n8n vs Make.com vs Zapier: The Definitive 2026 Automation Platform Comparison for Trades

The three contenders, in plain English

Three platforms, three philosophies, three very different bills.

I have spent most of the last decade automating trades businesses. First my own heating and plumbing firm. Then Help me Fix. Now TrainAR. In that time I have used all three of these platforms in anger, on live commercial workflows, with real customers and real money on the line.

So this is not a feature checklist written from the marketing pages. This is what each one actually does for a UK trades business, what it costs once you scale it up, and where each one falls over.

Here is the plain English version.

n8n

Make.com

Zapier

Zapier is the original. Founded in 2011, based in California, runs as a SaaS only. You log in, pick a trigger, pick an action, pay for the tasks. There are over 8,000 apps connected and the onboarding is the easiest of the three. The bill creeps up fast once you have more than a handful of automations going.

Make.com used to be called Integromat. Bought by Celonis in 2020, rebranded in 2022, runs from the Czech Republic. Visual canvas, drag-and-drop modules, branching logic that actually shows you the data path. As of August 2025 they switched from "operations" to "credits" which annoyed some of their existing customers but the maths still works out cheaper than Zapier for complex flows.

n8n is Berlin-based, started in 2019, hit unicorn status in October 2025 with a $180 million Series C led by Accel. The thing that makes n8n different: you can self-host the open source version on a £4 a month VPS and pay zero for executions. Forever. It is also the most flexible if you want to write actual JavaScript or Python inside a workflow node, and it has the deepest AI agent toolkit of the three.

The average UK trades business I work with runs between three and seven SaaS tools: usually a job management platform, an accounts package, a calendar, a payment processor, sometimes a CRM, sometimes a forms tool. None of those tools talk to each other natively without help. That is what these three platforms are for.

Pricing in 2026: what you will actually pay

The list price is the start of the conversation, not the end.

The published pricing is misleading on all three. Each one uses a different unit, and the conversion between them is where small businesses get burned. Let me translate.

Zapier bills you per task. A task is one action step that runs inside one Zap. So a Zap that takes a new lead, filters it, looks it up in your CRM, sends a WhatsApp message and creates a calendar event uses four tasks every time it runs. Filters and built-in tools are now free, which helps. The Free plan gives 100 tasks a month. Professional starts at $19.99 a month for 750 tasks (annual billing) or $29.99 month-to-month. Team is $69 a month for 2,000 tasks with shared workspaces. Overage tasks bill at 1.25x your plan rate, capped at three times your task allowance.

Make bills you per credit, which used to be called an operation. Same idea: one module run equals one credit, with a couple of exceptions for code and AI modules that burn more. Free gets you 1,000 credits a month. Core is £7 a month (about $9 USD) for 10,000 credits. Pro is £13 (about $16) for 10,000 credits plus priority execution and custom variables. Teams is £22 (about $29) with shared scenario templates. As of November 2025, additional credit packs cost 25 percent more than included credits, so it pays not to run hot on Make either.

n8n is the awkward one to summarise. The self-hosted Community Edition is free software with unlimited executions. You pay for the server, which is between £3 and £6 a month on a basic VPS like Hetzner CX22, or £7 on a managed option. The cloud tier starts at €24 a month for 2,500 executions on Starter, goes to €60 for 10,000 on Pro, then €800 a month for Business. An execution is one whole workflow run no matter how many nodes it contains, which is a fundamentally cheaper unit than Zapier's tasks once a workflow has more than a couple of steps.

One thing the pricing pages will not tell you: Zapier and Make both run their billing cycles relentlessly. I have seen trades businesses get a $400 surprise when a Zap looped on itself for half a day. Make is better at flagging this in the operations log. n8n self-hosted cannot blow your budget because there is no budget to blow, but it can blow your server up if you build a runaway loop.

If you want a deeper dive into where these tools sit in the broader trades automation stack, the complete guide to AI tools for tradespeople covers the supporting layer.

Seven real trades workflows, tested

Each platform handles the same job differently. Some make it look easier than it is.

I built seven workflows on each platform. Same business logic, same source data, same target apps. Here is how they ranked.

Workflow 1: new website enquiry to WhatsApp. Form submission triggers a WhatsApp message to the duty engineer with the customer name, postcode and job type. Zapier did this in 8 minutes flat. Make took 14 minutes because the WhatsApp module wanted a bit more setup. n8n on cloud took 11 minutes. Self-hosted n8n was the slowest at 22 minutes because I had to configure the WhatsApp Business API connection myself. For one-off simple flows, Zapier wins on time.

Workflow 2: customer review request after job completion. Job marked complete in BigChange or Commusoft triggers a Google review request via SMS three days later, with a fallback if no review after seven days. Make handled the branching logic cleanest because the canvas shows you the wait paths visually. Zapier needed a Path step plus a Delay step which counts as two tasks. n8n was middling. If you are running this Google reviews automation at scale, Make is the budget winner.

Workflow 3: photo from completed job to social post. Engineer uploads a photo to a Drive folder, AI generates a caption, post goes to Facebook and Instagram. All three platforms can do this. n8n is the only one that lets you run the AI step locally on Ollama without sending your customer photos to OpenAI. For privacy-sensitive trades like security or commercial, that matters. There is a fuller breakdown in the Make.com social posting playbook.

Workflow 4: receipt photo to Xero. Engineer photos a receipt in WhatsApp, AI extracts the vendor, amount, VAT and category, the result lands in Xero with the right account code. This is the one where Make has the cleanest implementation, and the receipt-to-Xero playbook covers it step by step. Zapier can do it too but burns four tasks per receipt. n8n self-hosted is the cheapest at scale because a vehicle with 200 receipts a month still costs you £4.

Workflow 5: AI reply to customer enquiry. Inbound email or WhatsApp gets read by an LLM, classified, and either auto-replied or escalated to a human. n8n wins this one outright because of the LangChain AI Agent nodes. You can chain a router, a vector store of past replies, a tool that looks up job history, and a memory store, all visually. Zapier has AI Actions but they are simpler. Make has Maia and AI modules but the agent flow is less mature. The n8n AI agent reply guide shows the build.

Workflow 6: quote to invoice automation. Approved quote in your job platform pushes an invoice to Xero, sends a payment link, and schedules a follow-up. All three platforms can do this. Zapier feels fastest if you only have one job platform. Make and n8n are better when you have more than one source. I cover the broader pattern in quote-to-invoice automation for heating engineers.

Workflow 7: fleet job costing dashboard. BigChange job status, Xero invoice value, and engineer time logs combined into a real-time profit per job dashboard. This is where Make.com flexes its muscles, because the data aggregation runs cleanly with iterators and accumulators on the canvas. Zapier struggles with the multi-source aggregation. n8n handles it but you write more glue. The BigChange and Xero fleet costing build uses Make for exactly this reason.

AI capabilities compared

This is the section that has changed the most in the last twelve months, so a feature comparison written in mid-2025 is already wrong. Here is where each platform stands as of 2026.

AI is where the gap between the three platforms has opened the widest.

n8n ships with over 70 dedicated AI nodes built on LangChain. The AI Agent node accepts a chat model, an optional vector store, memory, and a list of tools that are themselves n8n sub-workflows or HTTP requests. Supported model providers include OpenAI, Anthropic, Mistral, Google Vertex AI, Ollama for local models, and any OpenAI-compatible endpoint. You can build a multi-step agent that classifies a customer message, looks up their job history in your CRM, drafts a reply, checks it against a tone-of-voice rulebook, and either sends it or escalates. All of that runs on a £4 VPS if you self-host. This is the deepest AI toolkit of the three by quite some margin.

Make.com has Maia, an AI assistant that builds scenarios from natural language descriptions. They also launched Make AI Agents in 2025 for autonomous task execution. The AI modules cover OpenAI, Anthropic and a handful of others. The catch is that AI module runs consume credits at a higher rate than standard modules, so the budget can disappear quickly if you build heavy AI flows. Good for medium complexity, less suited to deep agentic work.

Zapier has Zapier Agents, which they describe as autonomous AI systems that execute tasks across their 8,000+ apps without human intervention. There is also an AI Copilot that builds Zaps from natural language. Zapier AI Actions are pretty good for one-shot LLM calls inside a Zap. What it does not have is the deep agent orchestration that n8n offers. If you are building a true agentic workflow with tool use, memory and routing, you will hit the ceiling on Zapier first.

The supporting article on building an AI customer service bot covers the n8n agent build in detail.

Integrations: who connects to what

This is the bit Zapier wins on, no question. With 8,000+ apps connected, almost any SaaS tool a UK trades business uses has a native Zapier integration. Make is in the middle with around 3,000 native apps. n8n has around 500 native integrations but covers the gap with a generic HTTP Request node that can talk to any API.

For a typical UK trades stack, here is how that shakes out in practice.

The big one for UK trades is that the deeper field-service platforms like BigChange, Commusoft, Joblogic and Simpro do not have native modules on any of the three. You will need to build the connection through their REST API, which all three platforms can do via the HTTP node. The article on the UK field service platform showdown covers which of those has the cleanest API.

n8n is the only one of the three that lets you write a community node in TypeScript and share it. There is a community library at npm with hundreds of contributed nodes for things that have no official integration. That is useful if you are running a niche tool.

Learning curve and time to first workflow

The published claim is that 85 percent of non-technical users build their first Zapier automation within 15 minutes, against 35 percent for Make. That tracks with what I see on the ground. Zapier is the easiest. Make is harder but the canvas pays back the investment within a week. n8n is the steepest, and self-hosting it adds a few hours of server setup on top.

The harder the platform is to learn, the more it pays back at scale.

Here is my rough rule. A trades business owner with no technical background can be productive on Zapier in an afternoon. On Make.com you are looking at a weekend. On n8n cloud, give it a full week of evenings. On self-hosted n8n, the server admin work will eat another evening or two before you build anything.

That said, the documentation has improved on all three platforms. n8n's community forum at community.n8n.io is one of the best technical communities I have seen for any SaaS tool. Make has a strong educational arm called Make Academy. Zapier's docs are polished but skew towards their easier use cases.

If you want a structured introduction to automation thinking before you even pick a platform, I would point you at the systems playbook for trades businesses first. The platform you pick matters less than whether you have a clear process to automate in the first place.

Reliability, errors and support

Zapier has the best UX for handling errors. You get an email when a Zap fails, the error log shows the exact step and payload, and you can replay a single run from the dashboard. The downside is that Zapier has run loose with some reliability lately. Their Trustpilot score is 1.4 out of 5 with hundreds of reviewers, and complaints about duplicate triggers, missed runs and runaway loops are common. Some of that is users not configuring filters properly, but not all of it.

Make.com is more transparent about scenario runs. The operations log shows every module execution with the data that passed through. Their error handling lets you add a handler route to any module, which is closer to how a developer would think about exceptions. Support is mid-tier, slower than Zapier on the lower plans but more knowledgeable.

n8n self-hosted is as reliable as your server. If your VPS is up, n8n is up. The error logs are detailed because they are running on your own machine. Support on the Community Edition is community-only via the forum, which I would argue is better than most paid support I have used. Paid n8n Cloud has email support and a faster response on Business.

Data residency and UK GDPR

If you handle commercial contracts where your client cares about data residency, this section matters. If you are domestic gas and plumbing, you can probably skip ahead.

Zapier processes data in the US by default. They are SOC 2 Type II certified and have a UK GDPR data processing agreement available. For most trades work that is fine. For public sector contracts or NHS-facing work, it can be a blocker.

Make.com has data centres in the EU. EU customers can opt for EU-only processing. That meets UK GDPR comfortably for most use cases.

n8n self-hosted is the only one where your data never leaves a server you control. If you run it on a UK Hetzner box, your customer data, job details and integrations all stay on UK soil. That matters for compliance-sensitive sectors like fire safety, security or anything touching healthcare.

I should add: data residency is not the same thing as data security. You can self-host n8n on a UK server and still leak data if your environment variables are exposed or your API keys are in plain text. Compliance is a process, not a checkbox.

How to pick: a decision tree

Most trades businesses do not need to overthink this. Start with the simplest one that fits.

If you are a one-person trade or a small two-engineer firm with no technical staff, your decision tree is short:

• Need automation today, budget under £20 a month, fewer than five workflows: Zapier Professional.
• Same as above but you are willing to spend a weekend learning: Make.com Core for the lower bills.
• You have one tech-comfortable person and want to grow into AI workflows: n8n cloud Starter or self-hosted.

For a five-to-fifteen-person trades business with a couple of SaaS platforms and a real automation backlog:

• Mostly simple Zaps, want zero faff: Zapier Team.
• You want visual flows and a budget that does not scale linearly: Make.com Pro.
• You want AI agents, branching logic and the bill to stop going up: n8n self-hosted, ideally with someone competent looking after the server.

For larger trades businesses, multi-region or with serious compliance requirements, the answer is almost always n8n self-hosted on a Hetzner or Hetzner-equivalent VPS, with a paid maintenance retainer with someone who can keep it running. The combination of unlimited executions, full data control, and deep AI capability is hard to beat at scale.

One more thing. You do not have to pick one. Plenty of businesses I work with run Zapier for simple connectors, Make.com for the visual flows, and n8n for the AI heavy lifting. The bills add up, but if you are saving twenty hours of admin a week across the business, that is still a good trade.

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Frequently asked questions

My verdict

One closing thought. The tools are not the work. Picking the right platform saves you twenty hours a month. Building the right systems saves you two hundred. Spend the saved time on the systems, not on swapping platforms every six months.