whichever tool you pick, build in three things from day one: retries with a delay for transient failures, an alert to a human when a run fails permanently, and a way to safely re-run without creating duplicates.

AI features and agent workflows

All three platforms now offer AI steps: summarizing text, classifying emails, extracting fields from documents, or drafting replies with a large language model. The differences lie in depth and control.

• Zapier offers built-in AI actions and agent-style features aimed at business users, with minimal setup.
• Make provides modules for major AI providers and its own AI tooling, which fit naturally into its visual data flows.
• n8n has the most developer-oriented AI toolkit of the three, with nodes for building agents that use tools, memory, vector stores, and retrieval (RAG), and the ability to connect to self-hosted models. If you want an AI agent that looks up an order, checks a policy document, and drafts a response for human approval, n8n gives you the most control.

For more on where AI agents genuinely help (and where they do not), see our article on the rise of AI agents in customer support.

Data privacy, security, and compliance

When your workflows touch customer data, health information, or financial records, ask where that data is processed and stored. Zapier and Make are cloud-only, so your data passes through their infrastructure and their sub-processors. Both publish security documentation, and their compliance offerings vary by plan, so review them against your requirements.

n8n's self-hosted option is the main reason many regulated or privacy-conscious businesses choose it. You can run it inside your own cloud account (for example on AWS), behind your firewall, with your own encryption, backups, and access controls. The trade-off is responsibility: you are now in charge of updates, uptime, and security patches.

Two example workflows, built three ways

Example 1: Lead capture to CRM and Slack

A visitor submits your website's contact form. The workflow should create or update the contact in your CRM, tag the lead source, and notify the sales channel in Slack.

1. Trigger: a webhook receives the form data.
2. Search the CRM for an existing contact by email.
3. Create the contact if new, or update it if it exists.
4. Post a formatted message to Slack with the lead's name, company, and message.

This is a simple, linear workflow that every platform handles well. On Zapier it is quick to build with native steps. On Make and n8n it takes a few more minutes but costs less to run at volume. If this is the only workflow you need, Zapier's simplicity often wins. We cover the details of this setup in how to connect website leads directly to your CRM.

Example 2: Invoice processing

Supplier invoices arrive as PDF email attachments. The workflow extracts vendor, date, totals, and line items; checks them against purchase orders; and either pushes them into your accounting system or flags discrepancies for review.

1. Trigger: a new email with an attachment in a dedicated inbox.
2. Extract data from the PDF using an AI or document-parsing step.
3. Loop over line items and compare them with purchase-order data.
4. Branch: matching invoices go to accounting; mismatches go to a review queue with a Slack alert.
5. Log every run, and route failures to an error workflow.

Here the differences are obvious. Looping over line items inflates usage on per-operation billing, branching gets unwieldy in a linear editor, and the extraction step benefits from custom validation code. This is the kind of workflow where we typically reach for n8n, or Make for teams that prefer a fully managed tool.

Recommendation matrix

Your situation	Best fit	Why
Non-technical team, a handful of simple workflows	Zapier	Fastest to learn, widest app catalog
Visual thinkers, data-heavy flows, cost-conscious	Make	Strong branching and error handling on a visual canvas
Developer on the team, complex logic or custom code	n8n	Code nodes, full API access, execution-based billing
Strict data residency or privacy requirements	n8n (self-hosted)	Data stays on your infrastructure
High volume, many steps per run	n8n	Cost does not grow with the number of steps
Advanced AI agents with tools and retrieval	n8n	Most flexible AI and agent tooling

Frequently asked questions

Can we start on Zapier and move to n8n later?

Yes, and many businesses do. There is no automatic converter, so each workflow must be rebuilt, but simple workflows usually take minutes to recreate. Document your workflows as you build them to make any future migration easier.

Is self-hosting n8n hard?

Getting it running with Docker is straightforward for anyone comfortable with servers. Running it reliably in production, with backups, a proper database, queue mode for heavy loads, monitoring, and timely updates, is a real operational job. If nobody on your team wants that responsibility, n8n Cloud or a managed setup is the safer choice.

Need help choosing or building?

We design, build, and maintain production automations on all three platforms, with a particular focus on n8n and AI agents. If you want a second opinion on your current setup or a plan for automating a specific process, take a look at our AI agents and automation services or get in touch.