Make.com Review: Cheaper Than Zapier, and Harder
Make counts more things than Zapier and charges far less for each. Only executed branches consume operations — which is where it stops being somewhat cheaper.
If you have read our Zapier review, you already know the shape of the problem: automation tools bill for something that multiplies faster than you expect, and the bill arrives before the understanding does. Make is the main alternative, and the interesting thing is that it does not solve that problem — it charges differently, and the difference matters enormously at volume and barely at all when you are starting out.
This review is mostly a comparison, because that is the actual decision people are making. Nobody researches Make in isolation; they research it because Zapier sent them an invoice they did not expect.
Operations against tasks
The two tools count differently, and understanding the difference is the whole review.
Zapier counts a task for each action step that completes. The trigger is free. Filters are free.
Make counts an operation for each module execution — and triggers count, and filters count.
On the face of it, Make’s counting is worse. Per unit it charges for more things. But the units cost dramatically less: roughly 10,000 operations on an entry plan around $10.59 a month, against roughly 2,000 tasks on Zapier’s comparable tier at $19.99. That is around five times the volume for about half the money, which comfortably swamps the difference in what gets counted.
The nuance that matters most for complex work: in Make, only the branches that actually execute consume operations. A ten-module scenario that routes early down a short path might use three or four operations per run, not ten. For workflows with real conditional logic, that compounds — and it is where Make’s advantage stops being “somewhat cheaper” and becomes “several times cheaper”.
Where the crossover actually is
At genuinely low volume — a handful of simple two- or three-step automations running a few dozen times a month — the two are close enough that price should not decide it. Zapier is easier to start with, has a larger integration library, and you will be finished sooner.
The crossover arrives with either volume or complexity. Thousands of runs a month, or workflows with multiple paths and conditions, and Make’s economics pull decisively ahead. Most people discover this in the wrong order: they build in Zapier, grow, get the invoice, and then migrate — which costs a weekend they had not budgeted either.
The visual builder, which is the other difference
Zapier presents a workflow as a vertical list of steps. Make presents it as a canvas of connected modules that you arrange spatially, with routers that split flow down multiple paths.
For a linear sequence, the list is clearer. For anything branching, the canvas is enormously better — you can see the whole shape of a scenario at once, including which paths exist and where they diverge. Once a workflow has three or four conditional routes, the list format stops communicating and the canvas keeps working.
The cost is the learning curve. Make asks you to understand data structures, mapping between modules, iterators and aggregators. That is not difficult, and it is more than “connect A to B”. People who describe Make as harder are describing something real.
Where it falls short
The integration library is smaller. Not small — smaller. Zapier’s breadth is its genuine moat, and if your business runs on something niche, checking that Make supports it is the first thing to do, before any pricing comparison.
It expects more of you. Data mapping, error handling and iteration are exposed rather than hidden. Powerful, and a real barrier for someone in operations who just wants a form to fill a spreadsheet.
Debugging is visual but not simple. You can inspect what each module received and returned, which is genuinely helpful, and diagnosing why an API rejected something is still slow.
Operation counting has its own traps. Iterators processing a hundred records consume operations per record. A scenario that looks small can be expensive if it loops over a large dataset.
What it does well
- Far more volume per pound than the obvious alternative
- Only executed branches consume operations
- Visual canvas that scales to genuinely complex logic
- Routers, iterators and aggregators built in
- Good visibility into what each module actually did
What to think about first
- Smaller integration library — check your apps first
- Steeper learning curve than the alternative
- Triggers and filters both consume operations
- Loops over large datasets get expensive quickly
- Overkill if you only need three simple automations
How it compares
| Option | Strongest at | Weakest at | Choose it if |
|---|---|---|---|
| Make | Cost at volume, branching logic, visibility | Learning curve, integration breadth | Your workflows are complex or high-volume |
| Zapier | Integration breadth, ease, speed to first result | Cost at volume | You need many apps connected quickly |
| n8n and self-hosted | Cheapest at scale, full control | You maintain the infrastructure | Volume is high and someone technical owns it |
| Writing it directly | No per-run cost at all | Build and maintenance time | One workflow dominates everything |
A pattern worth copying: keep whichever tool has your obscure integrations for the long tail, and move your two or three highest-volume workflows to whichever is cheapest. Splitting is usually better than committing entirely to one side.
Who it is for
Anyone whose automation bill has become uncomfortable. The clearest case, and the reason most people arrive.
Workflows with genuine conditional logic — different handling by customer type, region, order value, status. This is where both the canvas and the branch-based counting pay off at once.
Small technical teams who will happily spend an afternoon learning a tool that then costs a fifth as much to run.
It is the wrong choice if you need three simple automations and want them working this afternoon, if your critical app is only supported elsewhere, or if the person building them is not comfortable thinking about data structures.
Building automations?
Workflows usually move files around, and files usually need converting first. Our free browser-based tools handle that without uploading anything to a server.
Frequently asked questions
Is Make actually cheaper than Zapier?
What counts as an operation?
Is it harder to learn?
Does it support the apps I use?
Should I migrate from Zapier?
Why did my operations run out so fast?
The verdict
The right answer once automation stops being a hobby. It counts more things than Zapier and charges far less for each, and the branch-based counting makes complex workflows dramatically cheaper. Check your integrations first, budget an afternoon for the learning curve, and watch anything that loops. If you need three simple automations working today, stay where you are — this is the tool you move to, not the one you start with.
Sources and method
Plan pricing and operation allowances reflect published figures as of August 2026 and change regularly; both platforms adjust packaging often, so verify before committing. The comparison of counting rules is drawn from both providers’ documentation and independent pricing analysis rather than our own billing. We have not run these workflows ourselves and do not claim to have. Primary source: Make’s official site.