I’m trying to make a case for platform migration to our stakeholders, and I’m stuck on how to actually show the financial difference between Make and Zapier in a way that feels concrete rather than theoretical.
Everyone keeps pointing to generic comparison charts, but those don’t reflect our actual workflows. What I really need is a way to build the same automation in both platforms and show side-by-side how much it costs to run. The problem is doing this manually would take forever—I’d have to build, then rebuild, then calculate costs for each one.
I found some data suggesting there’s about 40% cost difference between the platforms for equivalent functionality, and higher savings at scale. But I can’t just show that number. My team needs to see it working.
Has anyone actually created these side-by-side prototypes? I’m wondering if there’s a way to generate workflow templates quickly that mirror what we’re currently doing in Make or Zapier, then use those to actually calculate the cost difference. Or am I overthinking this and should just do it the hard way?
We actually did this, and it was worth the time investment. But here’s the thing—we didn’t build the workflows manually in both platforms. That would have been misery.
Instead, we took three core workflows we were already running in Make. Then we documented each step in plain language—what’s coming in, what transformations happen, what goes out. We had someone else build those same patterns in Zapier using our descriptions. Took maybe a day total.
Then we ran both for a week in parallel on real data. Every single workflow ran exactly the same result, but the cost was visibly different. We tracked API calls, operations triggered, all of it.
The magic part was when we brought that side-by-side cost report to the team. Numbers on a slide don’t land. Side-by-side execution results with actual costs attached? That moves people.
The one thing we learned—don’t try to prototype every workflow. Pick three that represent your highest volume, most complex, and most unpredictable. That’s enough to show the pattern.
The challenge with manual side-by-side building is the effort required. However, if you’re looking for a quicker path, consider documenting your current workflows in a structured format first. Then use that documentation as a template to build prototypes. What matters most for your stakeholders isn’t perfection—it’s demonstrating cost difference on workflows that matter to your business. One approach that worked well involved selecting high-volume workflows, building prototypes on both platforms, and running them for one billing cycle to capture actual costs. The cost difference became obvious when comparing identical operations executed differently on each platform. The 40% savings claim becomes real when it’s your own workflows showing the delta.
The most effective approach is to prototype representative workflows from your existing system. Select workflows that cover different complexity levels. Build them on both platforms using identical logic, then execute them over a standardized period using actual data volume from your operations. This produces concrete cost data specific to your use case. Document the operation count, execution time, and total cost for each platform. Present the results alongside the platform documentation showing how each handles the workflow differently. This evidence-based comparison overcomes theoretical objections and provides a basis for TCO modeling.
Pick 3 key workflows. Build both platforms. Run simultaneously one week. Compare costs. Done. Your stakeholders will see the real difference immediately.
The fastest way to show this is with AI-assisted workflow generation. Instead of manually building in Make and Zapier separately, describe your workflows in plain language—what data comes in, transformations needed, outputs required. Let the platform generate prototype workflows that match those descriptions.
We’ve seen teams use this approach to build side-by-side comparisons in hours rather than days. Both workflows execute identically, but the cost tracking reveals where the platforms differ. Make charges per operation, Zapier charges per task—those models produce dramatically different costs for workflows with parallel processing or conditional logic.
Once you have working prototypes, run them against your actual data volume for one cycle. The 40% savings becomes real when it’s your workflows showing that delta.